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This chapter has benefited greatly from very thoughtful suggestions and encouragement from Brandon Yoder, Molly Scudder, Jacqueline Su, and Jennifer Silva. The chapter draws on faculty development resources produced at Yale-NUS College in collaboration with many colleagues, including Nancy Gleason, Joanna Lee, Lily Seah, Courtney Carter, Rachel Tan Wei Fen, Sahar Kazemini, Sara Amjad, and Matthew Stamps. I am indebted to many former and present mentors and colleagues at Yale-NUS College and the University of Virginia who fostered, deepened, and enabled my exploration into issues of academic inclusion and equity, including Deandra Little, Michael Palmer, Melissa Thomas-Hunt, Kyle Farley, Suyin Chew, Fiona Kanagasingam, Sara Amjad, D Dangaran, Jacqueline Su, Brian McAdoo, Joanne Roberts, and too many students to list by name. Thank you especially to Sara, D, Jackie, and Joanna for being particularly sage, humorous, and generous guides in helping me grapple with shifting expectations of higher education, the complex interplay of generation change, social justice, and academia, and to see the importance of faculty leadership regarding inclusion in the classroom and college.

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Yale-NUS College, Singapore, Singapore

Catherine Shea Sanger

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Correspondence to Catherine Shea Sanger .

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1. Yale-NUS College, Singapore, Singapore

Catherine Shea Sanger

2. New York University Abu Dhabi, Abu Dhabi, United Arab Emirates

Nancy W. Gleason

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Sanger, C.S. (2020). Inclusive Pedagogy and Universal Design Approaches for Diverse Learning Environments. In: Sanger, C., Gleason, N. (eds) Diversity and Inclusion in Global Higher Education. Palgrave Macmillan, Singapore. https://doi.org/10.1007/978-981-15-1628-3_2

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Inclusive Pedagogy and Universal Design Approaches for Diverse Learning Environments

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For educators in diverse contexts, it is not only socially virtuous but also pedagogically valuable to proactively anticipate and incorporate students' heterogeneous backgrounds, abilities, and interests into teaching and course design. This chapter highlights...

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Why teachers teach but kids don’t learn | Ben Richards | TEDxYouth@Haileybury

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On a Monday morning, you wake up to find your life in an organizational mess. The workload feels overwhelming as you drag yourself through your day, but you can't seem to get it all done. Now, the weight of tomorrow's tasks feels even more disorienting. This vicious cycle perpetuates the constant state of mental and physical exhaustion caused by chronic stress, known as burnout. If left untreated, it can deplete your mental and physical energies to the point of total shutdown.

Many of us get guilt trips for giving in to extra hours of sleep when we're tired. Studies suggest chronic stress and unhealthy work environments constantly keep the brain 'listening' for threats and preparing to respond to them. Like a computer running multiple background programs that consume its memory, constant effort occupies cognitive resources and leads to exhaustion and burnout.

"I think part of the confusion for the public is that burnout is something that we can't medically diagnose. It's an occupational phenomenon," says Anthony Montgomery, an organizational psychologist from Northumbria University in the U.K.

To understand and treat the condition effectively, scientists are looking into the biological correlates of burnout. They are finding burnout diminishes cognitive performance, making people exert themselves more to achieve normal performance and affecting their ability to remember common details about daily tasks.

Consistent Performance Under Stress

Burnout may occur in part from a prolonged stress response, an evolutionary survival mechanism for handling threats. For example, when primitive Homo sapiens saw a lion on the Serengeti, they instinctively ran faster to escape. This "fight-or-flight" response flooded their systems with stress hormones like adrenaline and cortisol, enabling them to recruit mental and physical resources to flee and save their lives. Once they reached safety, they could relax as their bodies quelled the stress response.

The same chemical response kicks in when you have a difficult meeting with your boss. But it may fail to subside as constant stressors to perform well and keep your job stay with you even after the meeting ends. Overexposure to these hormones over time dysregulates sleep and other homeostatic mechanisms in the body, making it more prone to burnout.

Montgomery conducted seven tests measuring how burnout impacts different aspects of cognitive function in a 2022 study. He reported that individuals with higher levels of burnout performed worse at tasks related to executive functions of the brain, which include planning, switching, and coordinating different tasks.

"Executive functions are like the brain's conductor, and the other functions are the musicians," explains Kaisa Hartikainen, clinical neurologist and brain scientist from the University of Tampere in Finland. She explained that while performing a well-practiced melody, you don't need the conductor, but with a more challenging task, you do. These functions involve the prefrontal cortex - the cognitive control center of the brain.

Waning Ability to Perform and Remember

In an October 2023 study, Hartikainen designed a versatile computer-based reaction time test that tapped into executive functions. Participants with electroencephalography (EEG) electrodes across their scalps pressed a button in response to whether a triangle was pointing up or down. The rule specifying which color indicated a need to respond and which to withhold a response changed frequently.

Intriguingly, she found the burnout group performed tests just as well as the control group. But EEG recordings suggested those in the burnout group were slower to transition from one cognitive process to another and recruited more task-related neurological resources than those in the control group to compensate for sluggish processing.

Laura Sokka, a clinical neuropsychologist from the Finnish Institute of Occupational Health, observed a similar effect in 2016. Sokka recorded EEGs of people while they performed visual tasks on a computer with varying memory loads. Participants were required to focus on visual memory tasks and respond to an occasional 'distractor' sound, which measured alertness. She found burnout depleted individuals' alertness to surrounding stimuli while they actively focused on completing tasks.

"We [also] observed a decrease in the working memory-related responses over the posterior scalp and an increase over the frontal areas," says Sokka. Activity across posterior brain regions reflects the use of working memory, the ability to remember short-term details about tasks, she explained. Moreover, increased frontal area responses meant extra consumption of cognitive resources in performing those tasks - but when burnout got worse, the frontal brain failed to fully rescue performance.

Looking at Burnout as a Physiological Disorder

"It's important that we find out what happens in the brain when we suffer from burnout so that we can show it's not just our opinions [or feelings], but there's something physiological behind those symptoms as well," said Sokka.

Contrary to popular belief, Montgomery says burnout is not just linked to our performance but starts as a social phenomenon. "The way we interact with people has a big influence on our well-being," he said. "And the degree to which we feel competent and in control is mediated by how well we get on with people around us. It's organizationally driven."

"We can't separate psychology from the brain. But we need objective measures to diagnose patients reliably and to study intervention strategies."

Society looks at burnout as a coping mechanism problem, says Hartikainen. But that's what people thought about depression until drug companies found it's a brain disorder they can treat. "If burnout lasts long enough, there are alterations in the brain structure and in the brain functions," she explained.

Hartikainen says severe burnout also affects our motivation and ability for interventional self-care, like yoga or meditation. When somebody experiences burnout, their stressful routine is typically hard to break out of, and they might lack the capability, energy, and executive function resources to engage in healthy activities.

She further stressed a message to workplaces and policymakers: Overloading the brain with unrealistic tasks and deadlines can cause a harmful cognitive strain, affecting people's productivity and quality of personal interactions. "We need to start looking at occupational burnout as a problem with the brain," she said.

About the Author

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Burnout Exhausts Brain Function and Physiology

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Burnout caused by chronic stress perpetuates a constant state of mental and physical exhaustion, hindering cognitive performance and everyday memory.

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What is Human Learning?  How do Humans Learn?

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Inclusive pedagogy seminar - University of Edingburgh

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Inclusive pedagogy seminar - University of Edingburgh

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TrillEDU:  Culturally Responsive Pedagogy...  | Jeffrey Dessources | TEDxNewJerseyCityUniversity

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Epistemic cognition and socio-scientific issues

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Epistemic cognition and socio-scientific issues

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Krista R. Muis*,

Marianne Chevrier,

Courtney A. Denton and

Kelsey M. Losenno

Department of Educational and Counselling Psychology, McGill University, Montreal, QC, Canada

When thinking critically about socio-scientific issues, individuals' expectations about the nature of knowledge and knowing, as well as their emotions when these expectations are met or not, may play an important role in critical thinking. In this study, we examined the role of epistemic emotions in mediating the effects of epistemic cognition on critical thinking when contending with conflicting information about genetically modified foods. Two hundred four university students completed a prior knowledge test on genetically modified foods, and then reported their epistemic beliefs about genetically modified foods. Participants then read a text that presented advantages and disadvantages of genetically modified foods, and reported the epistemic emotions they experienced during reading of that text. Participants then composed an argumentative essay about genetically modified foods, which were coded for critical thinking. Results from path analysis revealed that a belief in complex knowledge predicted less surprise and confusion, but more enjoyment. For the source of knowledge, a belief in the active construction of knowledge predicted less surprise and enjoyment. For justification for knowing, a belief that knowledge should be critically evaluated positively predicted curiosity, and negatively predicted confusion and boredom. Moreover, beliefs that knowledge about genetically modified foods is complex and uncertain positively predicted critical thinking. Confusion and anxiety also positively predicted critical thinking, whereas frustration negatively predicted critical thinking. Lastly, confusion mediated relations between epistemic beliefs and critical thinking. Results suggest complex relations between epistemic cognition, epistemic emotions, and critical thinking that have implications for educational practice as well as for future research on epistemic cognition and epistemic emotions.

Introduction

The information landscape in the 21st century is one of contrast. On the one hand, the Internet and social media provide an unprecedented wealth of diverse and accessible information from around the world. On the other hand, the structure of social networks and algorithmic filtering (e.g., news feeds and recommendations) have considerably narrowed the breadth of content that individuals consume, making it increasingly difficult to escape echo chambers and challenge one's views with new information. In this context, any topic is likely to become the object of controversy. Topics of personal and global relevance such as ways to combat climate change or the safety of infant vaccines appear to be politically controversial, dividing the public's opinion on what is considered accurate information, and stifling political action. To make informed decisions individually and collectively, the challenge lies in overcoming personal biases, and weighing the pros and cons of conflicting perspectives to reconcile views ( Noroozi et al., 2018). This is one aspect of the process known as critical thinking ( Kuhn, 2018).

There is little debate over the idea that society benefits when individuals are able to think deeply and critically about important issues (e.g., Dewey, 1933; Halpern, 2014). Educating people to become critical thinkers is of vital importance for the well-being of future generations. Accordingly, the Organization for Economic Cooperation and Development (OECD; Tremblay et al., 2012) has made teaching critical thinking a priority for higher education. However, empirical research shows that teaching critical thinking skills is arduous and often unyielding ( Abrami et al., 2008; Niu et al., 2013; Huber and Kuncel, 2015), with up to 45% of students completing post-secondary degrees lacking these essential skills ( Arum and Roksa, 2011). In light of these observations, many have suggested that to improve critical thinking outcomes, empirical work is needed to achieve a greater understanding of the underlying cognitive, motivational, and affective mechanisms that enable critical thinking ( Alexander, 2014; Greene and Yu, 2014; Bråten, 2016).

Socio-scientific topics are often characterized by the presence of opposing views that offer conflicting explanations to complex and multifaceted phenomena ( Levinson, 2006). Deciding what to believe or what to do about these topics requires that individuals engage with the underlying issues of knowledge that characterizes these topics: What counts as knowledge? How certain are the facts? Who can be trusted to provide a clear perspective on the topic? In other words, thinking critically about socio-scientific topics requires thinking about the knowledge- and knowing-related aspects of these issues ( Greene and Yu, 2014), a process termed epistemic cognition ( Greene et al., 2016). However, when engaged with complex and conflicting issues, individuals' expectations about the nature of knowledge and knowing may be challenged, and in turn elicit emotions such as surprise, curiosity, confusion, frustration, or anxiety ( Muis et al., 2018).

Common understandings of critical thinking assume that emotions have no role to play in critical thinking, except perhaps to introduce unwarranted bias ( Kahneman, 2011). However, knowing and feeling are closely related, and emotions may play a significant role in helping individuals disentangle the two ( Brun and Kuenzle, 2008). For example, Tiedens and Linton (2001) suggest that emotions can serve as information about the state of certainty. To illustrate, when presented with a knowledge claim, feelings of uncertainty may lead an individual to doubt the veracity of that claim. This uncertainty may then lead to a more thorough treatment of information and a greater attention to the quality of arguments over the source's characteristics. Nonetheless, little is known about how cognitive and affective processes interact to predict critical thinking. As such, the aim of the current study is to shed light on the role that epistemic cognition and epistemic emotions play when thinking critically about socio-scientific issues. In the following sections, we define the concepts of critical thinking, epistemic cognition, and epistemic emotions, and review theoretical and empirical work that informed the hypotheses of the current study.

Thinking Critically About Controversial Topics

Critical thinking is regarded as one of the most important skills that individuals can develop and is a fundamental aim of education ( Bailin and Siegel, 2003; Halpern, 2014). Though several definitions of critical thinking are offered in the literature (e.g., Kurfiss, 1988; Siegel, 1988; Facione, 1990; Scriven and Paul, 1996; Litman, 2008; Ennis, 2018), Ennis (2018) argued that they do not significantly differ from each other. Drawing from these definitions, we define critical thinking as purposeful, reasonable and reflective thinking that enables individuals to decide what to believe or what to do when faced with complex and conflicting issues ( Facione, 1990; Ennis, 2018). Following Kuhn (2018), we further define critical thinking as incorporating two key dimensions: inquiry (input), and argument (output).

According to Kuhn (2018), these two key dimensions of critical thinking can be delineated as an input phase and an output phase. Inquiry, the input phase, captures what an individual does as they are faced with complex and conflicting issues. Critical thinking during this phase includes skills like identifying pertinent information, evaluating claims, identifying counter-arguments, and critically analyzing and synthesizing information. These processes are carried out for the ultimate purpose of bringing this newly synthesized information to bear on a claim, which leads to the second dimension of critical thinking: argument.

Argument refers to a product that is constructed in written or oral form by an individual, which consists of a claim and one or more supporting reasons or evidence that are connected to the claim with warrants ( Toulmin, 2003). Argumentation refers to the dynamic process that captures what is done to create the argument ( Kuhn et al., 2015). As such, the output phase refers to the actions or processes of reasoning systematically in support of an idea, action or theory. Argumentation can be captured via dialogic methods ( Kuhn, 2018) or via argumentative essay writing ( Noroozi et al., 2018; Latifi et al., 2019; Valero Haro et al., 2019). For example, high-quality argumentative essays encompass a clear claim supported by evidence and reason, followed by acknowledgments of counter-arguments against the original claim, and integration of the arguments and counter-arguments which eventually lead to the final conclusion ( Noroozi et al., 2016). The goal is to provide strong evidence to support one argument over another by weakening the other position ( Kuhn, 2018).

Recent research has shown that critical thinking skills differ across academic disciplines ( Gordon, 2000) given that various disciplines have different argumentation structures, epistemologies, and rules and goals ( Noroozi et al., 2016). For instance, in nursing, critical thinking is concerned with rigorous investigation and reflection on all aspects of a clinical situation to decide on an appropriate course of action ( Simpson and Courtney, 2002). In engineering, critical thinking consists of considering assumptions in problem-solving, selecting appropriate methods for experiments, structuring open-ended design problems, and assessing social impacts ( Claris and Riley, 2012). When it comes to taking a position on a socio-scientific issue such as genetically modified foods, the task of critical thinking rests on identifying opposing arguments, assumptions, and evidence, evaluating the credibility, reliability, and relevance of claims, producing valid explanations and arguments, and making decisions or drawing valid conclusions ( Facione, 1990; Kuhn and Crowell, 2011; Noroozi et al., 2016; Latifi et al., 2019).

Bailin and Siegel (2003), as well as other philosophical theorists of critical thinking (e.g., Paul, 1990), emphasized the importance of generalizable abilities such as assessing reasons, evaluating claims, identifying underlying assumptions, and recognizing and applying valid forms of justification. They argue that what is "critical" about critical thinking is the use of a criterion-an epistemic criterion-for evaluating reasons and making sound judgments. The generalizable reasoning abilities described by Bailin and Siegel (2003) have long been studied by educational and developmental psychologists in the field of epistemic cognition (e.g., King and Kitchener, 2002; Chinn et al., 2011; Hofer and Bendixen, 2012; Greene et al., 2016). Epistemic cognition concerns individuals' thoughts and beliefs about the nature of knowledge and the process of knowing ( Hofer and Pintrich, 1997). From the perspective of educational development, Kuhn (1991, 1999) identified the development of epistemic cognition as perhaps the most central underpinning of critical thinking.

The Role of Epistemic Cognition in Critical Thinking

Epistemic Cognition

Epistemic cognition refers to how individuals vet, acquire, understand, justify, and use knowledge ( Greene et al., 2016). Specifically, individuals engage in epistemic cognition when they activate personal beliefs about the nature of knowledge and knowing (i.e., epistemic beliefs), define epistemic aims and criteria for knowing, and use evaluation and justification strategies to address issues of knowledge and knowing ( Chinn et al., 2011; Barzilai and Zohar, 2014; Muis et al., 2018). The vast majority of research on epistemic cognition has focused on epistemic beliefs, which refer to individuals' personal beliefs about the nature of knowledge and the process of knowing ( Hofer and Pintrich, 1997). Hofer and Pintrich (1997) proposed that epistemic beliefs comprise four dimensions: (1) the complexity of knowledge, ranging from the belief that knowledge consists of a simple accumulation of facts, to the belief that knowledge consists of a complex structure of interrelated propositions; (2) the uncertainty of knowledge, ranging from the belief that knowledge is certain and unchanging, to the belief that knowledge is tentative and evolving; (3) the sources of knowing, ranging from the view that knowledge resides in external authorities, to the view that individuals are knowers who actively construct knowledge; and (4) the justification for knowing, which addresses how individuals evaluate knowledge claims, from an unquestioning reliance on authorities, to the evaluation and integration of evidence and arguments from various sources.

Relations Between Epistemic Cognition and Critical Thinking

Epistemic Emotions and Critical Thinking

In educational psychology, one important line of research has concerned achievement emotions, that is, emotions that are tied to achievement activities (e.g., studying) or achievement outcomes (success or failure), such as anxiety, pride, or shame. However, not all emotions triggered in educational settings are related to achievement. Notably, Pekrun and Stephens (2012) distinguished topic emotions, social emotions, as well as epistemic emotions. Topic emotions relate to the content of learning (e.g., pride when learning about the American space conquest), whereas social emotions focus on relations to others in the learning context (e.g., compassion, gratitude; Weiner, 2007). Of particular relevance to critical thinking, epistemic emotions relate to the perceived quality of knowledge and the processing of information ( Pekrun and Stephens, 2012).

