# data[].attributes.headline
Directions: Post one teaching strategy you read about or one that you found on the Internet or in the literature. Indicate how it promotes higher order thinking and provide your rationale.                                        If you wish to, consider uploading an image, website link, video etc. for the teaching strategy you selected. Visit the Week #10 Announcement for a video and image of how to do this. Share your ideas with your peers, so that they can use them in their practice!

# data[].attributes.subject
Directions: Post one teaching strategy you read about or one that you found on the Internet or in the literature. Indicate how it promotes higher order thinking and provide your rationale.                                        If you wish to, consider uploading an image, website link, video etc. for the teaching strategy you selected. Visit the Week #10 Announcement for a video and image of how to do this. Share your ideas with your peers, so that they can use them in their practice!

# data[].attributes.body
*Connect learning to clinical practice using factual knowledge simulations

Rationale...

Linking what we learn and applying it to clinical practice is crucial in the development of higher level thinking. This teaching strategy helps nurses go beyond simple recall, it requires them to use what was learned by analyzing and applying education in specific instances. Simulations help prepare students for higher level thinking. Being able to analyze, synthesize, evaluate, and apply what was learned in simulation lab requires critical thinking skills. For example, taking a patient's temperature can be taught in clinical, but actually understanding what a normal temperature is and when it is not normal, what to do clinically, and how to help the patient is significant. Taking the temperature is the basic knowledge but understanding what to do after you get an abnormal reading is where higher level thinking must be used to help evaluate what is next. Higher level thinking is critical for patient care and safety of the patient. Applying what students learn is significant in reaching a higher level of learning. When knowledge is retained and applied, it ties together important aspects of what skills are needed to be able to understand at a higher level. Flipped classroom strategy can be used in this case. Giving students information to review before class and having them apply the information, helps with getting a more thorough understanding of the information learned. Being aware of what strategies are effective and how knowledgeable the teacher is about the different strategies, also plays a vital role in the success of the strategies to improve higher level thinking. A match game could be used to show different body temperatures. Use additional cards to match what intervention is needed for the temperature shown. This clinical assessment skill can help improve advanced levels of thinking by analyzing and evaluating what needs to be done in each scenario.

# data[].attributes.body
I've always been educated to think on my own about a question or problem to come up with a solution. Most of the times my answers won't be right, but that's the point of the exercise. It's like a warm-up for my brain and thoughts. Once I came to my conclusion with rationales, I would then discuss with my peers or friends and discuss their thoughts. This collaborative effort helps us both with ideas and solutions that we can later report to a larger audience. I feel this method helps encourage critical thinking and prompts learners to analyze and discuss reasoning before engaging in peer discussions. It helps individuals to think on their own and requires reflection and evaluation to better understand and compare a peer's perspective. As I verbalize my thoughts and listen to others, it will help clarify my misunderstandings and develop a more reasonable judgement on the problem. I do believe this strategy may not be for everyone, but it has helped me both clinically and in classroom discussions to help with engagement and a self-awareness in learning.

I can recall my nursing school clinical days; I was taking care of a post-op patient who had pain despite receiving pain medications by the nursing staff. I discussed this with my peer, and we each gave our thoughts and rationales. I felt that maybe the pain medications prescribed were not strong enough and the patient could use more, but my peer brought up a thought that the patient could be anxious and amplified his pain level. This is an example of how we each gave our thoughts and came away with possible reasons to the presenting problem.

# data[].attributes.body
The teaching strategy that promotes higher level thinking that I chose is problem-based learning, or PBL. This method boosts students critical thinking and requires using previous knowledge to resolve problems. This is a student-centered, self-directed learning approach, where students can actively take part in the learning, collaborate with peers, and solve real-world problems. This facilitates improvement in problem-solving skills, clinical thinking, and clinical reasoning, to overall promote better patient care. PBL allows facilitators to provide real-life problems students would face, allowing them to assess, discuss, and solve the problem to be more prepared in the real world. Practicing various scenarios that could happen helps one feel more prepared, confident, and competent in the clinical setting. This is so important in the nursing field! Students can work together with peers to solve problems, which also improves communication skills and allows for peer feedback. In nursing, PBL can be implemented with case studies and real-world scenarios, as well as in simulation. PBL can also allow for discussions and reflection time upon completion of solving the scenarios, case study, or simulation. Open discussions and reflections are additional methods that can aid in higher level thinking. They can provide deeper thought processes, feedback, and ways to improve. PBL can be used in nursing education, for continued education training, and in the clinical setting to further individual’s thinking and skills. The above article goes into more depth about PBL and a study done to show its benefit in emergency settings. I especially liked Figures 1 and 2 towards the middle of the article to represent the teaching implementation of PBL. The teacher introduces the lesson and scenarios and the students recognize the problem. The students then identify, assess, and solve the problem, and upon completion there is a chance for discussion, feedback, and reflection. I strongly believe PBL is vital in the nursing field and can help enhance nurse’s thinking, reasoning, and clinical skills to ultimately improve patient care. I look forward to utilizing PBL as a teaching strategy in my future role as an educator!

