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Both HLW and ELW's goals were to discuss learning for transfer, which does not occur automatically. It is something that needs to be learned and practiced. Not only do student need to learn how to learn for transfer and practice the necessary skills. However, teachers also need to learn how to teach for transfer and practice teaching it effectively to their students. Although both papers focus on the "idea" of transfer and share similarities in thought; HLW focuses on the cognitive realm and ELW goes beyond the cognitive realm, discussing non-cognitive  competencies, such as personality traits, behaviors, and intrapersonal and interpersonal competencies (a more psychological outlook) and their desirable outcomes in education and the workplace. Deeper learning refers to learning for transfer in ELW.

Both papers agree that learning for transfer means being able to apply knowledge beyond the classroom. The goal of instruction, as EWL says, is too prepare students to accomplish tasks and solve problems that are different than those addressed during instruction. This is what will prepare student for the labor market and allow them to have knowledge that will be transferable across occupations.

Similarly, HLW discusses how learning for transfer means that students need to learn knowledge beyond context dependency. If students learn knowledge with context dependency, then their knowledge will not be flexible enough to apply outside of that context. Hence, it is important for students to learn in multiple contexts in order to have more flexibility with their knowledge and not be context-dependent. HLW discusses near transfer vs. far transfer. Essentially, transfer is considered near if the learning contexts are similar and far if they are dissimilar.  Helping student develop far transfer is the goal of teachers, as this means students will able to apply their knowledge beyond the classroom.

Both HLW and ELW discuss how the brain can be cognitively trained to learn "for" transfer by learning how to organize knowledge and how to create highly connective networks between nodes of knowledge.

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Organization of knowledge: experts vs. novices

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Organization of knowledge: experts vs. novices

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HWL discusses how organizational structure is important for information retrieval and how the way students organize knowledge will affect how they learn and apply the knowledge they have acquired. It is not just the isolated pieces of knowledge alone that result in learning. However, it is the way the knowledge is connected and organized.

Both HLW and ELW  discuss how experts organize information in conceptual chunks that are well connected with other knowledge. This creates complex structures that allow experts to notice meaningful patterns, and therefore, use them to solve complex and more generalized problems. By having highly interconnected relationships among chunks of knowledge, experts are able to use multiple knowledge organizations when solving problems.

As HWL discusses, the more nodes of knowledge are interconnected with other nodes, the easier it will be for the brain to travel from one piece to another (which experts generally have). However, novices generally have isolated nodes that lack much connection with other nodes. Hence, this lack of connection inhibits the brains ability to travel between nodes and therefore recognize and respond to patterns. Hence, experts need to help students, or novices, to create such organizational structures.

Similarly, EWL discusses how experts have large banks of well-organized facts and procedures in their long-term memory and have coded them into well-connected schemas. Their methods of encoding and organizing helps them "interpret new information and notice features and meaningful patterns of information that might be overlooked by less competent learners" (pg 79). Furthermore, these schemas are what enable experts to more readily retrieve needed information when solving a problem.

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Longterm-memory/working memory and cognitive load: experts vs. novices 

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Longterm-memory/working memory and cognitive load: experts vs. novices 

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ELW discusses how experts commit knowledge to their long-term memory, coding their knowledge into "well-connected schemas" (pg 79). Hence, the organization and well-connected nature of knowledge that experts have gets stored in the long-term memory (lightening the burden on the brain's working memory, which has a finite limited capacity). This idea is also discussed in HLW, but is referred to as "cognitive load." Many times, both the teachers and students may have the same amount of cognitive resources to complete a task. However, due to the lack of fluency for the student, many tasks may require a high cognitive load for them. Fluency and automaticity (which ELW says is the result of knowledge going into the long-term memory) demands less cognitive resources making it easier for expert to complete complex tasks.

HWL talks about how expertise can be a liability, as well as an advantage. Since teachers have this "unconscious competence" (pg 97) that allow them to apply knowledge automatically and instinctively, which their students lack, teachers tend to become blind towards the learning needs of their novice students. This is called "expert blind spot" (pg 99). Hence, teachers sometimes end up having unrealistic expectations since they fail to recognize the increased cognitive load their students have compared to them, making it difficult for their students to complete complex tasks. Teachers sometimes lack the understanding of the difference between knowledge being in the working memory for students vs. knowledge being the long-term memory for teachers and the huge difference that can make in the application of knowledge for students.

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Using Analogies as a method of learning/completing complex tasks 

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Using Analogies as a method of learning/completing complex tasks 

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Even though ELW and HLW seem to agree on the use of analogies to organize knowledge in the memory (as seen in column 1), they do not seem to agree on the use of analogies for the purposes of learning and completing complex tasks.

It seemed to me that HLW refers to analogies as a positive  and important way to help students apply their prior knowledge and know where it is and is not applicable. HLW discussed how instructors use analogies in order to point out both similarities, as well as differences, while also discussing the limitations of analogies. Through carefully designed analogies, students can be "guided away from misconceptions" (pg 27).