Surprise is likely to occur when individuals appraise new information as unexpected ( Meyer et al., 1997) or when they are unable to generate an explanation for the new information ( Foster and Keane, 2015). Mildly surprising information can lead to deep processing and integration of information, whereas information that is greatly surprising can be regarded as implausible and new information may fail to be integrated ( Munnich and Ranney, 2018). When information is not overly complex or perceived as relatively comprehensible, curiosity may arise. Litman (2008) proposes that epistemic curiosity arises in one of two forms: as a pleasant desire for information (i.e., interest-type curiosity), or as an unpleasant urge to obtain information to close the gap between what one knows and what one wants to know (e.g., deprivation-type curiosity; see also Loewenstein, 1994; Markey and Loewenstein, 2014). If the course of curiosity is followed, enjoyment may ensue, for instance, when validation or verification of a hypothesis is achieved ( Brun and Kuenzle, 2008), or when an epistemic aim is achieved ( Chinn et al., 2011; Muis et al., 2018). Confusion, on the other hand, follows from a lack of understanding when novel and complex information is perceived as incomprehensible ( Muis et al., 2018). Confusion can also arise in the face of severe discrepancies or contradictions, or from disruptions of goals or sequences of action ( D'Mello and Graesser, 2012). If an individual repeatedly fails to resolve the discrepancy causing confusion, frustration may arise ( D'Mello and Graesser, 2012; Di Leo et al., 2019; Munzar et al., 2021). Frustration can be described as a blend of anger and disappointment and, as such, can be an activating emotion when closer to anger, or deactivating if closer to disappointment ( Pekrun et al., 2002).

Consequences of Epistemic Emotions

Empirical Evidence

To date, little theoretical and empirical work has explored how epistemic cognition relates to epistemic emotions experienced when contending with complex or conflicting information. To address this gap, Muis et al. (2015) examined relations between epistemic cognition, epistemic emotions, learning strategies-including critical thinking-and learning achievement in the context of learning about climate change. They hypothesized that individuals with more constructivist beliefs would experience more positive emotions given the consistency between the to-be-learned content and their epistemic beliefs, whereas individuals with less constructivist beliefs would experience more negative emotions given the conflicting perspectives presented to them on the causes and consequences of climate change. Results from path analyses revealed that individuals who espoused more constructivist epistemic beliefs about the justification for knowing used more critical thinking strategies, and that this relationship was mediated by curiosity: The more learners believed that knowledge is justified by systematic inquiry and integration of sources of information, the more they experienced curiosity and, in turn, the more they used critical thinking and attained greater learning achievement. They also found that surprise negatively predicted critical thinking, but surprise was not predicted by any epistemic belief dimension.

In sum, significant relations between epistemic cognition, epistemic emotions, and critical thinking are suggested in the literature. However, the studies reviewed were predominately designed to assess relations between epistemic beliefs, epistemic emotions, and critical thinking during learning; they did not instruct participants to think critically. As Greene et al. (2014) argued, the study of epistemic cognition and critical thinking should involve the need to argue for, and justify, conclusions drawn across sources and perspectives. As such, to fully understand the role of epistemic cognition and epistemic emotions in critical thinking, more research is needed wherein individuals are asked to engage in critical thinking during a complex learning task. We address this gap in the literature.

The Current Study

On the basis of theoretical and empirical considerations from Muis et al. (2015, 2018), Pekrun ( Pekrun et al., 2002, 2017; Pekrun, 2006), as well as from the work of D'Mello and colleagues ( D'Mello and Graesser, 2012; D'Mello et al., 2014), we propose the following hypotheses: (1) Epistemic beliefs will predict critical thinking. Specifically, more constructivist beliefs will positively predict critical thinking. (2) Epistemic beliefs will predict epistemic emotions. Specifically, more constructivist epistemic beliefs will positively predict positive epistemic emotions, including interest-type curiosity and enjoyment, and negatively predict surprise and negative emotions, including confusion, frustration, anxiety and boredom. (3) Epistemic emotions will predict critical thinking. Specifically, surprise, curiosity, enjoyment, confusion, and anxiety will positively predict critical thinking, whereas frustration and boredom will negatively predict critical thinking. (4) Epistemic emotions will mediate relations between epistemic beliefs and critical thinking.

Materials and Methods

To test these hypotheses, we designed a study that specifically embedded a task that challenged individuals to critically evaluate knowledge claims from opposing perspectives, and to take a position on the topic in the form of an argumentative essay. The topic selected was genetically modified foods. Participants first took a knowledge assessment test to assess baseline knowledge about genetically modified foods, reported their epistemic beliefs about genetically modified foods, and then read a text on genetically modified foods that was comprised of two parts. The first part of the text was informative in nature and written in the style of a refutation text to ensure that all participants would engage in essay writing with good baseline knowledge about the nature of genetically modified foods. Refutation texts address commonly held misconceptions and directly refute them by presenting correct scientific explanations ( Sinatra and Broughton, 2011). The effectiveness of refutation texts for facilitating the revision of misconceptions has been well documented (see Tippett, 2010). The second part of the text was argumentative in nature and presented a series of points in favor for and against genetically modified foods. These points were supported by evidence that varied in strength and degree of certainty, but all information provided was valid. After having read the experimental text, participants wrote an argumentative essay of their choice in favor for or against genetically modified foods.

Procedure

Participants were recruited from three research-intensive universities from Eastern Canada (40.7%), Western Canada (26.5%), and the Southern United States (32.8%). Ethics approval was first obtained by the ethics review board for each participating university. To recruit participants, flyers were posted around university campuses, advertisements were posted on university websites, and subject pools from psychology courses were used. Participants provided informed consent to participate in the study and then completed a prior knowledge test and the Topic-Specfic Epistemic Beliefs Questionnaire ( Bråten and Strømsø, 2009) to assess epistemic beliefs about genetically modified foods. Participants were then randomly assigned to read a version of the text that presented the advantages of genetically modified foods first ( n = 102), or the disadvantages of genetically modified foods first ( n = 102). After reading, participants completed the Epistemic Emotions Survey ( Pekrun et al., 2017) to capture the epistemic emotions they experienced while reading. Lastly, participants composed an argumentative essay and then completed a demographics questionnaire to conclude the study. Participants were compensated for their time with $15 cash, a $10 gift card, or course credit, depending on the university from which the participant was recruited. Figure 1 provides an overview of the procedure.

Figure 1. Overview of procedure.

Participants

Two hundred four university students from three universities across Canada and the United States participated. See Table 1 for a breakdown of all demographic characteristics of the sample by gender, year in university, race, and first language spoken. No differences between groups were found on any of the variables of interest as a function of university location, gender, year in university, or first language spoken. Participants studied a variety of domains (e.g., business administration, social sciences, natural sciences, computer sciences, psychology, linguistics, and arts) and reported an average GPA of 3.24 out 4.0 (SD = 0.55). Participants from the Western Canadian institution reported significantly lower GPA ( M = 2.97, SD = 0.67) than participants from the Eastern Canadian ( M = 3.43, SD = 0.44) and Southern American institutions [ M = 3.30, SD = 0.39; F(2, 124) = 10.02, p < 0.001]. Overall, no significant differences were observed between Canadian ( M = 3.23, SD = 0.60) versus American ( M = 3.30, SD = 0.39) participants in terms of reported GPA. Participants were 21.46 years of age on average (SD = 4.28).

Table 1. Demographic characteristics of the sample.

Materials

Experimental Text

Participants were given a text that first presented factual information about genetically modified foods, followed by a portion that presented advantages and disadvantages of genetically modified foods. The first half of the text was adapted from Heddy et al. (2017) and focused on debunking four common misconceptions about genetically modified foods by presenting accurate scientific explanations. Erroneous conceptions included the notion that genetically modifying food is the same process as cloning, that it involves injecting hormones into a plant or animal, that it only occurs in laboratories by scientists, and that it is the product of contemporary scientific research.

The second part of the text presented four advantages of, and four criticisms against genetically modified foods. It was written by the first author and adapted from content published by the Canadian Standards Association ( Whitman, 2000). To counterbalance a possible effect of text order with regard to the presentation of the advantages and disadvantages of genetically modified foods, two versions of the text were created: one version presented the advantages first, followed by the disadvantages, and the other version presented the disadvantages first, then the advantages. The text contained 1,295 words in total, including the informative and argumentative sections, with a Flesch-Kincaid index of grade 12.7 and a Flesch Reading Ease index of 37.7 (see Kincaid et al., 1975).

Prior Knowledge Test

Participants' prior knowledge about genetically modified foods was measured with a 10-item multiple-choice test adapted from Heddy et al. (2017). Each question presented four possible choices and participants were instructed to select the best answer. Examples of items include: "Cross-pollination is considered to be a process through which plants can be... (a) genetically modified. (b) cloned. (c) hormone injected. (d) exactly replicated." "Methods that are NOT used in producing genetically modified foods include which of the following? (a) Gene cloning methods. (b) Hormone injection. (c) Cross pollination. (d) selective pollination." Correct answers were given a score of 1 and incorrect answers were given a score of 0. Scores were then added to create a total sum, then a percentage, which was used as an indicator of prior knowledge.

A confirmatory factor analysis (CFA) was conducted to examine the factor structure of the prior knowledge test using Mplus Version 7.11 ( Muthén and Muthén, 2015). The initial model revealed a poor fit, χ ² = 103.94, df = 35, p < 0.001, RMSEA = 0.05, and CFI = 0.88. An analysis of item loadings revealed low loadings for two items; therefore, these items were deleted. The final model (with the remaining eight items) resulted in a good fit, χ ² = 64.14, df = 20, p < 0.01, CFI = 0.94 and RMSEA = 0.04. Cronbach's reliability coefficient was acceptable, α = 0.79.

Epistemic Beliefs

Epistemic beliefs about genetically modified foods were measured with a version of the Topic-Specific Epistemic Beliefs Questionnaire (TSEBQ; Bråten and Strømsø, 2009) adapted to this topic. The TSEBQ comprises 24 items that participants rate on a 7-point Likert scale ranging from "strongly disagree" to "strongly agree." Four dimensions of epistemic beliefs were measured: six items assessed beliefs about the complexity of knowledge (e.g., "Knowledge about genetic modification is primarily characterized by a large amount of detailed information"), six items assessed beliefs about the uncertainty of knowledge (e.g., "Certain knowledge about genetic modification is rare"), five items assessed beliefs about the source of knowing (e.g., "I often feel that I just have to accept that what I read about genetic modification problems can be trusted"), and seven items assessed beliefs about justification for knowing (e.g., "When I read about issues concerning genetic modification, I evaluate whether the content seems logical").

A CFA was conducted to examine the factorial validity of scores for the instrument using Mplus7. The initial model (with 24 items) showed poor fit, χ ² = 419.25, df = 246, p < 0.001, RMSEA = 0.06, and CFI = 0.78. Due to low loadings, 10 items were deleted: three items were removed from the uncertainty subscale, three from the complexity subscale, two from the source subscale, and three from the justification subscale. The final model (with 14 dimensions) resulted in good fit, χ ² = 102.31, df = 71, p < 0.001, RMSEA = 0.05, and CFI = 0.93. Cronbach's reliability coefficients were acceptable, α = 0.79 for the uncertainty subscale, α = 0.78 for the complexity subscale, α = 0.78 for the source subscale, and 0.76 for the justification subscale.

Epistemic Emotions

Epistemic emotions experienced while reading the experimental text were measured with the Epistemic Emotions Survey (EES; Pekrun et al., 2017). This questionnaire comprises 21 items that measure seven epistemic emotions, including: surprise, curiosity, enjoyment, confusion, frustration, anxiety, and boredom. Each item consisted of a single word describing one emotion, with three descriptors per emotion (e.g., "anxious," "nervous," and "worried" measured anxiety). Participants rated the intensity of their emotional responses to the text using a five-point Likert scale ranging from "Not at all" to "Very strong." The scores for the descriptors of each emotion were averaged to represent each emotion. Cronbach's reliability coefficients were acceptable, α = 0.78 for surprise; α = 0.76 for curiosity; α = 0.84 for enjoyment; α = 0.77 for confusion; α = 0.83 for frustration; α = 0.85 for anxiety; and α = 0.80 for boredom.

Essay

To assess critical thinking, we chose to measure argumentation, the second key dimension of critical thinking ( Kuhn, 2018). Accordingly, participants were instructed to compose an argumentative essay of their choice in favor for or against genetically modified foods and to justify their position. Instructions were as follows: "Based on the content you just read, write a brief (2-3 paragraphs) argument for or against genetically modified foods. Explain how you came to form and justify your point of view. You can refer back to the text you read, and include your judgment of the arguments, evidence, and conclusions it presented." Critical thinking was assessed using a coding scheme developed for this purpose.

Coding critical thinking in essays

A coding scheme was developed by the second author to assess critical thinking in argumentative essays. The coding scheme was informed by the work of Facione and Facione (2014), which outlines the development and use of a scoring rubric for evaluating critical thinking (see Table 2 for full descriptions and examples). Five elements were targeted via the coding scheme: taking a position, presenting supportive arguments in favor of a position, acknowledging an alternative perspective, evaluating the validity of claims on both sides of the issue, and integrating arguments from opposing viewpoints into a coherent perspective or conclusion. One point was attributed if participants took a position; no points were attributed if participants did not take a position. One point was attributed if participants supported their position with valid arguments, evidence, facts or reasons; no points were attributed if no arguments were presented in support of their position or if arguments were invalid. One point was attributed if participants acknowledged and presented an alternative perspective on genetically modified foods; no points were attributed if participants only presented arguments in favor of one perspective. One point was attributed if participants evaluated claims or arguments before accepting them as valid; no points were attributed if participants expediently accepted or dismissed claims or arguments without evaluation. Lastly, one point was attributed if participants reconciled or integrated perspectives; no points were attributed if the conclusion was one-sided, categorical, or failed to acknowledge the validity of any counter-argument. Points were summed to create a total score on five.

Table 2. Coding scheme for critical thinking in argumentative essays.

The coding scheme was tested by the second and third authors using 31 transcripts (15% of the sample), and inter-rater reliability for the first round was established at 75%. All disagreements were resolved through discussion and were used to update the coding scheme. A second round of coding was performed with an additional 31 transcripts (new 15% of the sample), and final inter-rater reliability was established at 88%. The second author then coded the remainder of the essays.

Results

Preliminary Analyses

Prior to conducting full analyses, all variables were inspected for skewness and kurtosis. Based on Tabachnick and Fidell's (2013) recommendations, acceptable ranges of ±3 for skewness and ±8 for kurtosis were used to investigate the relative normality of the distributions for each variable. Analyses revealed that the distributions for confusion (4.45), frustration (7.28), anxiety (3.73), and boredom (6.10) were positively skewed; however, given the nature of emotions, normal distributions for these variables are unlikely, so the variables were retained for subsequent analyses. Examination of text order (i.e., advantages of genetically modified foods first or disadvantages of genetically modified foods first) showed no or order effects on any variable. Descriptive statistics for all variables are presented in Table 3 and correlations between variables are presented in Table 4.

Table 3. Descriptive statistics for variables.

Table 4. Correlations between variables.

To check for univariate outliers, each variable was converted to a standardized z-score. Any z-scores exceeding critical cut-offs of ±3.3 was considered an outlier ( Tabachnick and Fidell, 2013). Results revealed univariate outliers for justification ( n = 2, z = −3.36 to −5.53) and frustration ( n = 1, z = 3.51). Instead of deletion, all cases were retained given the values were not extreme and did not exceed more than 2% of cases for each variable (see Cohen et al., 2003). To check for multivariate outliers, Mahalanobis distances were calculated based on a χ distribution with 12 degrees of freedom and a critical cut-off point of 32.91 (α = 0.001; see Meyers et al., 2017; Tabachnick and Fidell, 2013). No multivariate outliers were found.

Mediation Path Analysis

To test the hypothesized mediation model, we conducted a mediation analysis using Hayes (2018) PROCESS macro for SPSS, which is recommended for testing complex mediational models and maintaining high power while controlling for Type I error rates (see Hayes, 2018). Bootstrap sampling was used (with 10,000 bootstraps), which does not require assumptions of normality and which was appropriate given a few slightly skewed variables. A power analysis using ( Faul and Erdfelder, 1992; for a full description, see Erdfelder et al., 1996) with power (1-β) set at.80 and α set at 0.05 revealed a required sample size of 218 for the present analysis. Given a sample of 204, the analysis would be underpowered. As such, we adjusted the level of the confidence intervals to 90% for the bootstrap sampling, which required a sample size of 180. The final model is depicted in Figure 2 with standardized effects.

Figure 2. Final model with standardized coefficients. Only significant paths are represented. * p < 0.05; ** p < 0.01.

We first examined the total effects model, which expresses the sum of the direct and indirect effects of epistemic beliefs on critical thinking scores to determine the predictive relations between epistemic beliefs and critical thinking, independent of the effects of mediational variables. We next calculated the direct effects of epistemic beliefs on epistemic emotions, the direct effects of epistemic beliefs on critical thinking, and the indirect effects of epistemic beliefs on critical thinking via epistemic emotions. At each step, we controlled for the effects of prior knowledge.

Complexity beliefs (β = 0.16, SE = 0.06, t = 2.06, p = 0.04) and uncertainty beliefs (β = 0.14, SE = 0.07, t = 2.07, p = 0.04) were direct predictors of critical thinking. For direct effects of epistemic beliefs on epistemic emotions, complexity beliefs predicted surprise (β = -0.24, SE = 0.07, t = −3.52, p = 0.0005), enjoyment (β = 0.15, SE = 0.07, t = 2.04, p = 0.04) and confusion (β = −0.28, SE = 0.07, t = −4.02, p = 0.0001); source beliefs predicted surprise (β = −0.15, SE = 0.07, t = −2.21 p = 0.02), and enjoyment (β = −0.18, SE = 0.07, t = −2.59, p = 0.03); and justification beliefs predicted curiosity (β = 0.14, SE = 0.07, t = 2.02, p = 0.04), confusion (β = −0.14, SE = 0.07, t = −2.01, p = 0.04), and boredom (β = −0.15, SE = 0.06, t = −2.02, p = 0.04). For the direct effects of epistemic emotions on critical thinking, confusion (β = 0.24, SE = 0.10, t = 2.30, p = 0.02) and anxiety (β = 0.18, SE = 0.10, t = 2.17, p = 0.03) were significant positive predictors, and frustration (β = −0.24, SE = 0.10, t = −2.40, p = 0.01) was a significant negative predictor of critical thinking. Finally, for indirect effects of epistemic beliefs on critical thinking via epistemic emotions, results showed that the effect of complexity beliefs on critical thinking was mediated by confusion, with a point estimate of −0.07 and bias corrected bootstrapped confidence interval (90%) of −0.12 to −0.02.