# data[].attributes.attachment_link.readable_text
Abstract

At present, with the rapid increase of emergency knowledge and the improvement of people's requirements for medical quality, the traditional teaching mode cannot fully meet the needs of emergency teaching in the new era. PBL is a project-based teaching that allows students to have a deeper understanding of content knowledge and to better apply what they have learned to their lives. This paper aims to improve the clinical emergency teaching mode by PBL teaching method, and improve the comprehensive ability of clinical emergency of medical students. This article proposes a problem-based PBL imaging teaching method, combining the characteristics and content of clinical emergency courses, focusing on students, highlighting the problem-solving process, and improving students' creative thinking ability. To cultivate students' interest in clinical learning, develop their self-learning ability, train their teamwork and communication skills, and cultivate their ability to set, question and solve questions, so as to promote medical students' overall comprehensive ability to integrate specialized knowledge and clinical practice. In this paper, the PBL teaching method and the traditional teaching method of comparative experiments show that the PBL teaching method can more effectively highlight the characteristics of clinical emergency medicine teaching mode, and make full use of the limited emergency teaching resources, so as to improve the quality of clinical emergency teaching. Compared with the traditional teaching mode, the theoretical knowledge and clinical operation skills of medical students under the PBL teaching mode are improved by 13%, Autonomous learning ability, communication ability and creative thinking ability have also been relatively improved.

Keywords: PBL teaching method, traditional teaching method, imaging diagnosis, clinical emergency, performance of PBL

1 Introduction

With the rapid evolution of mankind from the large-scale industrial age to the information age and even the age of artificial intelligence, we are increasingly aware of the seriousness of the various challenges that physicians have to face. The unified teaching method based on classroom teaching is the most widely used teaching method in medical colleges and universities in China. The traditional teaching mode focuses on teaching knowledge, although it can cultivate medical students with solid basic theoretical knowledge, but the lack of clinical practice ability and problem-solving ability will cause the phenomenon that theoretical knowledge and practical operation ability are divorced, so it is difficult to adapt to the clinical practice process. A relatively single teaching method often loses students' interest and independent thinking ability, making teachers' guidance and students' learning burdens heavier and more difficult. Therefore, in clinical emergency education, in addition to transferring knowledge, it is more important for students to learn independent thinking, literature review, and the ability to realize autonomous learning, and to improve students' ability to explore and solve problems, so as to cultivate high-quality suitable for the development of the times Medical talents. At the same time, this teaching adapts to the trend of modern teaching and the development of emergency medicine. Applying this model not only enables medical students to quickly grasp the relevant knowledge points, but also cultivates their learning ability and improves their ability to effectively apply their knowledge when dealing with clinical problems.