HLW discusses that research shows when giving students problems that have already been solved and having them explain the solution to themselves, then students will be able to solve new problems better.  The reasoning HLW gives for this is that by reasoning through a solved problem, students will develop more cognitive resources to use for strategizing how to work through a new problem. However, if only given non-worked out problems, students wont have cognitive resources to work off of, and therefore, may not be learning much. HLW referred to this as the worked-example effect, which is one way to reduce cognitive load for students so they can focus on a particular dimension of learning.

ELW, on the other hand, claims that evidence generally shows people who learn to solve a first problem using an analogy, which ELW defines as when "one solves a problem by using the solution of a similar problem" (pg 77),  will not always find it easier to solve the second problem. So, to me, it doesn't seem that ELW supports the use of analogies to learn/solve problems.

Somehow, I feel that the organization of knowledge in the brain and the process of learning/solving complex problems really go hand and hand, and therefore, cannot be separated. Hence, it doesn't "fully" make sense to me that ELW can see an analogy to be useful for the organization of knowledge, but not useful for learning/solving complex problems. Maybe I'm misunderstanding something or failing to make a connection. If you can shed light on this issue, I'd love to hear!

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HLW discusses how analogies provide structure for students to organize new information and learn better. Analogies help guide  "students see past superficial similarities and instead focus on deeper connections and relationships" (pg 58). ELW also views analogies as a useful way to organize knowledge in the memory in order to solve problems.

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Cognitive and Non-cognitive competencies/skills 

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Cognitive and Non-cognitive competencies/skills 

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ELW spend time taking about cognitive (IQ) and non-cognitive (intrapersonal and interpersonal) skills/competencies when discussing deeper learning and 21st century skills. HLW did discuss cognitive skills. However, I didn't recall reading anything about non-cognitive skills in their paper.

ELW took time to discuss these cognitive and non-cognitive skills in reference to education outcomes, as well as job outcomes. I liked how ELW delved in the sociocultural perspective, within the interpersonal domain, and its importance for deep learning.

HLW mentioned how learning is holistic and intersects with developmental processes in a student's life, including their experiences and beliefs. However, HLW did not dive too deeply into this realm and its effect on learning (only mentioned it). HLW's main focus was on cognition, and therefore, they unraveling cognition in great detail, which ELW didn't. So, I think they complemented each other well in that respect.

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I like how ELW described the story of the teachers who implemented teaching practices to create a new culture of learning within their math class.  This new culture not only welcomed multiple dimensions of mathematical work (which seems to be a good step to helping students learn math for transfer), but they also had students be responsible for each other's learning of math. Students were put into groups and were assigned roles.  What they found was that this innovative approach led to "gains in cognitive competencies" and "showed that students developed positive dispositions towards mathematics and conscientiousness in addressing mathematics problems -- important intrapersonal competencies" (pg 88). The percentage of students who believed that anyone could be good at math if they tried hard was 84% compared to 52% in a traditional class.

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I was deeply intrigued by the findings in ELW regarding the correlation between personality factors and grades; specifically, how only conscientiousness, among the personality factors, was correlated with grades in higher education.

Furthermore, it was found that conscientiousness "is a valid correlate of job performance across all performance measures studied" (pg 51). It predicts performance and wages across a many different occupations.

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This has made me interested in learning more about interpersonal and intrapersonal competencies and how I can make that a focus in my classroom, alongside of cognitive competencies.  As a math teacher, I was shocked to hear that 84% of students had made such a statement, as I rarely hear that in a math classroom. Most often, students come into class with the presupposition that only "mathy" people are good at math and that they aren't one of them. Hence, I truly enjoyed reading the non-cognitive aspects of transfer in ELW, as I am a believer of its importance in student learning.  This fall term I will be teaching my flipped class. Hence, I believe I will have plenty of opportunities to focus on intrapersonal facets that will encourage "productive beliefs about learning" (pg 84) within my students.

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I want to know why this personality trait stand out most compared to the other four (openness, agreeableness, extroversion, cognitive ability, and emotional stability). I never gave much credit to conscientiousness when it came to both myself or the effect it would have on my students. As teachers, and as students, we think our success depends on our cognitive abilities. However, this is an interesting twist to the deeply ingrained mentality within our education culture and beliefs about knowledge transfer and it's dependence on cognitive competence (IQ). Just thinking back to the story about the Railside school in ELW and the importance of interpersonal competence, namely conscientiousness, I began to become more interested in opening my mind to these new avenues and rethinking my deeply rooted views about knowledge and competence.

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Why are there discrepancies between these findings in ELW?

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Why are there discrepancies between these findings in ELW?

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1) "empirical studies show that cognitive competencies are

able to account for only a small fraction of the association between education and earning" (pg 49).

2) "concluded that general cognitive ability was more important for later job success than

conscientiousness or any other intrapersonal or interpersonal competency" (pg 49).
3) "Cognitive test scores explained about 6 percent of the variance in

performance, leaving 94 percent to be explained by other factors" (pg 50).

The study in #2 seems to claim that cognitive ability was more important in job success. However, the studies in #1 and #3 doesn't seem to give cognitive competencies such importance. So why it is considered significantly important in one study and not significantly important in the other two studies.

***Note:  I consider "performance" and "education and earning" to all imply "job success." ***

So, it just seems to me that the study in #2 contradict the studies in #1 and #3. Thoughts?