Two Illustrative Cases

The following cases reflect examples of how epistemic beliefs and epistemic emotions related to critical thinking for different individuals. These cases were chosen as they represent individuals with similar demographic profiles and levels of prior knowledge about genetically modified foods, but whose epistemic beliefs and emotions as well as critical thinking skills present an interesting contrast.

Case 1

Case 1 was a 24-year-old female in the 3rd year of an environmental sciences degree with a self-reported GPA representing an academic average between 80-84% (or A-). Her prior knowledge about genetically modified foods was below average (test score = 20%). She reported epistemic beliefs that were slightly less constructivist than average on the complexity subscale (score = 3.33/7.00), less constructivist than average by more than two standard deviations on the uncertainty subscale (score = 2.83/7.00), and less constructivist than average on the source subscale by one standard deviation (score = 2.60/7.00). For epistemic emotions, she reported slightly less confusion than average (score = 1.33/5.00), slightly more frustration than average (score = 2.00/5.00), more anxiety than average by more than one standard deviation (score = 3.33/5.00), and more boredom than average by more than a standard deviation (score = 3.00/5.00).

Our analysis of Case 1's essay indicated little critical thinking (score = 2/5) and reflected a one-sided view of genetically modified foods. Her essay included a well-positioned positive stance on genetically modified foods ("Genetically modified food is the way of the future") as well as a few arguments in its support ("For instance, rice can be GM to have more nutrients, thus preventing millions of people from starvation" and "Already there are many third world nations that have hungry and malnourished populations. Genetically modified foods can help them by modifying their staple of food grown there.") However, Case 1 did not identify nor engage with arguments from the opposing position. No arguments against genetically modified foods were specifically identified. Only the fact that genetically modified foods could have detrimental health effects was alluded to in a sentence that quickly dismissed the counter-argument with a statement that was justified by means of not having directly observed any opposing evidence: "Every day, there are hundreds of foods being bought in grocery stores that are GM and so far there have been no real significant downside to eating it (detrimental). In fact, I'm sure you've even eaten something that's been GM this week!" Further, no conclusions were reached that hinted to an integration or reconciliation of perspectives. A conclusive statement was offered that solidified a position in favor of genetically modified foods ("Our knowledge is meant to be passed on to others so they can benefit from the fortunes that we are so lucky to have."). Overall, Case 1 is representative of individuals with less constructivist epistemic beliefs who did not present elaborate critical thinking. Further, though prior knowledge was low, Case 1 reported little confusion. She also reported high levels of frustration, anxiety, and boredom. For Case 1, it may be the case that the presentation of opposing arguments led to more frustration and anxiety given her less constructivist beliefs about genetically modified foods. That is, consistent with Muis et al. (2018), the nature of the information presented to her was in stark contrast to her epistemic beliefs, thus triggering negative epistemic emotions. She expected knowledge about genetically modified foods to be certain and simple but was presented as uncertain and complex. This increase in frustration and anxiety may have then led her to focus solely on one side of the argument, resulting in lower performance on the task.

Case 2

Case 2 was a 24-year-old female in the 2nd year of a degree in psychology. She reported a GPA representing an academic average between 85-89% (or A). Akin to Case 1, Case 2's prior knowledge about genetically modified foods was below average (test score = 20%). She reported epistemic beliefs that were more constructivist than average by more than one standard deviation on the uncertainty subscale (score = 5.00/7.00), more constructivist than average by more than one standard deviation on the uncertainty subscale (score = 5.83/7.00), and slightly less constructivist than average on the source subscale (score = 4.00/7.00). For epistemic emotions, she reported more confusion than average by more than one standard deviation (score = 3.00/5.00), more frustration than average by more than one standard deviation (score = 2.67/5.00), slightly more anxiety than average (score = 3.00/5.00), and slightly less boredom than average (score = 1.67/5.00).

Case 2's essay reflected an integrated perspective on genetically modified foods. Case 2 first assumed a cautiously positive stance on genetically modified foods: "Though the use of genetically modified foods may present possible solutions to certain of the world's problems, there is insufficient research on the matter and, more specifically, evidence supporting its proposed benefits." She then presented some of benefits of genetically modified foods: "Genetically modified foods have been proposed to aid in addressing the many problems tied to the ever-growing population of the world, including malnutrition and land usage" and then exposed some criticism, pointing to a lack of supportive evidence, "However, these are mere propositions based on hypothetical scenarios, i.e., there is no evidence to show that certain foods can be genetically modified to provide additional vitamins and minerals - what has been proposed is a hypothetical solution." The same pattern was repeated with the opposing perspective: Case 2 first presented arguments against genetically modified foods: "Meanwhile, a growing body of research is pointing to evidence supporting its harmful side-effects. For instance, a causal link was found between the presence of the modified B.t. corn and death of monarch butterfly caterpillars. Research has also shown that GM fed rats had digestive tracts that differed to rats fed unmodified foods", then identified limitations, "While research on the effects of GM foods in humans is still rather limited, such animal studies are an important start." A full reconciliation of perspectives was not reached, but a conclusion was drawn that followed the aforementioned evaluations and identified a lack of evidence as a halt to fully embracing the benefits of genetically modified foods: "Overall, the research on genetically modified foods remains inconsistent and limited. There is insufficient evidence to show that the benefits of genetically modified foods could outweigh its costs." It may be the case that an optimal level of anxiety and confusion, combined with low boredom, motivated Case 2 to exert efforts to analyze each perspective on genetically modified foods to better understand their characteristics and nuances, resulting in observable critical thoughts.

Discussion

Socio-scientific issues such as genetically modified foods are often depicted as controversial by influencers who are either in favor or against the propositions of scientific expertise. In the face of such issues, successful critical thinking occurs when individuals purposefully decide what to believe or what to do by evaluating knowledge claims and reconciling opposing views, taking relevant evidence and context into account ( Ennis, 1987; Facione, 1990). Prior theoretical and empirical work suggests that individuals' thoughts and beliefs about the nature of knowledge and knowing play an important role in supporting critical thinking. However, little is known about the role that knowing-related emotions may play in critical thinking and the effects of epistemic cognition on such thinking. We hypothesized that epistemic cognition supports critical thinking via epistemic emotions.

This research contributes to the literature on epistemic cognition and epistemic emotions by empirically testing Muis et al. (2015) and Muis et al. (2018) model of epistemic cognition and epistemic emotions, and by providing new findings concerning relations between epistemic cognition, epistemic emotions, and critical thinking. Further, this study is the first to explore these relations in the context of an elaborate critical thinking task where participants were asked to decide what to believe about a socio-scientific issue on the basis of conflicting evidence. Specifically, results showed that a belief in complex and uncertain knowledge directly predicted critical thinking (Hypothesis 1). Complexity, source, and justification beliefs also predicted epistemic emotions, including surprise, curiosity, enjoyment, confusion, and boredom (Hypothesis 2), and epistemic emotions, confusion, frustration, and anxiety, in turn predicted critical thinking (Hypothesis 3). Lastly, confusion mediated relations between epistemic beliefs and critical thinking (Hypothesis 4). Next, we interpret each of the results described above and conclude with a discussion of limitations and directions for future research.

The Role of Epistemic Beliefs When Facing Socio-Scientific Issues

In support of our hypothesis, more constructivist epistemic beliefs about the nature of knowledge (complexity and uncertainty dimensions) significantly predicted critical thinking, indicating that the more individuals believed in complex and tentative knowledge, the more they presented support for arguments, acknowledged alternatives, evaluated claims, and drew balanced conclusions. However, epistemic beliefs about the nature of knowing (beliefs about the sources of, and justification for knowing) were not significantly related to critical thinking. It should be mentioned that it is frequent in epistemic belief research that not all belief dimensions are salient in a given situation, depending on the nature of the task ( Hammer and Elby, 2002; Greene et al., 2010). Similar to this study, Strømsø et al. (2011) examined relations between epistemic beliefs and undergraduate students' evaluations of documents' trustworthiness and found that source beliefs significantly predicted evaluation of conflicting claims, but justification beliefs did not contribute significantly to trustworthiness scores.

For our study, three dimensions of epistemic beliefs were found to have direct effects on five epistemic emotions. In particular, in line with hypotheses, the more individuals believed that knowledge about genetically modified foods is complex, the less likely there were to experience surprise and confusion, and the more likely they were to experience enjoyment. This supports the notion that epistemic beliefs shape individuals' assumptions about the nature of knowledge ( Bromme et al., 2010), such that those who expected knowledge about genetically modified foods to be simple may have experienced dissonance related to the complex nature of information presented in the text. Individuals who expected knowledge to be complex, when presented with conflicting information, were not surprised by this conflict nor were they confused about the conflicting information. Moreover, consistent with hypotheses, more constructivist complexity beliefs predicted more enjoyment when reading about advantages and disadvantages of genetically modified foods.

Additionally, those who viewed personal interpretations and judgments as the main sources of knowledge about genetically modified foods experienced less surprise but also less enjoyment during learning when reading contradictory perspectives about the value and usefulness of genetically modified foods. This result is consistent with findings from Strømsø et al. (2011) who found that the more students viewed the self as a meaning maker, the less they trusted texts written by climate change experts. Similarly, Kardash and Scholes (1996) found that the less students believed in external authority as a source of knowledge, the stronger their opinions about the HIV-AIDS relationship.

Moreover, when individuals are presented with conflicting information about a topic, it is beneficial to evaluate and integrate evidence and arguments. That is, individuals who believed that knowledge is justified through a process of critical evaluation and integration of information experienced more curiosity and less confusion and boredom compared to individuals who believed in an unquestioning reliance on authorities. In the case of the texts presented to participants in this study, authorities reported both pros and cons about genetically modified foods. Under this condition, individuals are likely more confused given that they may be uncertain as to which authority to trust, may find the task too challenging, and then experience greater boredom. However, as previous research has shown ( D'Mello et al., 2014), confusion can be beneficial for learning by increasing critical thinking. We describe relations between emotions and critical thinking next.

The Role of Epistemic Emotions in Critical Thinking

Consistent with the contention that confusion can be beneficial for complex cognitive tasks, confusion was found to be a positive predictor of critical thinking. Also consistent with hypotheses, confusion was negatively predicted by complexity and justification beliefs and, as such, fully mediated relations between these beliefs and critical thinking. Although the full mediation effect seems to suggest that more constructivist beliefs are detrimental to critical thinking via decreased levels of confusion, we suggest that effects revealed here are more complex than they appear. It might be the case that compared to individuals with less constructivist epistemic beliefs, those who espouse more constructivist beliefs experience less confusion related to the complex nature of genetically modified foods knowledge, but nevertheless perceive discrepancies between perspectives that can trigger lower levels of confusion associated with beneficial effects. Indeed, philosophers such as Morton (2010) and Elgin (2008) have argued that epistemic emotions such as surprise and confusion can draw attention to the object of the emotion, which can lead to deep processing of information as well as metacognitive self-regulation ( Muis et al., 2015). Moreover, two of the epistemic belief dimensions directly positively predicted critical thinking. As such, it may be the case that individuals with more constructivist epistemic beliefs experience less confusion, but still directly engage in critical thinking given that they believe that knowledge must be critically evaluated and that perspectives must be weighed before coming to a specific conclusion on an issue.

In terms of positive emotions, in this study, we did not find significant predictive relationships between enjoyment and critical thinking. Therefore, the current results do not replicate prior work by Muis et al. (2015), who found curiosity to predict critical thinking. Muis et al. (2018) proposed that curiosity and confusion are similar in that they both result from surprise triggered by dissonance, incongruity, or uncertainty. They proposed that the complexity of information or of a task predicts whether curiosity or confusion follows surprise. Specifically, they argued that when complexity is high, surprise may turn into confusion, whereas curiosity is more likely to ensue in cases where discrepancies can be easily revolved. In the current study, it appears that curiosity and confusion highly co-occurred. More research is needed to better understand how individuals experience curiosity and confusion when trying to determine what is true or what to believe about a complex and controversial topic.

Educational Implications

The results obtained in the present study have several implications for educational interventions aimed at increasing critical thinking about socio-scientific issues. First, findings support the notion that knowledge- and knowing-related issues should be highlighted and discussed in educational settings, with the aim of developing more constructivist forms of epistemic cognition. Notably, discussions surrounding the complex and tentative nature of scientific knowledge may be beneficial to shaping individuals' expectations about the issues they will be called upon to reflect and act on during their lifetime. Barnett (2004), a prominent philosopher of higher education, has described the mission of university education as preparing students for a complex and uncertain future: For individuals to prosper, make decisions, and come to a position of security amid multiple interpretations, individuals must come not only to learn for uncertainty, but to learn to live with uncertainty. Barnett contends that no risk-free curricular approach can achieve this; instead, he calls for a curriculum that aims at educational transformation through exposure to dilemmas and uncertainties. This may include, for instance, confronting students with the limits of knowing in a field and with the limitations of the field as such. In addition to uncertainty- and complexity-focused curricula, Muis et al. (2016) proposed that to achieve epistemic change, epistemic climates are needed that involve constructivist pedagogical approaches (e.g., inquiry-based learning, apprenticeship, collaborative learning, knowledge building, and communities of practice), decentralized authority structures, open-ended assessment practices, and appropriate levels of teacher support, as students experience the sometimes difficult process of belief change.

Finally, it is also important to note that all students could benefit from being taught how to write argumentative essays; the task we used to capture the output dimension of critical thinking ( Kuhn, 2018). As previous research has shown, undergraduate and graduate students typically perform below the expected level for argumentative essay writing tasks ( Kellogg and Whiteford, 2009). Our sample was no different, with an average of just over 53%. Clearly, beyond focusing on epistemic cognition and epistemic emotions in the classroom, students could benefit from direct instruction on argumentative writing. One method that has been effective in improving students' argumentative essay writing is via scaffolding through adaptive fading ( Noroozi et al., 2018), and worked examples and peer feedback ( Latifi et al., 2019; Noroozi and Hatami, 2019; Valero Haro et al., 2019). Indeed, as Muis (2007) argued, it may be the case the teaching students these skills may also help to improve their epistemic cognition. Of course, one could also argue that we measured only one key dimension of critical thinking. Future research should also measure the inquiry dimension of critical thinking to assess whether results from our study replicate. Importantly, relations between constructs may differ depending on how critical thinking is measured. We address limitations next.

Limitations and Future Directions

Several concerns may limit the results presented herein. First, the analysis used correlational associations of the study variables over time but did not experimentally manipulate the predictor variables. As such, future research should complement the approach used here with experimental studies. However, this may be easier to do with emotions, which can to some extent be manipulated experimentally, than with more stable epistemic beliefs. A second limitation concerns the rubric employed to capture critical thinking in essays. Specifically, we opted for a quantitative approach to coding critical thinking by attributing one point for the presence of each component of critical thinking. However, a weighted coding scheme or a holistic rubric are two other modes of critical thinking assessment that include qualitative elements of analysis that could have yielded different results. Third, epistemic cognition and epistemic emotions were measured via self-report, which also have inherent limitations (see, for example, DeBacker et al., 2008). Therefore, future research is needed to replicate the findings presented here using alternative methods, which we delineate below.

The current findings have important implications for future research on epistemic cognition and epistemic emotions. Specifically, to fully understand how epistemic cognition supports critical thinking, future research should explore the role that other facets of epistemic cognition play in mediating this relationship. For instance, how do individuals' knowledge of epistemic strategies shape critical thinking, and do these abilities influence the arousal of epistemic emotions in the face of complex and conflicting information? And how might epistemic aims moderate these relations? Prior work has shown that these other epistemic facets play a significant role in epistemic emotion arousal and researchers have called for more research on epistemic cognition that conceptualize and operationalize the construct beyond the sole notion of epistemic beliefs ( Greene et al., 2016).

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by McGill University Research Ethics Board. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

KM developed the larger program of study, designed the materials and research questions, cleaned and analyzed the data, and wrote the manuscript. MC helped develop the research questions, collected the data, cleaned the data, developed the coding scheme for the essays, coded the essays, analyzed the data, and wrote the manuscript. CD helped collect the data, coded the essays, and helped in writing the manuscript. KL helped collect the data and wrote the manuscript. All authors contributed to the article and approved the submitted version.

Funding

Funding for this work was provided by a grant to KM from the Social Sciences and Humanities Research Council of Canada (435-2014-0155), and from the Canada Research Chair program. Correspondence concerning this article can be addressed to KM, Department of Educational and Counselling Psychology, Faculty of Education, McGill University, 3,700 McTavish Street, Montreal, QC, H3A 1Y2, or via email at krista.muis@mcgill.ca.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Footnotes

References

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Epistemic Emotions and Epistemic Cognition Predict Critical Thinking About Socio-Scientific Issues

# data[].attributes.attachment_link.description
When thinking critically about socio-scientific issues, individuals' expectations about the nature of knowledge and knowing, as well as their emotions when these expectations are met or not, may play an important role in critical thinking. In this study, we examined the role of epistemic emotions in mediating the effects of epistemic cognition on critical thinking when contending with conflicting information about genetically modified foods.

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Positioning through epistemic cognition in higher education

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Positioning through epistemic cognition in higher education

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doi: 10.1007/s10734-023-01048-2. Online ahead of print.

Affiliation

¹ Newcastle Business School, Northumbria University, Newcastle Upon Tyne, UK.

David William Stoten . High Educ (Dordr).

doi: 10.1007/s10734-023-01048-2. Online ahead of print.

Affiliation

¹ Newcastle Business School, Northumbria University, Newcastle Upon Tyne, UK.

Abstract

Teaching and learning in higher education is informed by a multitude of conditioning factors, not least the values systems and outlook of academics. Understanding the epistemological positioning taken by academics in relation to teaching and learning is therefore important if we are to make judgments about how we educate now, and could do so in the future. Developments in educational theory and digital technology have opened-up new possibilities for the ways in which students learn, and to a degree this has been accelerated by the responses from universities to the COVID-19 pandemic. How then should we conceive the future? Heutagogy is one of a number of theoretical approaches that has attracted interest from those who wish to see greater student control over the learning journey- but how widespread is this view amongst academics? This paper reports on a qualitative study in which 12 academics in an English Business School were asked to describe their views on teaching and learning, which we can encapsulate through the concept of epistemic cognition. The findings infer that there is little epistemological underpinning for heutagogy and that if academics are going to innovate, then additional resource and professional development should be put in place to support epistemic reflexivity, and a shift in their epistemological positioning. The paper conceptualises academics' positioning through a typology of epistemic views.

Keywords: Business school; Epistemic cognition; Epistemic competence; Heutagogy; Teaching and learning.