Although originally designed as a teaching method for graduate admissions in medicine, problem-based learning (PBL) has been widely used in undergraduate medicine, science, and social science courses. Although it is generally acknowledged that new learners of PBL need support, this does not provide a good description of the undergraduate course, which makes some students feel incomprehensible. In this submission, Moro C provides many extensive considerations and practical suggestions to support the transition of learners to PBL and universities. In a globalized world where the diversity of learners is increasing, this kind of support is particularly important in a learner-centered and socially responsible higher education pattern. But his research is not comprehensive enough, and more in-depth research is needed to prove the feasibility of this method ( Moro and Mclean, 2017). The formative assessment of clinical teaching for emergency medicine (EM) teachers is limited. The purpose of this study is to develop a behavior-based tool to assess EM teachers' clinical teaching skills during shift and provide feedback. Dehon e uses a three-stage structured development process. In the first stage, the nominal group technology is used to communicate with a group of teaching staff, and then with residents to generate potential assessment projects. Phase 2 includes an independent focus group and uses improved Delphi technology to evaluate the projects generated in phase 1 with faculty and residents as well as a group of experts. Since then, residents have divided the programs into novice, intermediate and advanced educator skills. Once the items to be included are identified and then ranked, the investigators build them into the tool (phase 3). Results: the final tool "teacher shift card" is a behavior anchored assessment and feedback tool to facilitate feedback to EM teachers on their teaching skills during the shift. However, his method is not supported by specific experimental data and lacks accuracy of experimental results ( Dehon et al., 2018). In the past 20 years, social work education has built a bridge between the classroom and the scene by learning clinical skills through customer simulation. Pecukonis EV outlines an innovative simulation model, combined with LS, for teaching motivation interview (MI). In addition, he also discussed the guiding principles and specific steps of using simulation and LS to teach MI. Unfortunately, most simulation models ignore the method of real-time guidance and monitoring students. In the implementation of clinical simulation, there are few opportunities to correct students' behaviors or practice new skills at the best teachable time in the interview. This instruction must wait until the end of the interview and the beginning of the presentation. With the addition of LS, the students' simulation experience has been enhanced, because the tutor is now an active participant in the interview. With LS, teachers can now direct and even simulate appropriate clinical responses and interventions. However, the research model is too complex to be put into practical application ( Yan, 2017; Pecukonis, 2021; Ramadan, 2021).

The innovation of this article lies in the advantages of the PBL teaching method, breaking through the traditional learning method, giving full play to the student-centered teaching method, cultivating students' interest and ability in autonomous learning, and improving the ability of autonomous learning. The article also integrates integrated cognitive activities such as questioning, judging, comparing, choosing and analyzing, synthesizing and generalizing knowledge. ability. Ability to think, solve problems, and solve problems; In order to improve the quality of clinical emergency teaching, it is necessary to cultivate students' teamwork ability, expand their knowledge, and master professional clinical emergency operation skills.

2 Implementation of Problem-Based Learning Based Image Teaching Method in Clinical Emergency

2.1 Problem-Based Learning Teaching Method

PBL is a problem based learning (PBL) which was founded by Howard Barrows, an educator in 1969 at the Medical College of McMaster University in Canada. That is, problem-based learning is a student-centered, group oriented and teacher oriented learning method ( Umami, 2018; Liu, 20192020). The PBL model originated in medical education and is an inquiry-based teaching method, that is, a core learning approach for research-based learning, integrated practice courses. This method is in the form of group discussion in a complex and substantive problem situation, so that students can solve problems through independent research and cooperation, and learn and obtain the scientific knowledge behind the problems, so as to make it possible. It is a kind of education method combining basic science and clinical practice. The biggest feature of this teaching method is to change the passive learning of traditional teaching methods into active learning ( Petruk, 2017; Gallagher et al., 2017). According to current research, in this teaching method, students are first grouped, and then questions are set. Under the guidance of teachers, each group of students discusses and analyzes to find answers to the problems. In the teaching process, firstly, students learn the professional theoretical knowledge more deeply by searching for answers on their own; secondly, through multiple rounds of group discussion and summarization, they have exercised their learning ability, communication skills and teamwork ability, and finally students deal with the actual situation. The ability to question can also be greatly improved ( Stephanie and Hughes, 2016; Tarling et al., 2016). The traditional teaching method (Lecture-Based Learning), that is, the method of "learning based on teaching," referred to as LBL ( Light and Razak, 2020; Xu et al., 2022), is a traditional theoretical teaching method based on the teacher's teaching ( Ananga, 2020). It is an education-based teacher-centered teaching method that emphasizes the transfer of knowledge in the classroom. Cannot meet the needs of students for knowledge and practice, development skills are not enough to improve students' ability to explore and solve problems ( Dzombak et al., 2020; Posteraro et al., 2020). PBL education is a new educational strategy that allows students to find effective solutions to situational problems. This educational strategy is very consistent with the current theoretical theories and educational principles ( Macqueen et al., 2016). In the medical field, the PBL medical teaching model is a process in which medical students work in small groups, with the participation and guidance of a tutor, to formulate, discuss and learn about a complex, multi-scenario, real-world problem-based topic or case.

2.2 Interpretation of Low-Quality Medical Images With Deep Learning Methods

2.2.1 Image Degradation Mechanism

Assuming that A is a low-quality image and B is a corresponding high-quality image, the image degradation mechanism can be expressed as follows:

Among them, σ represents the image degradation function in a broad sense, such as additive noise, multiplicative noise, compound noise, etc.

2.2.2 Deep Learning Image Restoration Paradigm

Low quality images arise because of the presence of many unnecessary or redundant interfering information in the image data, which must be corrected prior to image enhancement processing and classification processing. The image restoration model based on deep learning can be expressed as a regression paradigm of supervised learning: assuming that the network model is M, it represents the modeling function of the image degradation mechanism, which can be regarded as the optimal approximation to the inverse function σ−1 ; The input of is the low-quality image A, and the output result is expressed as M(A). The restoration requires that M(A) be as close as possible to the corresponding high-quality image Y. Training the recovery network can be seen as optimizing the following loss function:

The above loss function generally only considers the mean square error of the gray values of the pixels corresponding to the restored image M(A) and the high-quality image B. Representative algorithms include MLP, CNN, etc. In addition to directly learning high-quality images, some also link residual learning and restoration, directly learning the noise distribution of the image, and the regression paradigm can be expressed as the following form:

Among them, M(A) is the image noise fitted by the network, which is the real image noise, which can be obtained by the following calculation

That is, the difference between a low-quality image and a high-quality image. Compared with directly learning high-quality images, learning the noise distribution makes the optimization of the network easier, but to obtain the final restored image N, a further subtraction operation is required:

We can basically get the recovered image by the above subtraction operation, but we need to enhance the image in order to fully obtain the information in the image.

2.3 Gradient Regularization Image Enhancement Model

The results of image processing depend heavily on the mathematical model developed. Even for the same image, the results obtained using different mathematical models may vary greatly. Therefore, in the early stage of image restoration, people generally use known a priori information to build a gradient model.

2.3.1 Gradient Regularization Image Restoration Paradigm

arg min M+1 2 M−B 2+ρ 2 t⊗M−B 2,

(6)

Where t is the gradient operator, which represents the convolution operation, and is the balance factor. It can also be simplified to:

argmin M+1 2 M−B 2+ρ 2 t⊗(M(X)−B) 2.

(7)

2.4 Heuristic Information

Image enhancement is a widely used digital image processing technique, and currently, there are many methods used for image enhancement. As with other image restoration methods, since there is a corresponding image as a reference, the method mentioned above is no longer used here, and the calculation formula is as follows:

10 ln 10 (M A X 2 M S E(C,Z) ).

(8)

MAX represents the maximum gray value of the image. The image similarity is measured from three aspects: brightness, contrast, and structure. The calculation formula is as follows:

k=2 η v η e+x 1 η v 2+η e 2+x 1.

(9)

j=2 σ v σ e+x 2 σ v 2+σ e 2+x 2.

(10)

Among them, , represent the mean value of the restored image v and the reference image e, , represent the standard deviation of v, e, σ v e represents the covariance between the two,x 1 ,x 2 ,x 3 are smoothing constants, used To avoid the situation where the denominator appears to be 0, the value is generally entered as follows:

Generally, H 1=0.01,H 2=0.03 , and L represent the maximum value of the image gray scale, and the value range is [0,1,0,]. The smaller the value, the lower the image distortion. The higher the image distortion rate, the higher the risk of introducing information or components that do not exist in the original image, which can have serious consequences, such as the addition of tissue components to biomedical images, which can affect the doctor's diagnosis of the condition.

3 Experiments Based on Problem-Based Learning Teaching Method in Clinical Emergency

3.1 Experiment Object

Using the cluster sampling method, 50 students who practiced in a tertiary A hospital were used as the control group and received traditional teaching methods; 48 students who practiced in the emergency department were used as the experimental group and received PBL imaging teaching methods. After the teaching, the theory and skills of the two groups of students were evaluated; before and after the teaching, the two groups of students used self-study assessment tools, Skala Attitudes Skills Communication Skills and the Chinese version of the Critical Thinking Scale ( Gruppen, 2017; Messman et al., 2020). According to the internship arrangement, evaluate and statistically analyze the evaluation results, and include all interns in the internship evaluation form. And before entering the emergency internship, at the end of the departmental internship, the comprehensive examination transcript will be evaluated, and the evaluation results will be statistically and data analyzed. The general information of the experimental group and the control group was compared with the pre-hospital assessment scores, and the difference was not statistically significant ( p > 0.05), which was comparable.