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Conflict of interest statement

Conflict of interestThe author declares no competing interests.

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References

Agarwal, A. (2022). Learning platforms: edX. In S. Iniguez, & P. Lorange (Eds.), Executive education after the pandemic: A vision for the future (pp. 277-286). Palgrave, 277-286.

Alexander PA. Reflection and reflexivity in practice versus in theory: Challenges of conceptualization, complexity, and competence. Educational Psychologist. 2017;52(4):307-314. doi: 10.1080/00461520.2017.1350181. - DOI

Blackwood T, Round A, Pugalis L, Hatt L. Making sense of learning: Insights from an experientially-based undergraduate entrepreneurship programme. Industry and Higher Education. 2015;29(6):445-457. doi: 10.5367/ihe.2015.0278. - DOI

Blaschke LM. Heutagogy and lifelong learning: A review of heutagogic practice and self-determined learning. The International Review of Research in Open and Distance Learning. 2012;13(1):56-71. doi: 10.19173/irrodl.v13i1.1076. - DOI

Blaschke, L. M. & Hase, S. (2021). So, you want to do heutagogy: Principles and practice. In Hase, S. and Blaschke L. M. (Eds.) chapter 2, Unleashing the Power of Learner Agency. EdTech Books. https://edtechbooks.org/up/pp. Accessed 3 Apr 2022

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Positioning through epistemic cognition in higher education: conceptualising the ways in which academics in a business school view heutagogy - PubMed

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Teaching and learning in higher education is informed by a multitude of conditioning factors, not least the values systems and outlook of academics. Understanding the epistemological positioning taken by academics in relation to teaching and learning is therefore important if we are to make judgment ...

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Now that you know about the strategic networks and you have completed this activity, answer these questions:

How do your students/staff share and express what they know?

How can you provide a variety of options for action and expression into your work?

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Now that you know about the strategic networks and you have completed this activity, answer these questions: How do your students/staff share and express what they know? How can you provide a variety of options for action and expression into your work?

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Study: Chronic Stress Can Shrink Your Brain

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Caregiver stress: Tips for taking care of yourself

Caring for a loved one strains even the most resilient people. If you're a caregiver, take steps to preserve your own health and well-being.
By Mayo Clinic Staff
As the population ages, more people are doing caregiving. About 1 in 3 adults in the United States is an informal or family caregiver.

A caregiver is anyone who helps another person in need. A person in need might be an ill spouse or partner, a child with a disability, or an aging friend or relative.

Caregivers report higher levels of stress than do people who are not caregivers. It's important for caregivers to know that they, too, need help and support.

Caregiving is rewarding but stressful

Caregiving can have many rewards. For most caregivers, caring for a loved one feels good. And it can make your relationship stronger.

But the demands of caregiving also cause emotional and physical stress. It's common to feel angry, frustrated, worn out or sad. And it's common to feel alone.

Caregiver stress can put caregivers at risk of changes in their own health. Factors that can increase caregiver stress include:

Caring for a spouse.

Living with the person who needs care.

Caring for someone who needs constant care.

Feeling alone.

Feeling helpless or depressed.

Having money problems.

Spending many hours caregiving.

Having too little guidance from health care professionals.

Having no choice about being a caregiver.

Not having good coping or problem-solving skills.

Feeling the need to give care at all times.

Signs of caregiver stress

As a caregiver, you may be so focused on your loved one that you don't see how caregiving affects your own health and well-being. The signs of caregiver stress include:

Feeling burdened or worrying all the time.

Feeling tired often.

Sleeping too much or not enough.

Gaining or losing weight.

Becoming easily irked or angry.

Losing interest in activities you used to enjoy.

Feeling sad.

Having frequent headaches or other pains or health problems.

Misusing alcohol or drugs, including prescription medicines.

Missing your own medical appointments.

Too much stress over time can harm your health. As a caregiver, you might feel depressed or anxious. You might not get enough sleep or physical activity. Or you might not eat a balanced diet. All of these increase your risk of health conditions, such as heart disease and diabetes.

Tips to manage caregiver stress

The emotional and physical demands of caregiving can strain even the strongest person. Many resources and tools can help you care for your loved one and yourself. Make use of them. If you don't take care of yourself, you won't be able to care for anyone else.

To help manage caregiver stress:

Ask for and accept help. Make a list of ways in which others can help you. Then let them choose how to help. Ideas include taking regular walks with the person you care for, cooking a meal for you and helping with medical appointments.

Focus on what you can do. At times, you might feel like you're not doing enough. But no one is a perfect caregiver. Believe that you're doing the best you can.

Set goals you can reach. Break large tasks into smaller steps that you can do one at a time. Make lists of what's most important. Follow a daily routine. Say no to requests that are draining, such as hosting meals for holidays or other occasions.

Get connected. Learn about caregiving resources in your area. There might be classes you can take. You might find caregiving services such as rides, meal delivery or house cleaning.

Join a support group. People in support groups know what you're dealing with. They can cheer you on and help you solve problems. A support group also can be a place to make new friends.

Seek social support. Stay connected to family and friends who support you. Make time each week to visit with someone, even if it's just a walk or a quick cup of coffee.

Take care of your health. Find ways to sleep better. Move more on most days. Eat a healthy diet. Drink plenty of water.

Many caregivers have trouble sleeping. Good sleep is important for health. If you have trouble getting a good night's sleep, talk to your health care professional.

See your health care professional. Get the vaccines you need and regular health screenings. Tell your health care professional that you're a caregiver. Talk about worries or symptoms you have.

Respite care

It may be hard to leave your loved one in someone else's care. But taking a break can be one of the best things you do for yourself and the person you're caring for. Types of respite care include:

In-home respite. Health care aides come to your home to spend time with your loved one or give nursing services or both.

Adult care centers and programs. There are centers that give day care for older adults. Some also care for young children. The two groups might spend time together.

Short-term nursing homes. Some assisted living homes, memory care homes and nursing homes accept people who need care for short stays while caregivers are away.

Working outside the home

Caregivers who work outside the home can feel burdened. If this describes you, think about taking a leave from your job for a time if you can afford to do so.

Employees covered under the federal Family and Medical Leave Act may be able to take up to 12 weeks of unpaid leave a year to care for relatives. Ask your human resources office about choices for unpaid leave.

You aren't alone

Ask for the help you need. Besides asking family and friends, use local resources for caregivers.

To start, check out the national Eldercare Locator or contact your local Area Agency on Aging to learn about services in your area. Or try your state's Aging and Disability Resource Center. You can find these resources online or in a telephone directory.

There also are mobile apps and web-based services that give support to caregivers. These services can help build coping skills and teach about caregiving.

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Show references

1. Caregiver stress. Office on Women's Health. https://www.womenshealth.gov/a-z-topics/caregiver-stress. Accessed June 19, 2023.

2. Veronese S, et al. Palliative approach to Parkinson disease and parkinsonian disorders. https://www.uptodate.com/contents/search. Accessed June 19, 2023.

3. Petrovic M, et al. Digital mental health tools for caregivers of older adults - A scoping review. Frontiers in Public Health. 2020; doi:10.3389/fpubh.2020.00128.

4. Caregiver stress: The impact on physical health. National Council on Aging. https://ncoa.org/article/caregiver-stress-the-impact-on-physical-health. Accessed June 19, 2023.

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Practical solutions for caregiver stress

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Fight caregiver stress and prevent burnout by taking time to take care of yourself.

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Empowering lives through non-visual access to technology

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Learning Outcomes

Learning outcomes are what you want your students to learn, either as a result of a specific lesson or on the grander, more general scale of the entire course. Learning outcomes target knowledge, skills, or attitudes for change. Bloom's taxonomy specifically targets these by seeking to increase knowledge (cognitive domain), develop skills (psychomotor domain), or develop emotional aptitude or balance (affective domain). Learning outcomes might be identified by someone outside the teacher, such as state-wide or departmental standards. The taxonomy provides a basis for developing sub-goals and assessment methodology to meet these goals. It is important to note that learning outcomes are goals, and are not the activities performed to achieve those goals. Outcomes can be categorized into broad, global outcomes that may take many years to achieve and provide direction for education, educational goals that guide curriculum development over the weeks or months it takes to complete a specific course, and instructional goals that narrowly focus on the daily activities, experiences, and exercises used in a specific lesson plan.

Objective Builder Tool

For applications specific to a course, the Center for Distributed Learning has developed an objective builder tool to help craft the language for measurable learning outcomes.

Applications of the Taxonomy

Taxonomies are developed to provide a framework for organizing a continuum along an underlying structure. For example, languages may be classified as Romantic, Germanic, etc. based on their underlying grammatical structure and origin. Bloom's taxonomy primarily provides instructors with a focus for developing their course learning outcomes. There are a number of reasons why a teacher would want to use Bloom's taxonomy. Initially, it can be used to increase one's understanding of the educational process. Teachers can see and understand complex cognitive development and how lower-level skills build into higher-order thinking (e.g., recalling facts and comprehending previous problems allows a student to apply their experience to similar problems). Using this understanding facilitates the prioritizing of material and can steer the organization of lessons to maximize class time. For example, lower-level skills (e.g., memorizing factual knowledge) can be developed before higher-level skills are introduced (e.g., analysis of relationships). Current educators frequently face a confusing array of standards and curriculum requirements. Bloom's taxonomy offers a guiding framework for breaking these criteria down into accessible chunks which can be used to direct day-to-day lesson plans and can be easily compared to their own goals for the class. Just as different levels require different instructional delivery methods, they also require different assessment methods. Bloom's taxonomy can be used as a checklist to ensure that all levels of a domain have been assessed and align assessment methods with the appropriate lessons and methodologies. In this way, the taxonomy also makes it easier for you to maintain consistency between assessment methods, content, and instructional materials and identify weak areas.

Update to Bloom's Taxonomy (2001)

Originally, Bloom's taxonomy was one-dimensional with an exclusive focus on the knowledge domain. The current updated version developed by Anderson and Krathwohl (2001) reorganizes, and highlights the interactions between, two dimensions: cognitive processes and knowledge content. Anderson and Krathwohl identify two reasons for updating the original handbook. They emphasize a refocusing of educational outcomes back to the original handbook, which was ahead of its time and can still offer assistance to modern educators and to incorporate new findings in psychology and education into the framework. In their revision, cognitive processes are presented as verbs and the knowledge content are presented as nouns. Along with exchanging the levels of Evaluation and Synthesis (which they rename to Creation), Anderson and Krathwohl redefine the knowledge dimension to include four types:

Factual Knowledge: Basic elements of a discipline that a student must know and be able to work with to solve problems including basic terminology and specific details and elements.

Conceptual Knowledge: Interrelationships between basic factual knowledge that demonstrate how elements work together, for example, classifications and categories, principles and generalizations, and theories, models, and structures.

Procedural Knowledge: How something is done including the methods of inquiry, skills, algorithms, techniques, and methods needed to investigate, apply, or analyze information.

Metacognitive Knowledge: Awareness and knowledge of one's own cognition including strategies for learning, contextual and conditional knowledge about cognitive tasks, and self-knowledge.

References:
Bloom, B. S. (1969). Taxonomy of educational objectives: The classification of educational goals : Handbook I, Cognitive domain. New York: McKay.
Anderson, L. W., Krathwohl, D. R., & Bloom, B. S. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives. New York: Longman.

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IntroductionBloom's taxonomy was developed to provide a common language for teachers to discuss and exchange learning and assessment methods. Specific learning outcomes can be derived from the taxonomy, though it is most commonly used to assess learning on a variety of cognitive levels. The table below defines each cognitive level...

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Many students start college using the study strategies they used in high school, which is understandable-the strategies worked in the past, so why wouldn't they work now? As you may have already figured out, college is different. Classes may be more rigorous (yet may seem less structured), your reading load may be heavier, and your professors may be less accessible. For these reasons and others, you'll likely find that your old study habits aren't as effective as they used to be. Part of the reason for this is that you may not be approaching the material in the same way as your professors. In this handout, we provide information on Bloom's Taxonomy-a way of thinking about your schoolwork that can change the way you study and learn to better align with how your professors think (and how they grade).

Why higher order thinking leads to effective study

Most students report that high school was largely about remembering and understanding large amounts of content and then demonstrating this comprehension periodically on tests and exams. Bloom's Taxonomy is a framework that starts with these two levels of thinking as important bases for pushing our brains to five other higher order levels of thinking-helping us move beyond remembering and recalling information and move deeper into application, analysis, synthesis, evaluation, and creation-the levels of thinking that your professors have in mind when they are designing exams and paper assignments. Because it is in these higher levels of thinking that our brains truly and deeply learn information, it's important that you integrate higher order thinking into your study habits.

The following categories can help you assess your comprehension of readings, lecture notes, and other course materials. By creating and answering questions from a variety of categories, you can better anticipate and prepare for all types of exam questions. As you learn and study, start by asking yourself questions and using study methods from the level of remembering. Then, move progressively through the levels to push your understanding deeper-making your studying more meaningful and improving your long-term retention.

Level 1: Remember

This level helps us recall foundational or factual information: names, dates, formulas, definitions, components, or methods.

Level 2: Understand

Understanding means that we can explain main ideas and concepts and make meaning by interpreting, classifying, summarizing, inferring, comparing, and explaining.

Level 3: Apply

Application allows us to recognize or use concepts in real-world situations and to address when, where, or how to employ methods and ideas.

Level 4: Analyze

Analysis means breaking a topic or idea into components or examining a subject from different perspectives. It helps us see how the "whole" is created from the "parts." It's easy to miss the big picture by getting stuck at a lower level of thinking and simply remembering individual facts without seeing how they are connected. Analysis helps reveal the connections between facts.

Level 5: Synthesize

Synthesizing means considering individual elements together for the purpose of drawing conclusions, identifying themes, or determining common elements. Here you want to shift from "parts" to "whole."

Level 6: Evaluate

Evaluating means making judgments about something based on criteria and standards. This requires checking and critiquing an argument or concept to form an opinion about its value. Often there is not a clear or correct answer to this type of question. Rather, it's about making a judgment and supporting it with reasons and evidence.

Level 7: Create

Creating involves putting elements together to form a coherent or functional whole. Creating includes reorganizing elements into a new pattern or structure through planning. This is the highest and most advanced level of Bloom's Taxonomy.

Pairing Bloom's Taxonomy with other effective study strategies

While higher order thinking is an excellent way to approach learning new information and studying, you should pair it with other effective study strategies. Check out some of these links to read up on other tools and strategies you can try:

Other UNC resources

If you'd like some individual assistance using higher order questions (or with anything regarding your academic success), check out some of your UNC resources:

Academic Coaching: Make an appointment with an academic coach at the Learning Center to discuss your study habits one-on-one.

Office Hours: Make an appointment with your professor or TA to discuss course material and how to be successful in the class.

Works consulted

Anderson, L. W., Krathwohl, D.R., Airasian, P.W., Cruikshank, K.A., Mayer, R.E., Pintrich, P.R., Wittrock, M.C (2001). A taxonomy of learning, teaching, and assessing: A revision of Bloom's taxonomy of educational objectives. New York, NY: Longman.

"Bloom's Taxonomy." University of Waterloo. Retrieved from https://uwaterloo.ca/centre-for-teaching-excellence/teaching-resources/teaching-tips/planning-courses-and-assignments/course-design/blooms-taxonomy

"Bloom's Taxonomy." Retrieved from http://www.bloomstaxonomy.org/Blooms%20Taxonomy%20questions.pdf

Overbaugh, R., and Schultz, L. (n.d.). "Image of two versions of Bloom's Taxonomy." Norfolk, VA: Old Dominion University. Retrieved from https://www.odu.edu/content/dam/odu/col-dept/teaching-learning/docs/blooms-taxonomy-handout.pdf

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License.
You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Learning Center, University of North Carolina at Chapel Hill

If you enjoy using our handouts, we appreciate contributions of acknowledgement.
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Higher Order Thinking: Bloom's Taxonomy - Learning Center

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Many students start college using the study strategies they used in high school, which is understandable-the strategies worked in the past, so why wouldn't they work now? As you may have already figured out, college is different. Classes may be ... Read more

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Elizabeth Cox: The surprising link between stress and memory

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You spend weeks studying for an important test. On the big day, you wait nervously as your teacher hands it out. You're working your way through, when you're asked to define "ataraxia." You know you've seen the word before, but your mind goes blank. What just happened?

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Burn-out is included in the 11th Revision of the International Classification of Diseases (ICD-11) as an occupational phenomenon. It is not classified as a medical condition.

It is described in the chapter: 'Factors influencing health status or contact with health services' - which includes reasons for which people contact health services but that are not classed as illnesses or health conditions.

Burn-out is defined in ICD-11 as follows:

"Burn-out is a syndrome conceptualized as resulting from chronic workplace stress that has not been successfully managed. It is characterized by three dimensions:

feelings of energy depletion or exhaustion;

increased mental distance from one's job, or feelings of negativism or cynicism related to one's job; and

reduced professional efficacy.

Burn-out refers specifically to phenomena in the occupational context and should not be applied to describe experiences in other areas of life."

Burn-out was also included in ICD-10, in the same category as in ICD-11, but the definition is now more detailed.

The World Health Organization is about to embark on the development of evidence-based guidelines on mental well-being in the workplace.

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Burn-out an "occupational phenomenon": International Classification of Diseases

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Burn-out is included in the 11th Revision of the International Classification of Diseases (ICD-11) as an occupational phenomenon. It is not classified as a medical condition.It is described in the chapter: 'Factors influencing health status or contact with health services' - which includes reasons for which people contact health services but that are not classed as illnesses or health conditions.Burn-out is defined in ICD-11 as follows:"Burn-out is a syndrome conceptualized as resulting from chronic workplace stress that has not been successfully managed.

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Strategies for healthcare leaders to address burnout

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Strategies for healthcare leaders to address burnout

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Clinical use of mindfulness meditation for chronic pain

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Clinical use of mindfulness meditation for chronic pain

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Abstract

Ninety chronic pain patients were trained in mindfulness meditation in a 10-week Stress Reduction and Relaxation Program. Statistically significant reductions were observed in measures of present-moment pain, negative body image, inhibition of activity by pain, symptoms, mood disturbance, and psychological symptomatology, including anxiety and depression. Pain-related drug utilization decreased and activity levels and feelings of self-esteem increased. Improvement appeared to be independent of gender, source of referral, and type of pain. A comparison group of pain patients did not show significant improvement on these measures after traditional treatment protocols. At follow-up, the improvements observed during the meditation training were maintained up to 15 months post-meditation training for all measures except present-moment pain. The majority of subjects reported continued high compliance with the meditation practice as part of their daily lives. The relationship of mindfulness meditation to other psychological methods for chronic pain control is discussed.