The control group used traditional teaching methods, centered on the instructor, and intensively taught once a week. The content of the course included two basic elements: theoretical knowledge and technical skills. One week before the end of the internship, the trainees will be evaluated based on theory and skills.

The experimental group adopts the PBL teaching method, emphasizing the student-centered approach, integrating clinical case group discussions and simulated clinical scenarios into the teaching process, allowing students to analyze cases and find answers, thereby improving their own abilities. In this kind of curriculum construction, we break the content arrangement of the disease as the outline, teaching content as the outline of symptoms, and set the common clinical symptoms of emergency medicine, such as: dyspnea, chest pain, abdominal pain, coma, etc.

3.2 Teaching Preparation

Improve clinical education resources: establish and improve the clinical literature search network in hospitals, emergency departments, and student cards ( Kim et al., 2018; Brown, 2021). Strictly select teachers with lessons: select clinical education teachers and create a clinical education team in the emergency department. The team is evaluated and approved by the education and research department of the emergency department, and selects emergency educators with solid basic theoretical knowledge, professional knowledge and awareness, responsibility and communication skills, and excellent knowledge dissemination skills ( Dull et al., 2018).

3.3 Draw Up an Education Plan

Complete the training content of the teachers in the experimental group, and determine a unified teaching plan based on the mastery of the relevant PBL teaching concepts and methods, and the syllabus, purpose, requirements, and content of the clinical emergency teaching course. Using multimedia to explain the concept of PBL teaching method and the teaching method based on question and discussion ( Dehon et al., 2019; Karki, 2020; Tabassum et al., 2022), organize and teach teachers to discuss methods of mobilizing students' enthusiasm. Determine the PBL teaching content, such as case selection for frequently-occurring diseases that are more practical. Complete the PBL problem design PBL teaching cases are developed with the most typical emergency and frequently-occurring disease as the core, establish poorly structured problems, and complete the PBL problem design. Prepare 3 cases, each batch of students in the emergency department are required to complete one case, each case is divided into three times, each case has three acts, each act is arranged for independent study (2 days), concentrated discussion (1 class hour), and Group summary (1 class hour).

3.4 Draw Up a Training Plan

Pre-admission training control group for students: explain the syllabus, purpose, content, and assessment requirements of clinical emergency medicine students, and distribute critical thinking survey forms and questionnaires on clinical medicine students' cognition and attitude towards PBL. Emphasize that during the clinical emergency internship, strictly abide by the rules and regulations of clinical emergency ( Levine et al., 2016; Bertino et al., 2021). Experimental group: Explain the syllabus, purpose, content and assessment requirements of clinical emergency medicine students, and distribute critical thinking survey forms and questionnaires on medical students' cognition and attitude towards PBL. Then carry out the training before the implementation of PBL, that is, explain the concept of the PBL teaching model, the implementation method, the purpose of implementing PBL in the clinical emergency department, and the main points of cooperation. Distribute PBL teaching cases to allow students to preview in advance and ask students to analyze and discuss the cases, prepare and record their presentations.

Pre-admission training control group for students: based on traditional knowledge transmission, the one-to-one teaching method, namely LBL teaching method, is based on the traditional knowledge transmission, the teaching teacher implements the teaching of clinical emergency students according to the internship syllabus and requirements. Teaching tasks, first review relevant theoretical knowledge, combined with common clinical emergency diseases, students complete the internship tasks in the emergency department under the leadership of the teacher. Experimental group: PBL + LBL teaching method is adopted. The specific implementation methods are as follows: 1) Self-directed learning: After entering the course, students can find the best arguments and answers through reading textbooks, searching literature, consulting teachers, etc. in combination with relevant questions raised in the case, and can share the collected evidence with each other. One student recorded his doubts or the answers he found, and reported when preparing for group discussion ( Ahn et al., 2016; Runde et al., 2016). Also ask students to think about: ① How to consider the changes in the patient's condition? ②Try to analyze the causes and mechanisms of the above changes in the patient's condition? ③The current diagnosis? ④Current management? 2) Organizing discussion: Arrange students to report the results of the group study, ask questions based on actual clinical cases, the students report and speak, use the brainstorming method, each student puts forward their own opinions, and teaches the teacher to supplement the scenes involved in the problem and further ask questions, The team leader will make a record, and the team leader will list the best answers to the questions after the discussion ( Choi et al., 2019; Jain et al., 2020). In the course of the experiment, the teacher is responsible for coordinating, motivating them to actively participate in the discussion, ensuring that the discussion direction is targeted at the teaching purpose, allowing students to understand the clinical manifestations of patients during the discussion process, learn the key points of knowledge such as communication skills with patients, strengthen students' understanding and mastery of clinical emergency operation in the emergency department, and improve clinical thinking and problem-solving ability (Sengan, Khalaf, Rao, Sharma, Amarendra, Hamad; Jain et al., 2021). 3) Summarize: After the discussion, the teacher and students will jointly summarize the characteristics of clinical emergency department, the concept of common diseases, clinical diagnosis and precautions. At the same time, students are required to complete a reflection diary and sort out the ideas for solving problems to promote Theory and practice ( Patidar and Pichholiya, 2016; Tabassum et al., 2017).

3.5 Data Processing and Statistical Analysis Methods

Use EXCEL software to make a unified data entry template. After a researcher has verified that the questionnaire is correct twice, the content of the questionnaire is recorded in the data template, and the survey data is statistically analyzed with SPSS 20.0 ( Hexom et al., 2017), test level α Set to 0.05, the p values of the two probabilities are statistically significant, so p < 0.05. 1) The measured data is expressed by (±S), and the measured data is expressed by frequency or percentage. 2) For the measurement data that satisfies the smoothness and uniformity of the variance, please use two independent t-test samples, and use the chi-square test to measure the data between the two groups. For measurement data that does not satisfy the smoothness and uniformity of the variance, the rank sum test is used for the total score data, and the comparison between two or more groups is performed using ANOVA. 3) Use factor analysis and stepwise regression analysis to analyze the factors that affect critical thinking ability. 4) When comparing the emergency clinical ability before and after baseline, 2 weeks later, and 1 month later, the paired sample test is used for volume data, and the second test is used for measuring data. p < 0.05 is considered to be statistically significant.

3.6 Problem-Based Learning Teaching Implementation Plan Process in Clinical Emergency

The implementation plan based on the PBL teaching method in clinical emergency teaching is shown in Figure 1. The clinical emergency PBL teaching method experiment is completed according to the process, and then compared with the traditional teaching method, the experimental results are obtained.

The PBL teaching mode is a problem-based teaching mode with students as the core. The teaching process is shown in Figure 2:

FIGURE 2.

The teaching process of PBL teaching mode.

4 Performance Analysis Based on Problem-Based Learning Imaging Teaching Method in Clinical Emergency Teaching

4.1 Basic Information of the Two Groups of Students

As shown in Table 1, the experimental group and the control group were similar in age, basic average academic performance of professional courses, and the composition ratio of men and women, and the difference was not statistically significant ( p > 0.05).

4.2 Comparison of Problem-Based Learning Experimental Courses and Overall Attitudes

The basic abilities of students' PBL are scored by five levels of 1-5. As shown in Table 2, there is no statistical difference between the scores of the two groups of students ( p > 0.05).

As shown in Table 3, the experimental group and the control group have statistically significant differences in the experimental classes, satisfaction, sense of responsibility, and confidence in future work ( p < 0.05). It can be seen that the scores of the students in the experimental group are higher than those in the control group. Therefore, it can be concluded that the overall attitude of the students in the experimental group is better than that of the control group.

4.3 Teaching Situation

Two independent sample tests were used to compare the clinical ability scores of the two groups of students during two and 4 weeks of teaching. The result is shown in the figure below:

As shown in Table 4, except for the dimension of clinical handling ability ( p > 0.05), the scores of the PBL teaching experiment group and the total score of emergency clinical ability were higher than those of the control group, the difference was statistically significant ( p < 0.05) As shown in Table 5, after 4 weeks of teaching, except for the clinical management ability, the scores and total scores of the clinical emergency ability of the PBL teaching group were significantly higher than those of the control group, and the difference was statistically significant ( p < 0.05).

Figure 3 depicts the trends of the clinical emergency ability of the two groups of students with the internship time. The results show that the two groups of students have improved with the elapse of internship in the emergency department, but the PBL group has a larger increase than the control group. It is statistically significant ( p < 0.05). It can be seen that the PBL teaching method has a greater improvement in clinical emergency ability.

In this experiment, repeated measures analysis of variance was used to compare the clinical first aid capabilities of the two groups of trainees after 2 and 4 weeks. The between-group effects are divided into different groups (i.e., PBL teaching group and control group), the interaction effect is the grouping time, and the between-group effects are (2 weeks, 4 weeks).