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Lifestyle Medicine for the Prevention and Treatment of Pancreatitis and Pancreatic Cancer.

Subramanian SK, Brahmbhatt B, Bailey-Lundberg JM, Thosani NC, Mutha P. Subramanian SK, et al. Diagnostics (Basel). 2024 Mar 14;14(6):614. doi: 10.3390/diagnostics14060614. Diagnostics (Basel). 2024. PMID: 38535034 Free PMC article. Review.

Role of wet-cupping therapy in physiological and mental pains in patients with migraine: A quasi-clinical trial.

Abdulah DM, Younis HA, Mustafa ZR. Abdulah DM, et al. Medicine (Baltimore). 2024 Feb 2;103(5):e37055. doi: 10.1097/MD.0000000000037055. Medicine (Baltimore). 2024. PMID: 38306572 Free PMC article. Clinical Trial.

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national center for biotechnology information

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The clinical use of mindfulness meditation for the self-regulation of chronic pain - PubMed

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Ninety chronic pain patients were trained in mindfulness meditation in a 10-week Stress Reduction and Relaxation Program. Statistically significant reductions were observed in measures of present-moment pain, negative body image, inhibition of activity by pain, symptoms, mood disturbance, and psycho ...

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Caregiver Stress and Burnout - HelpGuide.org

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Caregiving stress can lead to burnout if you don't take care of yourself. These tips will help you avoid caregiver burnout and regain control over your life.

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National Fund for Scientific Research, Brussels, Belgium

Person Centred Research and Training Lab, Psychological Sciences Research Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium

Informal caregiving is a rewarding but demanding role. The present theoretical framework proposes to adapt the tridimensional concept of burnout to informal caregiving as a way to address the potential consequences of caregiving. This adaptation reflects caregivers' reported difficulties, as well as empirical findings on emotional exhaustion, depersonalization, and personal accomplishment as caregiving outcomes. But to understand burnout in informal caregiving contexts, it is also necessary to find ways to model it. The Informal Caregiving Integrative Model (ICIM) is thus proposed. This model is based on the integration of elements from literature on both informal caregiving stress and professional burnout. The goal of the ICIM is to emphasize the importance of every category of determinants of informal caregiver burnout (i.e., relating to the caregiver, the caregiving setting, and the sociocultural context), with a key mediating role for the caregivers' appraisal of their situation and their relationship with the care-recipient. This article is a first integrative step in the consideration of a form of burnout specific to informal caregivers and supports the design of empirical and interventional studies based on the theoretical foundation that the ICIM proposes.

Introduction

Informal Caregivers

Informal caregivers are individuals voluntarily caring for a relative or a friend facing illness, disability, or any condition requiring particular attention ( Schulz and Tompkins, 2010). Across the literature and in the media, it is widely accepted that being an informal caregiver puts a person at risk of poorer mental ( Pottie et al., 2014; Sallim et al., 2015) and physical health ( Kiecolt-Glaser et al., 2003; Känel et al., 2006; Capistrant et al., 2012). Although this consensus is contested ( Brown and Brown, 2014; Roth et al., 2015), it nevertheless appears that being an informal caregiver can represent, in many ways, an experience that puts the individual under stress ( Revenson et al., 2016).

The present work first proposes to adapt the concept of burnout to the context of informal caregiving as a means of addressing the consequences of such stress. As will be discussed, this adaptation is in response to concerns expressed in the literature about the measurement of the caregiving impact, currently driven by the study of the subjective burden. To drive future research on informal caregiver burnout, a new conceptualization must be constructed. To do so, two major models of caregiving stress and occupational burnout will be reviewed to identify their strengths and limitations. The Informal Caregiving Integrative Model (ICIM) will then be presented. The ICIM is designed to capture what makes existing models of professional burnout and informal caregiving stress so valuable, while trying to address their potential weaknesses.

Informal Caregivers' Burnout

The first reference to burnout in informal care was made in 1986. A study drew attention to "Spouse Burnout Syndrome," because some spouses of patients with chronic diseases showed symptoms comparable to those experienced by formal caregivers in burnout ( Ekberg et al., 1986). Despite its promising premises, this work received little attention for a long time. Since the first decade of the new millennium, however, an increasing number of studies have adapted burnout measures to assess informal caregivers' strain. In line with Ekberg's study in 1986, these studies have highlighted that some informal caregivers face strains comparable to the experiences of professionals in burnout ( Angermeyer et al., 2006; Perkins and Hewitt, 2016; Thorson-Olesen et al., 2018).

This tridimensional transposition must, of course, be empirically investigated. Although this is only an indirect indicator, studies that have transposed burnout measures into the informal help context do not seem to have any major psychometric problem, and the internal consistency indicators seem comparable to those found in the literature on professional burnout (e.g., Truzzi et al., 2012; Akinci and Pinar, 2014; Katsifaraki and Wood, 2014; Yan, 2014). In the literature, emotional exhaustion is often highlighted in studies of informal caregivers under the heading of general exhaustion. This exhaustion can occur at both physical and mental levels, but remains primarily emotional in nature ( Galiatsatos et al., 2017). There is little evidence of cases of depersonalization in informal caring contexts, except for studies adapting the Maslach Burnout Inventory, the most frequently used burnout scale. Other studies have shown that some caregivers put an emotional and psychological distance between themselves and the person they are caring for in order to preserve themselves ( Cross et al., 2018). This distance can take the form of a more pragmatic and distant style of care and relationship in the face of significant stress ( Hubbell and Hubbell, 2002). Personal accomplishment has been investigated in terms of personal growth resulting from the caregiving role, positive impact on the care-recipient, and caregivers' sense of acting in accordance with their values ( Cross et al., 2018). Although the positive and negative impacts of informal care are related, the positive impact may be relatively unaffected by the negative caregiving experience and flourish independently ( Lawton et al., 1991; Appleton et al., 2018). All these elements suggest that informal caregiver burnout is a promising concept to assess the impact of caregiving.

The Burden-Burnout Relationship

Despite this promising position, the literature studying the negative impact of informal care remains focused on the concept of subjective burden. Subjective burden is the subjective assessment of the stress that the helping situation can represent ( Galiatsatos et al., 2017). It is the caregiver's appraisal of the objective experience ( Lawton et al., 1991). Despite this seemingly clear definition, the concept of burden has been strongly criticized, with researchers pointing out that burden remains poorly defined and its assessment too vague ( Mosquera et al., 2016). Depending on the definition used by authors, subjective burden may refer to the physical, psychological, emotional, social, and/or financial consequences of caregiving. This conceptual heterogeneity leads to diverse forms of assessment ( Van Durme et al., 2012), and renders its use in public policy or research too ambiguous ( Bastawrous, 2013). A concept defined too heterogeneously makes it difficult to draw clear conclusions. Contributing to this confusion, authors use the notions of subjective burden and caregiver burnout without distinction by measuring burden and reporting that they have measured burnout (and vice versa) (e.g., Schoenmakers et al., 2009; Kokurcan et al., 2015; Ghane et al., 2016).

Understanding Caregiver Burnout: Existing Models

Studying informal caregiver burnout requires a theoretical basis on which to build an understanding of the burnout process. Existing studies addressing informal caregiver burnout seem to do so without this theoretical basis. The aim of the present work is thus to propose a theoretical model to guide future research on informal caregiver burnout. Such a model will need to combine elements of existing models from the literatures on caregiving stress and occupational burnout. In informal caregiving, the adaptation of Lazarus and Folkman's stress model has been preponderant in most research; by contrast, various models have been investigated in occupational burnout, although over the past decade, the Job Demands-Resources (JD-R) Model has provided a clear framework for research ( Schaufeli and Taris, 2014).

Model of Carer Stress and Burden

The model breaks down the process into six different interacting elements (see Figure 1). (1) Primary stressors are all objective elements in the caregiving setting, such as the type and intensity of symptoms, the tasks to perform or the intensity (hours/week spent caregiving). These primary stressors cause (2) secondary stressors, the consequences of the objective elements (e.g., lack of free time, family conflicts, financial strain). These are the mediators between the primary stressors and (3) the appraisal. The appraisal is the caregivers' subjective assessment of their situation. According to Lazarus and Folkman's theory (1984), this is an evaluation of the equilibrium between demands and resources. This evaluation leads to (4) the outcomes. These outcomes are psychosocial (e.g., depression or well-being), but could also be behavioral (e.g., substance consumption), or physiological (e.g., health issues related to chronic stress). This linear succession is influenced by (5) exacerbating and mitigating factors. These are all the elements other than primary and secondary stressors that modify the relationships between the variables. Coping strategies, personality facets, and other resources are among the factors modifying the relationships between primary and secondary stressors, appraisal, and outcomes. Finally, (6) background and contextual factors such as sociodemographic and cultural or ethnic determinants frame the caregiver's experience.

Figure 1. Model of Carer Stress And Burden [adapted from Sörensen et al., 2006 Copyright (2006), with permission from Elsevier].

The Carer Stress and Burden Model and the two other models it takes its origin from make a crucial distinction between primary and secondary stressors, acknowledging the distinct role of primary stressors and their consequences ( Pearlin et al., 1990). They also emphasize the central mediator role of appraisal between objective stressors and outcomes ( Lawton et al., 1991). However, this model only focuses on caregiving stress. Caregivers' psychological and social determinants are considered peripheral, although they play an important role in their appraisal and experience of caregiving strain ( Adelman et al., 2014). The dyad is not considered, neglecting the relation between caregiving strain and the relationship with the care-recipient ( Spruytte et al., 2002; Kindt et al., 2015). The appraisal is only defined by secondary stressors and background elements, yet primary stressors, the relationship with the recipient, and the caregiver's individual characteristics may also contribute to this appraisal ( Cuijpers and Stam, 2000). Dispositional and situational coping strategies are not explicitly integrated in the model, even though it is based on Lazarus and Folkman's work, and despite the crucial role played by coping strategies in the caregiving stress regulation ( Pinquart and Sörensen, 2005). Subjective burden is considered as an outcome and not an appraisal. Finally, there are few feedback loops, suggesting that all of the caregiving stress model elements lead to outcomes without any impact of these outcomes on caregiving in return.

The Job Demands-Resources Model

In the burnout literature, one model synthesizes the way burnout appears in occupational contexts: the Job Demands-Resources Model ( Demerouti et al., 2001). This model presents burnout as a two-dimensional process. On the one hand there is exhaustion, the wearing down of levels of energy, and the depletion of the caregiver's emotional resources. On the other hand there is engagement in the job, the willingness to perform well and to find new positive and constructive challenges within the work. In this view, burnout is caused by demands (stressors) and is diminished by resources (see Figure 2).

Figure 2. The Job Demands-Resources Model [adapted by permission from Springer Nature, Springer ebook by Schaufeli and Taris, 2014].

This model presents the role of burnout as a mediator between demands/resources and outcomes: the stressors (and resources) have a direct impact on burnout, which in turn causes outcomes. It also makes it clear that negative processes (e.g., burnout) do not obliterate positive ones ( Broese van Groenou et al., 2013). Although this has not been assessed directly (except for parental burnout: see Mikolajczak and Roskam, 2018), the model postulates an equilibrium between demands and resources. It is the imbalance between persistent demands and insufficient resources that will, in the end, lead to burnout. Although this balance is a core element in the JD-R, it is not directly incorporated in the model, and direct effects of demands and resources are emphasized instead. However, this balance could be thought of as similar to Lazarus and Folkman's appraisal, which is explicitly included in caregiving stress models.

The Informal Caregiving Integrative Model

The consideration of both the caregiver stress model and the JD-R model has made it possible to identify important factors to consider when building an understanding of informal caregiver burnout. Such a conceptualization should: (1) consider stressors and resources not only in the caregiving setting but also in the caregiver's psychosocial characteristics, (2) take into account the relationship with the care-recipient as a critical component in the understanding of the caregiving experience, (3) consider burnout as a key mediator between stressors and outcomes, (4) integrate the caregiver's appraisal as a core element in the model, (5) consider subjective burden as a measure of appraisal, and (6) include feedback loops. In addition, the consideration of determinants of caregiving should not focus on the often arbitrary distinction between demands and resources, but rather aim at understanding the processes by which these determinants may impact the caregiver's strain and appraisal.

To respond to these requirements, the Informal Caregiving Integrative Model (ICIM) is proposed as a theoretical framework to guide future research (see Figure 3). The rationale of the ICIM is to consider the different determinants of informal caregiver burnout (i.e., the caregiving setting, the caregiver, and the environment) on the same footing. Burnout is conceived of as a key mediator between these determinants and general outcomes, and the impact of the determinants on informal caregiver burnout is mediated by both the caregiver's appraisal and his or her relationship quality with the care-recipient.

Figure 3. The Informal Caregiving Integrative Model (ICIM).

To date, several elements of the model have already been explored by studies that focus on informal caregiver burnout. Because the ICIM is a theoretical model aiming at framing future research, the elements described in each section of the model do not aim at being exhaustive. The present goal is rather to illustrate the model with existing studies, mainly on informal caregiver burnout, and to suggest future directions for research in this field.

Determinants: Caregiver's Characteristics

The first set of determinants of caregiver burnout are the caregiver's characteristics. Caregivers remain individuals with personal cognitions, emotions, and motives that should be considered when aiming at understanding informal caregiver burnout. The characteristics of the caregiver can be divided into three main groups: background and sociodemographic, psychological, and physical factors.

Background and Sociodemographic Factors

The caregiver faces several elements that cannot be changed but still influence his or her caregiving strain. Being a female caregiver has been found to be associated with a heavier burden ( Salama and El-Soud, 2012) and more burnout ( Angermeyer et al., 2006; Truzzi et al., 2012). Often, the effect of gender has been confused with the effect of other gendered issues such as caregiving being more frequent among women than men ( Revenson et al., 2016), and this has led to other studies finding no relation between gender and caregiver burnout ( Kokurcan et al., 2015; Onwumere et al., 2017). Regarding the caregiver's age, no stable effect has been found ( Demirhan et al., 2011; Truzzi et al., 2012; Yan, 2014; Onwumere et al., 2017). However, a difference may lie in the type of relationship with the recipient, reflecting that assuming the caregiving role has different implications at different life stages ( Broese van Groenou et al., 2013; Perkins and Hewitt, 2016).

Research on role theory has suggested the significant impact of the caregivers' multiple roles ( Bastawrous, 2013). The accumulation of roles, such as being a parent at the same time as being an informal caregiver, also adds to the caregiver's strain ( Stephens et al., 2001; de Almeida Mello et al., 2016). Recent studies have shown such patterns in professional burnout. Double-duty caregivers - being a formal and informal caregiver at the same time - are at higher risk of professional burnout than work-only caregivers ( Häusler et al., 2017; DePasquale et al., 2018). In the same way, being an informal caregiver has been shown to increase the chances of parental burnout ( Lindström et al., 2011; Gérain and Zech, 2018; Séjourné et al., 2018). The informal caregiving role thus seems to affect the caregiver's other roles. This permeability is probably bidirectional, and the impact of the other roles on caregiving strain must be investigated to fully understand what is at stake in caregiver burnout.

As with gender or professional status, the relevance of studying background or sociodemographics lies not in the variable itself but rather in what it implies. The impact of gender would rather reveal gender discrimination, professional status may represent a resource or a demand, and role accumulation can be a major risk factor for multiple aspects of life. Future studies integrating these determinants should therefore investigate their meaning rather than the variable itself.

Psychological Factors

All these studies point to the necessity to consider psychological factors when studying caregiver burnout. While some of them are more related to trait elements (e.g., personality) that would be hard to modify, others could be targeted by interventions to help exhausted caregivers or to prevent future problems. Future research should thus fully identify the psychological processes involved in informal caregiver burnout in order to identify those with the greatest impact and those which are most promising for interventions.

Physical State

The physical health of caregivers is a factor that determines their involvement in caregiving. Healthy caregivers often take more responsibility in caregiving ( Pinquart and Sörensen, 2007). The experience of somatic disorders, illness, or chronic pain has been shown to put pressure on caregivers, making them more prone to burnout ( Hattori et al., 2000, 2001; Demirhan et al., 2011). While this is especially acute for aging caregivers, it is a factor in all caregivers' capacities to provide care and in the difficulties they may face. Future research should thus consider more closely how the evolution of caregivers' physical state could affect their ability to manage the situation and impact their mental health.

Determinants: Caregiving Setting

As pointed out in the Sörensen's Model of Carer Stress and Burden, a distinction needs to be made between primary and secondary stressors in the caregiving setting. Primary stressors are all the demands (and potential resources) defining the caregiving role. They are mostly referred to in the literature as "objective burden" ( Brouwer et al., 2004). Secondary stressors are all the demands and resources caused by the primary stressors.

Primary Stressors

Time since start of caregiving (duration) is often considered as a central element in caregiving strain. Yet it appears that there is no relationship between duration of care and burnout ( Sugihara et al., 2004; Lindström et al., 2011; Kokurcan et al., 2015), and only a weak link to burden ( Pinquart and Sörensen, 2003; Adelman et al., 2014). A similar pattern appears regarding time spent caregiving per week (intensity) ( Angermeyer et al., 2006; Truzzi et al., 2012; Adelman et al., 2014; Kokurcan et al., 2015), and living with the care-recipient has also been highlighted as an inconclusive stressor for subjective burden and burnout ( Cuijpers and Stam, 2000; Cheung and Chow, 2011; Yan, 2014; Chiao et al., 2015).

Being a spouse appears to be a risk factor ( Cuijpers and Stam, 2000; Sugihara et al., 2004), and caring for a man appears to be more demanding than for a woman ( Goetzmann et al., 2012; Onwumere et al., 2017). The reason behind the increased risk of caring for a man has not been investigated yet, but the low effect size of this association suggests that intensive investigation is not required.

Informal caregivers provide care to individuals with a wide diversity of health issues. Most studies, however, consider informal caregivers in the context of one particular health issue (e.g., neurodegenerative diseases, chronic pain, or disability) in order to control for a significant form of variability. Some studies have compared different populations in their sample (often one by one) (e.g., Weiss, 2002; Ybema et al., 2002; Lindström et al., 2010; Tramonti et al., 2019), but not enough to conclude about a particular risk profile. The autonomy (or functional impairment) of the care-recipient is a factor often related to caregiving subjective burden and burnout ( Cheung and Chow, 2011; Yan, 2014; Chiao et al., 2015; Lynch et al., 2018), but this variable remains specific to some populations (e.g., dementia). The common ground is the intensity of the symptoms in each health issue, which appears to be more related to caregiving subjective burden ( Chiao et al., 2015). Such evidence has also been highlighted for informal caregiver burnout in caregivers of individuals with mental illness ( Kokurcan et al., 2015) or dementia ( Cheung and Chow, 2011; Truzzi et al., 2012; Yan, 2014), and in caregivers of children with disability ( Demirhan et al., 2011; Basaran et al., 2013), chronic disease ( Riva et al., 2014), or comorbid issues ( Gérain and Zech, 2018). Beyond the health issue itself, correlative analyses have also shown a relationship between recipient's well-being and depressive symptoms on the one hand and subjective burden and informal caregiver burnout on the other, which suggests a mutual influence of the emotional states in the dyad ( Ybema et al., 2002; Yılmaz et al., 2009; Adelman et al., 2014; Kindt et al., 2015).