The results are shown in Table 6: 1) Except for the clinical management dimension, p is less than 0.05 for the inter-group effects, indicating that the differences in the overall mean values of the various dimensions of clinical emergency ability in different groups are statistically significant, that is, PBL teaching can improve students. 2) The intra-group effect p < 0.05 means that the difference in the overall mean scores of the various dimensions of the clinical emergency ability and the overall average of the total score is statistically significant. With the change of time, the clinical emergency ability of the trainees has improved. 3) Except for the clinical management ability, the interaction effect is less than 0.05, which means that the interaction effect of different measurement time and group has statistical significance on the overall mean difference of the various dimensions of emergency clinical ability and the total score, indicating that 4 weeks of PBL teaching can significantly improve the clinical performance of students Emergency room capacity.

TABLE 6.

Project

Between-group effects

Within-group effect

Interaction effect

F

p

F

p

F

p

4.4 Comparison of Ratings of Different Teaching Methods Between Two Groups of Students

The scoring system uses a 10-point system to score the adaptability, satisfaction, pressure, and improving communication skills of the teaching method. The results are shown in Figure 4.

As shown in Figure 4, there are statistically significant differences between the two groups of students in terms of their degree of adaptation, satisfaction, stress, and improving their communication skills ( p < 0.05). From the perspective of adaptation, The overall adaptation rate of the experimental group is lower than that of the control group. Therefore, the students in the experimental group are less adaptable to the PBL teaching method than the control group students' adaptation to the traditional teaching method. From the perspective of stress, the experimental group's pressure score is higher. Therefore, the PBL teaching method brings more pressure to the study of the experimental group students than the traditional teaching method to the control group of students. From the perspective of satisfaction and the improvement of personal communication skills, the scores of the experimental group are greater than those of the comparison group, so the PBL teaching method improves personal communication skills more than the traditional teaching method.

As can be seen in Figure 5, the results show that the two different teaching methods give two groups of students a statistically significant difference in the level of cultivation of various abilities, p < 0.05, and the improvement rate of the experimental group is greater than that of the control group. Therefore, the PBL teaching method gives The increase in learning ability brought by the experimental group students was more significant than the increase in learning ability brought by the traditional teaching method to the control group.

4.5 Comparison of the Two Groups of Students' Theoretical and Operational Performance

The independent sample test was used to analyze the theoretical scores of the two groups of students. The results are shown in Table 7. The test scores of the students in the experimental group were higher than those in the control group, and the average scores in the clinical experiments were also higher than those of the control group. The difference was statistically significant ( p < 0.05). It can be seen that The PBL teaching method has a greater improvement in theoretical and operational performance.

4.6 Comparison of the Questionnaire Received by the Two Groups of Students After Teaching

Table 8 shows the comparison of the effects of the experimental group and the control group after teaching. The results of the questionnaire show that the special gains of the experimental group after teaching are greater than those of the control group, except for the improvement of innovation ability, which is not statistically significant ( p > 0.05). The improvement of self-learning ability was the biggest difference between the experimental group and the control group, and the differences in other aspects were statistically significant ( p < 0.05).

TABLE 8.

Project

Type

Test group

Comparison group

t

p

N

17

32

N

19

36

N

32

35

N

8

40

5 Conclusion

The PBL teaching method can fully exercise people's thinking skills such as decision-making, creativity, reasoning and analysis in the process of conceiving solutions, exploring independently, making decisions and seeking solutions to problems. This article is based on the PBL teaching method to construct a clinical emergency teaching plan and carry out experimental application. In contrast to traditional teaching methods, the clinical emergency PBL teaching method constructed in this article is more prominent in improving the performance of students' clinical emergency ability, and can more effectively improve students' theoretical technical operation level, autonomous learning ability, communication ability and communication judgment ability. Thinking ability has obvious advantages in experimental teaching. It is more conducive to cultivating medical students' good study habits, enthusiasm and the ability to make full use of existing learning resources, thereby improving the comprehensive clinical professional quality of medical students. In the operation skills learning in the medical emergency, the PBL teaching method makes the learning goals and meanings of medical students clearer. The important role of various skills operations has been verified in the implementation process, and the proactiveness of the operation skills practice has been improved. However, there are still some shortcomings in this research. The traditional teaching model is deeply ingrained. A small number of teachers and students have a certain degree of rejection to the difficulty of adapting to the PBL teaching method. There is no multi-factor analysis on the factors that affect the effect of experimental teaching. Further research is needed. In the future article, we will focus on the factors that affect the effectiveness of PBL teaching practice from several levels.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Author Contributions

XX and YW: Writing-original draft preparation. SZ and FL: Editing data curation, supervision.