Primary stressors thus seem to have an impact on informal caregiver burnout. However, this impact appears mostly related to the health issue and not to descriptive characteristics of the caregiving role. Future research should therefore focus not only on the objective stressors, but also on what they entail (i.e., secondary stressors), and what they represent for the caregivers (i.e., their appraisal).

Secondary Stressors

Although it has not been widely investigated yet, the existence of secondary resources remains open to consideration. From this perspective, a resource arises because of the presence of a primary stressor, such as more social support or less isolation, due to caregivers' support groups or an increase in regular social support ( Sakakibara et al., 2015).

Determinants: Social Environment

The caregivers' social environment can be considered in three distinct ways: informal and partner support, professional support, and the sociocultural environment. Informal social support appears to diminish burden ( Choi and Sok, 2012; Adelman et al., 2014) and burnout ( Choi and Sok, 2012; Riva et al., 2014; Kokurcan et al., 2015), but this protective role is more important when the support responds to a caregiver's specific need ( Lindström et al., 2011). Because caregivers often take sole responsibility for care, the presence of other informal caregivers may represent a resource ( Peeters et al., 2010). However, such a resource could also translate into more stress due to additional conflicts, perceived inequities, worries, or diverging opinions ( Williams et al., 2016). Outside the caregiving setting, the face-to-face or online support of other caregivers also seems to be beneficial for caregivers because they share comparable experiences ( Perkins and Hewitt, 2016).

The partner is not always directly involved in caregiving but it appears that their support is essential to the provision of informal care (e.g., DePasquale et al., 2018). Research on support between parent-caregivers - parents providing care to one of their children - has shown that an unsatisfactory marital relationship and disagreements with the partner are related to burnout, highlighting the need for parents to face this challenge together ( Lindström et al., 2011; Riva et al., 2014; Gérain and Zech, 2018). Besides parent-caregivers, it may also be interesting to consider the quality of the relationship with the partner in the context of caring for a relative, other than a child, to understand how the caregiving situation modifies the dynamic in the couple. The particular situation of being the partner's informal caregiver will be addressed in the section on the relationship with the care-recipient.

The sociocultural environment of the individual is too often neglected in burnout research ( Pines et al., 2011), and informal caregiver burnout is no exception. Culture seems to be an important factor in the consequences of informal caregiving ( Pinquart and Sörensen, 2005; Chiao et al., 2015). At first, depending on their cultural norms, individuals could see their transition to the caregiving role as a normal process, or on the contrary experience it as a burden ( Sutter et al., 2016). Later on, the perceived normality or abnormality of the caregiving tasks performed and the trade-off made due to caregiving may also impact their appraisal ( Chiao et al., 2015; Konerding et al., 2018). As the care-recipient's health issue progresses, an unwillingness to delegate tasks and receive assistance due to cultural reasons may lead to burnout in the caregiver ( Scharlach et al., 2006). More broadly, there is a strong need to consider the cultural perspective and to be aware of the need to include groups often under-represented in research ( Parveen et al., 2018). Future research focusing on cultural aspects and their implications in caregiving will lead to a more precise understanding of caregivers' experience in different contexts and how it affects their well-being ( Bastawrous, 2013). In light of existing studies, such future work should try to understand the mechanisms by which culture affects caregiver stress and burnout (e.g., Knight and Sayegh, 2010).

Caregiving Appraisal

In the Informal Caregiving Integrative Model, all the determinants are held to have a direct impact on the caregiving appraisal. Absent from the JD-R, this appraisal is the subjective evaluation of the caregiving experience by the caregivers themselves. It is the evaluation of the balance or imbalance between demands and resources and is thus the weighting of the determinants. This evaluation is a mixture of positive and negative assessments, but its most investigated aspect in research is the subjective burden ( Galiatsatos et al., 2017). Close correlations have been found between subjective burden and emotional exhaustion, while less significant relationships have also been found with depersonalization and personal accomplishment ( Kasuya et al., 2000; Angermeyer et al., 2006; Kyung-Bock and Kim, 2008; Truzzi et al., 2008; Özlü et al., 2009; Choi and Sok, 2012; Salama and El-Soud, 2012; Akinci and Pinar, 2014; Götze et al., 2015). These results suggest that the impact of the appraisal on outcomes could be mediated by burnout ( Lee and Singh, 2010). Other appraisal elements such as feeling trapped in the caregiving role have not been investigated yet, but are probably related to caregiver burnout ( Sörensen et al., 2006).

Future work should focus on a more homogeneous definition of what form a positive appraisal could take, as opposed to the long-standing focus on subjective burden. A positive appraisal appears to have a positive impact on caregiver well-being (e.g., Yamamoto-Mitani et al., 2004), but this has not been investigated in connection with informal caregiver burnout. Focusing on positive appraisal could also have the broader goal of moving away from the long-standing view of caregiving as an ultimately negative experience, to a more balanced view in which positive appraisal is at the core of the evaluation ( Brown and Brown, 2014).

Relationship Quality

The relationship quality has been little considered in caregiving stress models, but the relationship with the recipient is the reason why an individual becomes a caregiver and remains a central element when considering either the care-recipient or the caregiver ( Revenson et al., 2016). The occurrence of an illness or a disability modifies the roles and the relationship in the dyad between the future care-recipient and the future caregiver ( Spruytte et al., 2002; Bastawrous et al., 2015). As the caring process progresses, the relationship quality remains a core-element in the caregiving experience. Of course, relationship quality with the care-recipient is determined by many elements, such as the relationship before caregiving or attachment style, but the key is to consider the impact caregiving may have on this relationship. Poor relationship quality has been found to be related to burden ( Cuijpers and Stam, 2000) and burnout ( Goetzmann et al., 2012; Kindt et al., 2015). Inequity in the relationship is also a key factor for caregivers of a spouse, particularly when the caregiving spouse feels like he or she is of minor importance in the couple, having been overshadowed by the other partner's health issue ( Ybema et al., 2002). One study has highlighted the need to take into account the disease's temporal characteristics when exploring further the impact of this relationship ( Fauth et al., 2012). Relational closeness appears to be a resource when the disease is manageable, and death remains a distant prospect. But when death appears closer, there may be a need to prepare for the separation.

Future research should focus on developing a deeper understanding of how the relationship quality could be a mediator between determinants and caregiver burnout. Dyadic coping has not been investigated in the context of informal caregiver burnout, but it appears to be a promising area for research in light of existing results (e.g., Rottmann et al., 2015). Investigation should also be broadened to the dyadic processes involved in caregiving, and to dyads other than couples ( Revenson et al., 2016). It should also address the relationship between appraisal and relationship quality and its evolution over time. If positive relationships could alleviate part of the subjective burden ( Lea Steadman et al., 2007), other elements such as perceived fairness or unfairness or modifications in roles could also impact the caregiver's appraisal (e.g., McPherson et al., 2010).

Informal Caregiver Burnout

Informal caregiver burnout is the key element of the ICIM. It is expected to be the consequence of the different sets of determinants, either directly or through the mediation of the appraisal and the relationship quality with the care-recipient. Caregiver burnout is also viewed as a key mediator between demands and various more general outcomes, as highlighted in several studies ( Lee and Singh, 2010; Kindt et al., 2015).

As pointed out in work on professional burnout, the negative impact of caregiving may overshadow the positive impact, but this does not mean that the latter cannot exist in presence of the former ( Schaufeli and Taris, 2014). Positive and negative caregiving impacts could both be present, leading to different combinations of caregiving strain (along similar lines to recent developments in the study of professional burnout, see Leiter and Maslach, 2016). From this perspective, future research could consider personal accomplishment as a dimension that may counterbalance the other two negative dimensions and lead to different outcomes.

General Outcomes

Beyond the specific impact of caregiving, more general outcomes can occur in reaction to or as a result of caregiver burnout. General outcomes of the caregiving impact are twofold: on the caregivers themselves and on the care-recipients. For the caregiver, informal caregiver burnout could lead to physical and psychological issues. In general, caregiver burnout is related to lower well-being, more psychological distress ( Götze et al., 2015; Kindt et al., 2015; Bachner, 2016), more negative and less positive emotions ( Kindt et al., 2015), and lower quality of life ( Ostlund et al., 2010; Takai et al., 2011). In terms of psychopathology, some studies have highlighted a moderate relationship between burnout and anxiety ( Yılmaz et al., 2009; Truzzi et al., 2012; Riva et al., 2014). As pointed out in the literature on professional burnout and on caregiving burden, the direction of these relationships is difficult to settle ( Adelman et al., 2014; Chiao et al., 2015). Anxiety could be a consequence of burnout and the caregiver's exhaustion, but trait anxiety could also lead to higher vigilance and overcaring, thus facilitating the occurrence of burnout. There is also a strong relationship between burnout and depression ( Truzzi et al., 2008, 2012, p. 012; Yılmaz et al., 2009; Lee and Singh, 2010; Katsifaraki and Wood, 2014; Bachner, 2016). Caregiver burnout could also have an impact on other spheres, for example by putting the individual at risk of professional burnout (as shown for parental burnout in Greaves et al., 2017). Informal caregiver burnout could also be a key mediator between subjective burden and decreased social activity ( Adelman et al., 2014): caregivers experiencing burnout are less likely to seek social contact. In terms of physical health, caregiver burnout is related to poorer subjective health ( Valente et al., 2011; Choi and Sok, 2012; Goetzmann et al., 2012), and to more reported somatic symptoms ( Weiss, 2002; Truzzi et al., 2012). Future research should further investigate the role of caregiver burnout in the erosion of the caregiver's physical health and the mechanisms by which this impact occurs (e.g., health behaviors, psychoneuroendocrinology).

Informal caregiver burnout could have a direct impact on the well-being of the care-recipient ( Kindt et al., 2015). Beyond that, caregiving strain could have an indirect impact through the onset of mistreatment ( Wiglesworth et al., 2010; Fang and Yan, 2016). Despite the affective bond, the risk of neglect and abuse remains a reality ( Acierno et al., 2010). Caregiver stress appears to be an important risk factor for the occurrence of physical or verbal violence ( Johannesen and LoGiudice, 2013). Early results have shown a link between burnout and violence, in both formal ( Truchot et al., 2013) and informal contexts ( Yan, 2014).

Circularity

Beyond the consequences themselves, caregiver burnout and more general outcomes will in turn have an impact through feedback loops and modify elements regarding the caregiver, the caregiving context, and the social environment. This circularity has often been neglected in models created to understand caregiving strain (as well as in the JD-R model), but it is critical in addressing how caregiving strain may evolve. The modification of one element will have a global impact on caregiving strain through a direct and indirect modification of the caregiving experience. Longitudinal studies should thus investigate these loops and understand their pathways.

Conclusion

The present work has proposed to adapt the concept of burnout to the informal caregiving context. This adaptation represents a response to criticisms made regarding the measurement of the impact of caregiving and its conceptual heterogeneity. The three-dimensional approach also expands the view of the impact of caregiving to the accomplishment found in the role and to the depersonalization that may occur. Additional studies should confirm the relevance of this concept, but it appears promising in light of the existing literature.

The second goal of the present work was to propose a theoretical model to frame future research on informal caregiver burnout. The review of the Job Demands-Resources Model from the occupation burnout literature and of the Caregiving Stress and Burden Model led to the development of the Informal Caregiving Integrative Model. This model aims to respond to the opportunities for the improvement of existing models, but also to preserve their most valuable features. The ICIM stresses the importance of taking full account of the actors and elements at stake when considering the determinants of caregiver burnout: the caregiving setting, the caregiver's characteristics, and their sociocultural environment. Key mediators between the determinants and caregiver burnout are the caregiving appraisal (both positive and negative), and also the relationship between the care-recipient and the caregiver, which has often been neglected.

Author Contributions

PG and EZ contributed to the conception of this theoretical work. PG performed the literature review and wrote the first draft of the manuscript. EZ critically revised it. PG and EZ refined the manuscript for submission. This final version was approved by both authors.

Funding

PG (Research Fellow) is funded by the Belgian Fund for Scientific Research (F.R.S.-FNRS, Belgium) with a grant from the Human Sciences Research Fund (n°6200219F).

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

Hattori, A., Ouchi, A., Shibuya, K., Sato, K., Hosoya, J., Nakahara, K., et al. (2001). [effect of background factors concerning both elderly persons and their families with regard to the caregiver burnout in the home]. Nihon Ronen Igakkai Zasshi. Jpn. J. Geriatr. 38, 360-365. doi: 10.3143/geriatrics.38.360

Hattori, A., Ouchi, A., Shibuya, K., Sato, K., Nakahara, K., Nishinaga, M., et al. (2000). [effect of the level of basic activities of daily living on home caregiver burnout]. Nihon Ronen Igakkai Zasshi. Jpn. J. Geriatr. 37, 799-804. doi: 10.3143/geriatrics.37.799

Maslach, C., Jackson, S. E., and Leiter, M. P. (1996). Maslach burnout inventor. 3rd Edn. Palo Alto, CA: Consulting Psychologists Press.
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No two students are alike, and the way every person learns will vary. Our brains are all unique, and our experiences all contribute to the different ways we learn. Psychologists have spent countless hours performing tests to better understand how students learn.

Current and aspiring teachers need tobe educated to be prepared for teaching students every day, and an important part of teacher education is understanding different ways of learning. There are many solidified learning theories that teachers can learn from as they prepare to help students in the classroom. Teachers who understand learning theories can use different techniques in their classrooms to cater to different kinds of learning. This can help all students find success in learning.

There are five main educational learning theories that educators can utilize to help them enhance their classrooms and make them better learning environments for all students.

What are the Five Main Educational Learning Theories?

Cognitive Learning Theory

Cognitive learning theory looks at the way people think. Mental processes are an important part in understanding how we learn. The cognitive theory understands that learners can be influenced by both internal and external elements.

Plato and Descartes are two of the first philosophers that focused on cognition and how we as human beings think. Many other researchers looked deeper into the idea of how we think, spurring more research. Jean Piaget is a highly important figure in the field of cognitive psychology, and his work focuses on environments and internal structures and how they impact learning.

Cognitive theory has developed over time, breaking off into sub-theories that focus on unique elements of learning and understanding. At the most basic level, the cognitive theory suggests that internal thoughts and external forces are both an important part of the cognitive process. And as students understand how their thinking impacts their learning and behavior, they are able to have more control over it.

Cognitive learning theory impacts students because their understanding of their thought process can help them learn. Teachers can give students opportunities to ask questions, to fail, and think out loud. These strategies can help students understand how their thought process works, and utilize this knowledge to construct better learning opportunities.

Behaviorism Learning Theory

Behaviorism learning theory is the idea that how a student behaves is based on their interaction with their environment. It suggests that behaviors are influenced and learned from external forces rather than internal forces.

Psychologists have been developing the idea of behaviorism since the 19th century. Behavioral learning theory is the basis for psychology that can be observed and quantified. Positive reinforcement is a popular element of behaviorism-classical conditioning observed in Pavlov's dog experiments suggests that behaviors are directly motivated by the reward that can be obtained.

Teachers in a classroom can utilize positive reinforcement to help students better learn a concept. Students who receive positive reinforcement are more likely to retain information moving forward, a direct result of the behaviorism theory.

Constructivism Learning Theory

Constructivism learning theory is based on the idea that students actually create their own learning based on their previous experiences. Students take what they're being taught and add it to their previous knowledge and experiences, creating a reality that's unique to them. This learning theory focuses on learning as an active process, which is personal and individual for each student.

Teachers can utilize constructivism to help understand that each student will bring their own past to the classroom every day. Teachers in constructivist classrooms act as more of a guide to helping students create their own learning and understanding. They help them create their own process and reality based on their own past. This is crucial to helping many kinds of students take their own experiences and include them in their learning.

Humanism is very closely related to constructivism. Humanism directly focuses on the idea of self-actualization. Everyone functions under a hierarchy of needs. Self-actualization is at the top of the hierarchy of needs-it's the brief moments where a person feels all of their needs are met and that they're the best possible version of themselves. Everyone is striving for this, and learning environments can either move toward meeting needs or away from meeting needs.

Teachers can create classroom environments that help students get closer to their self-actualization. Educators can help fulfill students' emotional and physical needs, giving them a safe and comfortable place to learn, plenty of food, and the support they need to succeed. This kind of environment is the most conducive to helping students learn.

Connectivism Learning Theory

Connectivism is one of the newest educational learning theories. It focuses on the idea that people learn and grow when they form connections. This can be connections with each other or connections with their roles and obligations in their lives. Hobbies, goals, and people can all be connections that influence learning.

Teachers can utilize connectivism in their classrooms to help students make connections to things that excite them, helping them learn. Teachers can use digital media to make good, positive connections to learning. They can help create connections and relationships with their students and with their peer groups to help students feel motivated about learning.

What are Additional Learning Theories?

While these five learning theories are the main educational learning theories for teachers who want to support their students' learning, there are additional theories they may want to understand. Some may work as good supplemental theories for teachers to bolster their educational support with a new approach.

Transformative Learning Theory

Transformative learning theory is a great approach for adult education and young adult learning. Also referred to as transformation learning, transformative learning theory focuses on the idea that learners can adjust their thinking based on new information.

This learning theory was founded by Jack Mezirow, who discovered it after doing studies on adult women who went back to school. His initial research found that adults don't apply their old understanding to new situations and that having a new perspective helped them gain a new understanding of things as they change. Mezirow also believed that students had important teaching and learning opportunities connected to their past experiences and that critical reflection and review could lead to a transformation of their understanding.

This approach works well for adult students, as children don't have the same kind of transformation with their learning experiences-and with life experience. Adult students could draw on childhood experiences and transforming those beliefs and understandings using critical reflection, leading them to an understanding of what they should believe and understand as adults.

Overall, the theory states that our worldview is changed the more we learn, which helps us grasp new concepts and ideas. By getting new information that helps evaluate past ideas, students are able to make a dramatic educational shift beyond standard learning. Teachers can employ this learning theory by encouraging their students to learn new perspectives while questioning their assumptions and open the floor for discourse to cement their new train of thought.

Using social learning theory can be a valuable tool for dealing with difficult students who like to disrupt the classroom and cause trouble. This theory focuses on the concept of children learning from observing others by acting on or not acting on what they see exhibited by their classmates. For example, they may see a classmate politely asking for a treat and getting one, or maybe they hear another classmate talking about something new they've learned, which teaches the student something new even if it's not something they try themselves.

This learning theory was founded by Albert Bandura. He conducted an experiment called the Bobo doll experiment in the early '60s, during which he studied children's behavior after they watched an adult act aggressively with a doll-like toy. He noted how the children reacted when the adult got rewarded, punished, or suffered no consequences after they attacked the doll. Bandura wrote about his findings in 1977, detailing social learning theory and how it affected the behavioral development of students.

There are four elements to social learning theory:

Attention, which calls upon different or unique lessons or activities to help children focus.

Retention, focusing on how the student will internalize information and recall it later on.

Reproduction, drawing on previously learned behavior and when it's appropriate to use it.

Motivation, which can extend from seeing other classmates being rewarded or punished for their actions.

By using social modeling based on these elements, teachers have a very powerful tool in their arsenal that can effectively guide their students to be more active in their learning, pay more attention, and channel their energy into their schooling.

Experiential Learning Theory

Experiential learning theory focuses on learning by doing. Using this theory, students are encouraged to learn through experiences that can help them retain information and recall facts.

Experiential learning theory, or ELT, was identified by David Kolb in 1984. Though his influence came from other theorists such as John Dewey, Kurt Lewin, and Jean Piaget, Kolb was able to identify four stages of ELT. The first two stages, concrete learning and reflective observation, focus on grasping an experience. The latter two, abstract conceptualization and active experimentation are about transforming an experience. To Kolb, effective learning is seen as the learner goes through the cycle of experiential learning theory. Students can enter the cycle in any way and at any point.

Some examples of this form of learning include taking students to the zoo to learn about animals instead of just reading about them or growing a garden to learn about photosynthesis instead of watching a video about it. By creating environments where students can learn and experience at the same time, teachers offer students the opportunity to immediately apply their knowledge and get real-world experiences. This approach also encourages teamwork and is shown to improve motivation.

How to Apply Learning Theories in Teaching

Teachers can create specific strategies and techniques to apply these learning theories in their classrooms. Teachers need to first focus on getting a well-rounded education to learn about all kinds of techniques for teaching and classroom management. Teachers need to understand learning theories to be prepared to utilize them in their classrooms.

An understanding of learning theories helps teachers connect to all different kinds of students. Teachers can focus on different learning styles to reach different students, creating teaching that focuses directly on student needs and aptitudes.

Take a look at other articles from WGU. Our articles feature information on a wide variety of subjects, written with the help of subject matter experts and researchers who are well-versed in their industries. This allows us to provide articles with interesting, relevant, and accurate information.

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When considering the best approach to helping students learn, teachers may call upon learning theories to support their educational pursuits. Read on to discover the five main educational theories and three supplemental theories that can make a big difference in how students learn.

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Cognitive Learning strategies and retention

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Cognitive Learning strategies and retention

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Ariel S. Winn,*,1, ² Lisa DelSignore, 3, ⁴ Carolyn Marcus, 2, ⁵ Laura Chiel, ⁶ Eli Freiman, ⁷ Diane Stafford, 8, ⁹ and Lori Newman 1, ¹⁰

Abstract

Introduction

Cognitive learning strategies are strategies that improve a learner's ability to process information more deeply, transfer and apply information to new situations, and result in enhanced and better-retained learning.

Methods

We developed an interactive workshop for a national conference of pediatric educators to teach five cognitive learning strategies. The specific strategies were (1) spaced retrieval practice, (2) interleaving, (3) elaboration, (4) generation, and (5) reflection. Each strategy was taught using an active learning exercise. We evaluated the effectiveness of the workshop through a commitment-to-change exercise in which we asked participants to commit to making a change in their teaching as it related to the workshop and then queried them 6 weeks later about their implementation successes and barriers.

Results

Of the 161 participants registered for the workshop, 52 completed the voluntary workshop evaluation. All 52 participants committed to making a change in their teaching as a result of the workshop. Of those 52 participants, 24 completed the 6-week follow-up survey. Eighty-two percent of those respondents ( n = 18) reported implementing a change based on the workshop, with 77% of respondents implementing a change that they had committed to directly after the workshop and 55% implementing a change that they had not originally committed to at the end of the workshop.

Discussion

This workshop successfully led to behavioral change in the teaching of cognitive learning strategies. We anticipate that this will lead to improved learning among the trainees whom participants teach.

Keywords: Cognitive Learning Strategies, Active Learning, Memory Science

Educational Objectives

By the end of this interactive workshop, learners will be able to:

1.

Identify and describe five cognitive learning strategies.

2.

Identify clinical teaching opportunities to apply cognitive learning strategies.

3.

Implement different cognitive learning strategies in various clinical teaching settings.

Introduction

Medical researchers project that the collective body of medical information will double every 73 days by 2020.1 It is incumbent on medical schools and clinical training programs to help students and trainees learn to absorb, organize, store, and retrieve this vast amount of information. Historically, students and trainees have been taught using passive learning strategies, such as rereading, highlighting, and cramming, along with attending lectures, conferences, or grand rounds as inactive participants. These passive learning strategies can be effective for short-term information recall, leading to the illusion of knowledge mastery, but are rarely effective in producing sustained learning.2-7

In contrast, there is emerging literature, popularized by the book Make It Stick: The Science of Successful Learning,4 indicating that applying cognitive learning strategies in active learning environments can help achieve more productive and sustained learning.4-9 Cognitive learning strategies are strategies that improve a learner's ability to process information more deeply, transfer and apply information to new situations, and result in enhanced and better-retained learning.6,10-11 These learning strategies engage learners in activities in which they are responsible for performing tasks while thinking about what they are learning and why they have reached particular solutions.4-9,12-14 There is solid evidence that routine integration of these strategies coupled with daily active learning practice results in higher-order and sustained learning outcomes.15-18

Although some medical educators have started to adopt active learning practices in the classroom setting, including the integration of problem-based learning, team-based learning, and flipped classroom models,12,19-22 many faculty have not received instruction on cognitive learning strategies.12 As more students enter medical school with exposure to cognitive learning strategies from their undergraduate college experiences, they will expect to engage in active learning using these strategies. Moreover, learners have increasingly begun to accept that delayed gratification and desirable difficulty lead to sustained retention of newly acquired knowledge and skills.4,23-25 Health professional students should therefore expect their faculty to be well trained in cognitive learning strategies.

In this workshop, participants learn the theory behind five specific evidence-based cognitive learning strategies. We identified these five strategies, after an extensive search of the literature, as valuable, practical, and easy to adopt within one's own teaching practice while greatly improving learning and retention of information. The five cognitive learning strategies addressed in this workshop include spaced retrieval practice, interleaving, elaboration, generation, and reflection2,4,6,8,9,12 (see Appendix A for definitions). Participants apply these cognitive learning strategies using concrete examples (both clinical and nonclinical) and engage in active group discussion and authentic practice. To encourage behavior change, participants then determine how to integrate these cognitive learning strategies into their current clinical teaching settings. This workshop provides a platform for health care professional educators to gain an understanding of five evidence-based cognitive learning strategies, apply these strategies, and then determine ways to incorporate cognitive learning into their teaching to promote knowledge gain, retention, and learner satisfaction. This workshop contributes to and enhances the existing literature on cognitive learning strategies, as it allows participants to practice each strategy and then determine practical ways they can incorporate the strategies when teaching in their own medical field or clinical discipline. Other workshops have focused primarily on questions, small-group discussions, or role-play as a way of teaching other active learning strategies based in cognitive learning theory.26-30 We know of no other source that provides this comprehensive educational experience.

Methods

Session Description and Implementation

We planned and presented this 90-minute workshop for the 2018 annual national meeting of the Association of Pediatric Program Directors (APPD). This workshop was adapted from a similar half-day retreat that we originally constructed for the Boston Children's Hospital Academy for Teaching and Educational Innovation and Scholarship, an interprofessional academy inclusive of self-identified clinician-educators (trainees, faculty, and health care professional staff) from all pediatric departments at Boston Children's Hospital.

A total of 161 participants registered for the APPD workshop. Registration information collected by the APPD organization showed that participants included pediatric residents, chief residents, and fellows, as well as junior and senior attending faculty members. No specific prerequisite knowledge of active learning or cognitive learning strategies was required. Our workshop was facilitated according to the outline and time line in the Table .

Table.

Time

Topic/Activity

Facilitator Responsible

Materials

5 minutes

Brief introduction to workshop objectives and facilitators

All facilitators

Microphones

15 minutes

Interactive didactic session on cognitive learning strategies ( Appendix B)

One facilitator

Laptop and projector for the PowerPoint presentation, microphones

50 minutes (10-minute sessions)

Small-group sessions:

Divided among facilitators

Cognitive learning strategies worksheet ( Appendix A, p. 1), large easel/flip chart with strategy already written out

15 minutes

Large-group discussion

All facilitators

Microphones

5 minutes

Workshop feedback completion

One facilitator

Commitment-to-change form ( Appendix H)

Facilitators of our session included attending physician educators, nonphysician medical educators, and chief residents (although we recognize that residents, fellows, or other health care professionals could also facilitate this session). All facilitators were well versed with the book Make It Stick: The Science of Successful Learning.4 Prior to the session, we suggested that each facilitator learn about the cognitive learning strategy he or she was responsible for presenting, either through the relevant sections of the book or through other relevant materials of the facilitator's choosing. Although we had more than five facilitators available to present the workshop, two facilitators could reasonably present the session in its entirety.

The first 5 minutes of the workshop involved a brief introduction to the session's organization, goals, and objectives and to each of the facilitators (name, educational role, and hospital/program affiliation). One facilitator then gave a 15-minute interactive didactic presentation ( Appendix B) that reviewed the differences between passive and active learning strategies, how active learning strategies promote learning for mastery, and how active learning strategies derive from cognitive learning theories. The presentation also included an overview of the specific cognitive learning strategies that would be practiced in small groups during the workshop.

The workshop then segued into the small-group sessions that focused on active practice of the five cognitive learning strategies over a 50-minute time frame. Participants were seated accordingly at five round tables. A limited number of chairs were assigned to each round table to encourage smaller group sizes. Groups were divided randomly, based on where participants chose to sit for the introductory portion of the workshop.

Facilitators were assigned to teach one cognitive learning strategy and rotated to each of the five tables while participants remained stationary. The facilitators were responsible for conducting a 10-minute session at each table based on their assigned strategy. Each 10-minute session was structured as follows:

The facilitator briefly reviewed the strategy and presented what was known about it based on educational and cognitive psychology literature (2 minutes).

The group engaged in an interactive activity to practice using the strategy and experience how it enhanced learning (5 minutes).

The group brainstormed suggestions on how the strategy could be applied to teaching in their clinical practice settings (3 minutes).

Each of the cognitive learning strategy activities the facilitators modeled is included in Appendices C- G. Participants were also given a cognitive learning strategy worksheet on which to take notes during the small-group sessions (first page of Appendix A). Please note that for programs in which only two facilitators are available, we suggest dividing the room in half, having one facilitator present two strategies and the other facilitator present three strategies, then switching. We have found that learning from multiple presenters enlivens the activities and discussions and reduces cognitive load.

After the small-group activity concluded, all participants reconvened as a large group to reflect on the session and pose questions to the facilitators for 15 minutes. Five of the seven facilitators made up the panel, whereas the additional two facilitators walked around the audience with microphones and stimulated discussion among the large group. Participants were encouraged to share experiences, questions, and challenges related to applying these cognitive learning strategies in actual clinical teaching settings. (For programs with two facilitators, we suggest one large-group discussion.) The last 5 minutes of the workshop were reserved for a short wrap-up session during which participants were encouraged to complete the commitment-to-change assessment form ( Appendix H). They were informed that they would receive an email follow-up from the facilitators in 6 weeks to inquire if they had implemented any changes to their teaching practices based on what was learned during the workshop.

Evaluation Strategy

Our evaluation strategy was based on the commitment-to-change framework31 first introduced in 1982 by Purkis.32 The framework measures behavioral change by asking attendants of an educational session to commit to a behavioral change. The framework then keeps track of the attendants to understand their success in the implementation of the behavioral change and identifies any barriers to successful implementation. At the end of our workshop, we asked participants to voluntarily complete our commitment-to-change assessment tool ( Appendix H). Six weeks after the workshop, we emailed the participants who completed the assessment tool. In the email, we included a scanned copy of their initial commitment-to-change form and asked them to complete an online assessment about their implementation successes and barriers ( Appendix I). We sent reminders at 1- and 2-week intervals.

Results

Of the 161 people registered for our workshop, 24 (14.9%) identified as residency program directors, 13 (8.1%) identified as fellowship program directors, 48 (29.8%) identified as associate residency program directors, five (3.1%) identified as associate fellowship program directors, 41 (25.5%) identified as chief or former chief residents, 10 (6.2%) identified as residents, three (1.9%) identified as hospitalists, five (3.1%) identified as coordinators, and 12 (7.4%) identified as other. We were unable to collect further data on the participants who attended the workshop and suspect that a small portion of those who registered did not attend and that a small percentage of attendants did not preregister.

Of those who attended the workshop, 52 completed our voluntary commitment-to-change form ( Appendix H) at the end of the workshop. One hundred percent of respondents reported they were planning to make a change in their teaching as a result of participating in the workshop. Two of the authors (Laura Chiel and Eli Freiman) reviewed the responses to question 2 separately and categorized the responses into the five cognitive learning strategies-spaced retrieval practice, interleaving, elaboration, generation, and reflection-and other (if unrelated or unclear relationship to a specific learning strategy). The two authors agreed on 96% of the forms. For the two forms without agreement, a third author (Lisa DelSignore) offered her categorization and prompted discussion, allowing them to reach 100% consensus. Eight respondents listed changes that corresponded to more than one cognitive learning strategy. The categorizations of these responses are listed in Figure 1 . The most frequent cognitive learning strategies cited were interleaving and reflection.

Forty-eight of 52 respondents wrote their email addresses on the initial form ( Appendix H) and were therefore able to participate in the follow-up survey. Twenty-two of these 48 participants completed the follow-up survey ( Appendix I), corresponding to a 46% response rate. Eighty-two percent of respondents ( n = 18) reported implementing a change based on the workshop. Seventy-seven percent of respondents ( n = 17) reported implementing one of the changes they had committed to at the end of the workshop. Fifty-five percent of respondents ( n = 12) implemented a change related to the workshop that they had not committed to at the end of the workshop. Fourteen percent of respondents ( n = 3) said that they had not yet implemented a change. Two of the authors (Laura Chiel and Eli Freiman) again reviewed the responses to question 3 separately and categorized the responses into the five cognitive learning strategies-spaced retrieval practice, interleaving, elaboration, generation, and reflection-and other. The two authors agreed on 100% of the forms. Six respondents listed changes that corresponded to more than one cognitive learning strategy. The categorizations of these responses are shown in Figure 2 . Three respondents did not implement any change based on the workshop. When asked about barriers to implementing change, two responded that they were not currently involved in any teaching, and one stated an intention to implement the change.

Discussion

We designed a faculty development workshop to teach pediatric educators five principles of cognitive learning strategies and found that participants were able to incorporate these learning strategies into their teaching as a result of the workshop. Our evaluation strategy was based on Purkis' commitment-to-change framework.32 The evaluation aligned with the third level of Kirkpatrick's evaluation model-learner behavior-in that the evaluation took place posttraining, when participants had returned to their own institutions, and determined the extent to which participants implemented or transferred what they learned during the training session.33 Using the commitment-to-change evaluation strategy provided solid evidence that participants gained knowledge and skills from the workshop and applied that learning to their own training programs. Those who did not implement a change reported that they either were not involved in teaching or still planned on implementing the change, without foreseeable barriers.

At the end of the workshop, participants were more committed to using interleaving and reflection than the other strategies. Interestingly, back at their home institutions, participants put all five strategies to use, suggesting that generation, elaboration, and reflection were easier to implement than participants had initially thought. In addition, more than half of the respondents reported implementing a change that they had not committed to during the workshop.

We have been able to reflect on the design and implementation of the workshop. Each activity was purposefully focused on a nonmedical topic, drawn from everyday life, allowing for presentation of the workshop across clinical disciplines and professions. Using nonmedical topics also ensured that medical information did not distract from the workshop. However, during each exercise, we brainstormed with the group how the strategy could be applied to clinical teaching. This sparked rich conversations as participants generated examples that related to their clinical settings. Participants also shared concerns about anticipated challenges and solutions to using the strategies. On further reflection, we realized that brainstorming implementation strategies could benefit from more time in future sessions. We also noted that all facilitators for the academy retreat and APPD workshop were physicians or involved in medical education. Given that these five cognitive learning strategies can be generalized to all health care professionals, it may be appropriate to have an interprofessional panel of facilitators, especially for audiences drawing from multiple professions. Inviting facilitators from varied health care professions routinely leads to the discovery of common teaching challenges and sharing of optimal solutions.

We believe that it is ideal to have five facilitators available to lead the workshop to allow one facilitator to teach each of the five cognitive learning strategies. We found that the variety of having five people rotate to each of the small groups increased the participants' interest and eagerness to learn all of the strategies. This configuration may present challenges for those trying to replicate the workshop, as not all educational programs may have this number of available facilitators. One solution to increase the number of presenters is to include residents or fellows as facilitators, as the strategies apply to all levels of learners, regardless of rank or seniority.

The evaluation strategy we used has limitations. Only a small portion of participants participated in the commitment-to-change activity. It is possible that those who participated were more likely to incorporate change into their teaching practices than those who did not participate. Furthermore, the outcomes were self-reported, and it is possible that participants over- or underestimated their incorporation of new teaching skills.

It is our hope that educators who gain an understanding of and experience with cognitive learning strategies through our structured workshop approach will implement these strategies when they teach their learners and when they train other educators. In this way, we hope to provide tools to confront the challenge of learning and retaining vast amounts of information so that it can be recalled quickly and applied appropriately in the delivery of optimal patient care.

Appendices

A. Handouts.docx

B. Introduction Slides.pptx

C. Spaced Retrieval Practice Facilitator Guide.docx

D. Interleaving Facilitator Guide and Handout.docx

E. Elaboration Facilitator Guide and Handout.docx

F. Generation Facilitator Guide and Handout.docx

G. Reflection Facilitator Guide and Handout.docx

H. Commitment-to-Change Initial Form.docx

I. Commitment-to-Change Follow-up Form.docx

All appendices are peer reviewed as integral parts of the Original Publication.

Acknowledgments

Drs. Winn and DelSignore are co-primary authors of this publication.

References

3. Mayer RE. The Promise of Educational Psychology-Volume II: Teaching for Meaningful Learning. Upper Saddle River, NJ: Merrill Prentice Hall; 2002. [ Google Scholar]

4. Brown PC, Roediger HL III, McDaniel MA. Make It Stick: The Science of Successful Learning. Cambridge, MA: Harvard University Press; 2014. [ Google Scholar]

7. Ambrose SA, Bridges MW, DiPietro M, Lovett MC, Norman MK. How Learning Works: Seven Research-Based Principles for Smart Teaching. San Francisco, CA: John Wiley & Sons; 2010. [ Google Scholar]

16. Fornari A, Poznanski A, eds. How-To Guide for Active Learning. Huntington, WV: International Association of Medical Science Educators; 2015. [ Google Scholar]

24. Bjork EL, Bjork RA. Making things hard on yourself, but in a good way: creating desirable difficulties to enhance learning. In: Gernsbacher MA, Pomerantz JA, eds. Psychology and the Real World: Essays Illustrating Fundamental Contributions to Society. 2nd ed. New York, NY: Worth Publishers; 2015:60-68. [ Google Scholar]

33. Kirkpatrick DL. Evaluating Training Programs: The Four Levels. San Francisco, CA: Berrett-Koehler; 1994. [ Google Scholar]

Articles from MedEdPORTAL : the Journal of Teaching and Learning Resources are provided here courtesy of Association of American Medical Colleges

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Applying Cognitive Learning Strategies to Enhance Learning and Retention in Clinical Teaching Settings

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Cognitive learning strategies are strategies that improve a learner's ability to process information more deeply, transfer and apply information to new situations, and result in enhanced and better-retained learning.We developed an interactive workshop ...

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The IP address used for your Internet connection is part of a subnet that has been blocked from access to PubMed Central. Addresses across the entire subnet were used to download content in bulk, in violation of the terms of the PMC Copyright Notice.

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At a glance

Culturally responsive teaching is a rich, intentional approach woven into every aspect of student learning.

It focuses on the assets students bring to the classroom rather than what students can't do.

It raises expectations and makes learning relevant for all students.

Culturally responsive teaching is a research-based approach to teaching. It connects students' cultures, languages, and life experiences with what they learn in school. These connections help students access rigorous curriculum and develop higher-level academic skills.

Our brains are wired to make connections. It's easier for our brains to learn and store information when we have a hook to hang it on. That hook is background knowledge. Students bring this knowledge to the classroom every day.

But for students of color, English language learners (ELLs), and other underserved student populations, those assets are often overlooked. When that happens, educators miss the chance to use them to support learning. (See recent work by Zaretta Hammond for the neuroscience behind this.)

Culturally responsive teaching values and reflects the assets of all students. By doing that, it raises academic expectations for all learners. It also sends the message that multiculturalism is an asset.

Dive deeper

The benefits of culturally responsive teaching

How culturally responsive teaching, UDL, and SEL work together

For educators: Culturally responsive teaching in the classroom

For educators: How to partner with families

Lydia Breiseth (director of Colorín Colorado), Shivohn García, PhD (senior director of the Impact team at Understood), and Shaquala Butler (Understood Teacher Fellow) contributed to this article.

About the author

About the author

Educators Team at Understood is made up of passionate writers, editors, educators, and subject matter experts who have worked in classrooms and with students who learn and think differently.

Reviewed by

Reviewed by

Karla Vigil, MAT is the chief executive officer and co-founder of the Equity Institute.

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Culturally responsive teaching helps create learning environments that validate and reflect the diversity, identities, and experiences of all students. Learn more.

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Cultural responsive teaching and the brain

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Cultural responsive teaching and the brain

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Culturally Responsive Teaching & the Brain

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Just recently I lead a seminar for a group of instructional coaches and BTSA support providers and I asked them to define culturally responsive teaching. It's usually how I start my workshops. Actually, I got them into groups of 5 and asked each group to draw me a picture of the process (Robert Marzano would call that a non-linguistic representation).

I ask them to do it because it gets at the mental models they are carrying around inside their heads about what they think it is.

More often than not, every group emphasizes a different aspect of culturally responsive teaching that is a mix of truth and misconceptions. It's like the story of the king who asked six blind men to tell them what an elephant was like. One felt his tail and said it was like a rope. Another had hold of a big floppy ear and likened the elephant to a fan. And so it went.

Well, that's pretty much what it's like hearing folks talk about culturally responsive teaching. In reality it isn't a set of best practices, but a process.

The Ready for Rigor Framework

I find what teachers (and instructional coaches) need is a framework for organizing the process. The Ready for Rigor frame takes the key elements of cultural responsiveness and organizes them into four practice areas. Unlike the individual part of the elephant that is mistaken for the whole, each area of the frame is interdependent with the others. The social-emotional and cognitive aspects of teaching and learning show up in each area. At its core is the neuroscience that unifies the frame: the brain's reaction to living in a racialized world as well as how it programs itself using culture.

The Inner Circle: Crosscutting Practices

Then there is the inner circle with the four staple practices of every culturally responsive teacher.

Affirmation - noticing and naming the unique talents and gifts of each child, especially those culturally grounded ways of being and expressing oneself.

Validation - acknowledging to students through word or deed the impact of unearned disadvantage in a racialized society without guilt or excuses.

Instructional Conversation - talking with students regularly about their learning process in order to move them safely into their zone of proximal development.

"Wise" Feedback - providing students with wise feedback, what Claude Steele says is the anecdote to stereotype threat. It is corrective feedback that first affirms the student's capacity to meet the goal or standard, tells him honestly where he missed the mark, gives him actionable steps to improve his learning, and helps him monitor his progress.

It Not Mysterious or Magic

There's no magic to the Ready for Rigor frame and it's not the only culturally responsive frame out there. The real point is that you have to have some type of framework to make culturally responsiveness operational. The art of cultural responsiveness lies in weaving together these four practices areas into a process that calms the brain and sets the stage for neuroplasticity where the brain can grow itself.

Learn more about how to operationalize the framework in my new book, Culturally Responsive Teaching and the Brain: Promoting Authentic Engagement and Rigor Among Culturally and Linguistically Diverse Students (Corwin, 2014).

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Why We Need a Framework for Culturally Responsive Teaching - Culturally Responsive Teaching & the Brain

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Just recently I lead a seminar for a group of instructional coaches and BTSA support providers and I asked them to define culturally responsive teaching. It's usually how I start my workshops. Actually, I got them into groups of 5 and asked each group to draw me a picture of the process (Robert Marzano would call that a non-linguistic representation).

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Four misconceptions about culturally responsive teaching

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Four misconceptions about culturally responsive teaching

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Culturally Responsive Teaching: 4 Misconceptions | Cult of Pedagogy

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In some cases, teachers think they’re practicing culturally responsive teaching, when in fact, they’re kind of not. Zaretta Hammond helps clear things up.

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Effective feedback is designed to determine a learner's level of understanding and skill development to plan the next steps towards achieving the learning intentions or goals.

Feedback is a compelling influence on learner achievement. When teachers seek or at least are open to what learners know, what they understand, where they make errors, when they have misconceptions when they are not engaged- then teaching and learning can be synchronised and powerful. Feedback to teachers makes learning visible
Hattie, J. (2009). Visible learning, Oxford, UK: Routledge, p173​

Feedback is a key element of the incremental process of ongoing learning and assessment. Providing frequent and ongoing feedback is a significant means of improving achievement in learning. It involves the provision of information about aspects of understanding and performance and can be given by practitioners, peers, oneself and from learners to practitioners.

Effective feedback assists the learner to reflect on their learning and their learning strategies so they can make adjustments to make better progress in their learning.

​Reporting to parents and families commonly occurs at least twice per year in a formal written statement from the school. Involving parents and families in the learning process by providing them with more frequent feedback about their child's learning progress and strategies they may use to assist their child to improve is effective in improving student achievement.

Purpose of feedback

Effective feedback is designed to determine a learner's level of understanding and skill development to plan the next steps towards achieving the learning intentions or goals.

Feedback provides the practitioner and learner with evidence about current knowledge and skill development. Understanding the learner's progress and level of achievement enables the practitioner to make decisions about the next steps to plan in the learning program. It enables the learner to reflect on their learning strategies to confirm them or make changes to improve their learning.

Feedback​

Feedback is one of the most effective teaching and learning strategies and has an immediate impact on learning progress. High-quality feedback is specific and ongoing. When delivered on time, Hattie's research shows feedback has an effect size of 1.13 on learning achievement.

Feedback from practitioner to the learner

Effective feedback from the practitioner:

focuses on the quality of the learner's work product and/or processes

motivates and challenges the learner to further develop their knowledge and skills

does not give praise, reward or punishment

recognises that which the student has done well and identifies what has been misunderstood or not understood

focuses on the quality of the work and is specific

is directly linked to the learning intentions and success criteria

may be spoken, a gesture or formalised in writing.

​Feedback from learner to practitioner

Listening to answers to questions and looking closely at the work of learners on learning tasks provides practitioners with powerful feedback about the level of learner understanding and their practice. This evidence supports reflection and can provide strategies to more effectively assist learners to make progress with their learning.

​Feedback from and to peers

Feedback often comes informally from and to peers. It can be improved and used productively if learners are taught concrete strategies for evaluating one another's work against the learning intentions and the success criteria and providing appropriate feedback. Knowing the questions to ask when evaluating learning assists learners in the process of self-assessment.

​​​Feedback improves learning

Feedback is designed to bring about an improvement in learners' performance and achievement. Feedback can be given by the practitioner or by peers. It can be either formal or informal. It can be oral or written, it can be formative or summative, but overall it must provide the learner with specific advice on how to improve their performance.

Feedback starts with learning intentions

The process of giving feedback begins with the practitioner and learner clarifying the learning intentions (or goals) for the activities they are undertaking and the success criteria by which they will assess the level of achievement to be demonstrated by learners. This enables the learners to measure their performance in terms of both mastery of the set task and the processes inherent in it. It also helps them to be clear about future goals.

​Elements of a good learning intention

Learning intentions explicitly state what the learner should know, understand and be able to do by the end of an activity, unit of work, or a lesson and they are expressed in language learners understanding. The learning intention should answer the learner who asks "Why are we learning this?"

Sharing and providing clarity on what the learner will learn is the purpose of the learning intention. Clearly stated skills, knowledge or understandings are the focus of the learning Intentions and are written in a language the students can understand.

A learning intention is not what task the learner should be able to do; it is not 'Write an essay' but rather 'Explain why people migrated to Australia (Victorian Curriculum F-10 History, level 9). A learning intention is what students should learn as a result of the teaching and learning activities. The medium by which learners demonstrate their learning is the essay but it is not the goal.

Another example is from Music (Victorian Curriculum F-10 level 4) where learners may create a sound picture. The Learning Intention is to 'understand variation in rhythmic patterns. The medium by which learners demonstrate their learning is a sound picture.

Learners may also set their learning intentions.

The success criteria set the performance by which achievement of the learning intentions will be measured. The success criteria are made known to the learners and for learning to be most effective the success criteria are co-constructed with the learners.

Read more about learning intentions.

Effective feedback informs the learner about their progress towards meeting the success criteria. A useful model for feedback is presented by Hattie as 'Feed Up, Feed Back, Feed Forward. In this model the learner considers three questions:

Feed Up

1. Where am I going (what are my learning intentions?)​

Feed Back​

2. How am I going (what does the evidence tell me?)​

Feed Forward

3. Where to next (what learning activities should I do to make better progress?)​

Read more about the feedback model in The power of feedback

Feedback is timely

Feedback needs to be timely. It needs to be given while there is still time for the learners to act on it and to monitor and adjust their learning.

It can be 'in-the-moment' in the case of classroom dialogue and discussion. The practitioner will receive feedback from the way learners answer questions and the questions asked by them. To effectively gather evidence from questioning about who does and who does not understand it may be necessary to vary the way, questions are asked in the classroom to ensure all learners can participate and provide evidence of their level of understanding. This evidence should indicate whether it is necessary to reteach, provide more varied discussion and practice, use peer teaching or move the learners forward.

​Feedback is clear and focuses on improvement strategies

Feedback on learning tasks also needs to be regular and provided as soon as possible after completion. Written, descriptive comments need to be in the language that is accessible to the learners and should refer back to the preliminary discussion of learning goals and success criteria. Effective feedback provides specific guidance on how to improve learning outcomes and it enables the learner to think about the learning involved in the task and not just the activity of completing the task.

​Feedback encourages reflection

The amount of feedback needs to be limited to what learners can reasonably accept. Effective feedback does not merely correct learners' errors but actively requires them to reconsider their work and think about why, for example, spelling and punctuation may be incorrect, where a mistake has been made in mathematical workings or an idea or situation has been misunderstood.

​Errors measure misunderstandings

It is recognised that making errors is a fundamental point in improving learning. Feedback on where the misunderstandings and misconceptions are occurring assists learners to move to greater understanding and success, to become more self-directed and to believe in their ability to complete tasks and reach goals.

​Feedback is more than a grade

Feedback on formal tasks that just include marks or grades or comments that discuss the level of performance and suggest that the learning journey is finished should be avoided. This can prevent the learner from fully considering and acting on the feedback. Multiple forms of feedback, such as comments, questions, and discussion provided frequently during learning encourage engagement and motivation to succeed.

Effective feedback is understood by the recipient and motivates them to want to learn more effectively.

Giving effective feedback

When practitioners develop sound professional relationships with learners based on mutual respect, feedback is a two-way process that supports progress in learning for the learners and understanding about where the learners are on the learning continuum for the practitioners.​

Tips for giving effective feedback to learners

​Explain to the learners that you are focusing on helping them to understand the assessment of their learning

Encourage learners to ask questions about their feedback

Make a regular time to discuss feedback with learners on an individual or small group basis

Advise learners that they will have an opportunity to ask questions about their assessment

Encourage them to note down their questions​

Try to give feedback as close to the learning and assessment task as possible

Be specific and explicit about feedback, providing examples where possible

Establish that the student understands what is being discussed

Ask the student what they think they need to improve on

Offer your advice about future steps for improvement

Invite conversations by asking learners to discuss the work with you and/or with their peers​

Digital portfolios or ePortfolios are useful tools for enabling learners to maintain a permanent record of their learning journey and they provide practitioners with a readily accessible record of the learner's self-assessment and reflections on their learning strategies.

A digital portfolio is a carefully crafted presentation of a student's learning journey using digital artefacts as evidence of learning. It has a clear purpose and is well organised. It both develops and demonstrates learning through effective student reflection. The learner uses the higher-order metacognitive skills to consider what they learned and self-assess what they need to focus on next to progress their learning. Digital artefacts can be derived from learning activities across all learning domains. An effective digital portfolio can be used to celebrate achievement, demonstrate progress through comparison over time and guide future learning.​

The production of a digital portfolio encourages a partnership between students and their teachers and increased student ownership and accountability for their learning. A digital portfolio provides students, their parents and teachers with a rich record of learning. A digital portfolio is not a collection of all student tasks, but careful selections that demonstrate growth and new knowledge such as two artefacts that show progression in learning over time.

A digital portfolio can be used in many ways. In a more sophisticated form the digital portfolio can be developed over several years and used as an ongoing record of progress, perhaps presented at "Student-Led conferences" and used to inform future learning plans. Best practice portfolios would integrate student goal setting, self-assessment and reflection on learning with the presentation of learning examples. Portfolios could also refer to expected student learning outcomes (Victorian Curriculum F-10 ).

The practitioner uses the evidence provided by the portfolio to reflect on the effectiveness of their instruction and to make adjustments to their teaching practice.

​​​​​​How to create a digital portfolio​

A digital portfolio consists of:

The digital artefacts within the portfolio

Digital artefacts may be audio, video, images, text and presentations constructed using any of the thousands of creative tools. Software such as Word/Pages, PowerPoint/Keynote, Excel/Numbers, movie maker/iMovie and free edustar products can be used. Online WEB2.0 services like SlideShare, Prezi, voki and mind42 and more recently iPad/android Apps are being used in schools to create digital artefacts.

The presentation platform used to organise and display the portfolio

The portfolio and its artefacts might be stored in the 'Cloud? in a student account. Portfolios can be organised and presented using software, web services or apps. Common software products such as Word/Pages, PowerPoint/Keynote and MS: OneNote can be used to construct digital portfolios. Current Web-based options include the Department's own Global2 and services such as Wikispaces, Evernote, Dropbox, Google-Apps for education, Prezi for Education, Weebly. There is also an increasing range of android/IOS apps such as Flowboard, Evernote, Voicethread, Open School portfolio, Three Ring, Kidblog, Weebly. Also, some learning management systems have the functionality to facilitate a digital portfolio.

Web-based

Android/IOS apps

​The processes used to construct it

In all effective digital portfolio programs, teachers need to provide support to students in the process of creating digital content and effectively selecting, reflecting and presenting this content through the portfolio.

​How to use a digital portfolio

A digital portfolio can be used in many ways. In a more sophisticated form the digital portfolio can be developed over several years and used as an ongoing record of progress, perhaps presented at "Student-Led conferences" and used to inform future learning plans. Best practice portfolios would integrate student goal setting, self-assessment and reflection on learning with the presentation of learning examples. Portfolios could also refer to expected student learning outcomes (Victorian Curriculum F-10).

The portfolio could be used by teachers as an assessment vehicle for the Victorian Curriculum F-10 domains mentioned above. It could be used by students for employment purposes.​

The power of purposeful feedback, Greenstein L, 2010.
Greenstein demonstrates how to provide specific and concise descriptive feedback on learners' work.

How am I doing?, Chappuis, J, 2012
Chappuis discusses the features of effective feedback with a focus on younger learners and offers succinct advice on how to put it into practice.

Assessment: feedback to promote student learning, Spiller D, 2009
Dorothy Spiller discusses some of the issues involved in the implementation of the feedback process.

The power of feedback. Review of Educational Research, Hattie J Timperley H, 2007
Hattie and Timperley summarise research on feedback and develop a model for effective feedback in the classroom. They discuss types of feedback, especially that which enables students to become more self-directed and internally motivated and what the evidence suggests about how best to implement feedback in the classroom.

Helping students understand assessment, Chappuis, J. 2005
This article explains how descriptive feedback improves student learning and provides tips for providing better quality feedback to learners.

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