Funding

This work was supported by Key Fund of Department of Cardiology, Shandong University Qilu Hospital (Qingdao) (QDKY2019ZD04), People's Livelihood Science and Technology Project of Qingdao (22-3-7-smij-6-nsh), Qingdao Key Health Discipline Development Fund.

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.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Choi J., Choi C., Kim S. H., Ko H. (2019). Medical Information Protection Frameworks for Smart Healthcare Based on IoT, Proceedings Of The 9th International Conference On Web Intelligence, Mining And Semantics (WIMS 2019). [Google Scholar]

2. Dzombak R., Pham K., Beckman S. (2020). Learning Design: Examining Programmatic Learning Outcomes and the Influence of Disciplinary Perspectives on Design Pedagogy. Int. J. Eng. Educ. 36 (2), 623-632. [Google Scholar]

3. Tabassum S., Ali S., Shamsher S. (2017). Rate and Indications of Emergency Caesarean Sections at a Teaching Hospital in Pakistan. Med. Forum Mon. 28 (9), 21-24. [Google Scholar]

Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Articles from Frontiers in Genetics are provided here courtesy of Frontiers Media SA

# data[].attributes.attachment_link.title
Performance of Problem-Based Learning Based Image Teaching in Clinical Emergency Teaching

# data[].attributes.attachment_link.description
At present, with the rapid increase of emergency knowledge and the improvement of people's requirements for medical quality, the traditional teaching mode cannot fully meet the needs of emergency teaching in the new era. PBL is a project-based ...

# data[].attributes.body
Lexie Lohman

Peer Learning/Instruction

I chose this teaching method as nurses tend to rely on others when they do not know the answer to a question. Whether this information is obtained from another nurse or a physician, we always like to know the evidence-based reasoning on why things are performed a certain way. Once learned, we often share our findings with others for them to learn, and to avoid the chance of making an error. This promotes critical thinking and encourages higher-level thinking as we tend to want to know the “why” of what we are doing. Peer learning suggests that as individuals, we learn from those around us. We learn to problem solve, collaborate, develop new ideas, and to also develop socially. This method of learning creates collaboration of those who may have different viewpoints and helps learners develop confidence. Examples of peer learning include study groups, group tests, projects, and problem-solving scenarios such as a decompensating patient. This is vital in the nursing world, as without peer learning and problem solving, nurses and physicians would not be able to properly care for the needs of their patients.

Learning the "why" of why we do certain things helps the learner understand the critical reasoning behind the idea.

Drawbacks of this teaching strategy include students feeling that time is not being managed due to disinterest in the learning topic, and faculty need to frequently analyze the peer learning strategy, as a quiet and withdrawn student may not work well with a student who is independent and assertive. I feel that working in surgical services, I can use Peer Learning as we work with many members of the hospital daily. Using peer learning can help bring together different viewpoints and competencies and encourage others to learn from different perspectives, which increases higher-level learning.

# data[].attributes.attachment_link.readable_text
Abstract

In peer instruction, instructors pose a challenging question to students, students answer the question individually, students work with a partner in the class to discuss their answers, and finally students answer the question again. A large body of evidence shows that peer instruction benefits student learning. To determine the mechanism for these benefits, we collected semester-long data from six classes, involving a total of 208 undergraduate students being asked a total of 86 different questions related to their course content. For each question, students chose their answer individually, reported their confidence, discussed their answers with their partner, and then indicated their possibly revised answer and confidence again. Overall, students were more accurate and confident after discussion than before. Initially correct students were more likely to keep their answers than initially incorrect students, and this tendency was partially but not completely attributable to differences in confidence. We discuss the benefits of peer instruction in terms of differences in the coherence of explanations, social learning, and the contextual factors that influence confidence and accuracy.

Keywords: Group decisions, Peer instruction, Metacognition, Confidence, Decision making

Significance

Peer instruction is widely used in physics instruction across many universities. Here, we examine how peer instruction, or discussing one's answer with a peer, affects students' decisions about a class assignment. Across six different university classes, students answered a question, discussed their answer with a peer, and finally answered the question again. Students' accuracy consistently improved through discussion with a peer. Our peer instruction data show that students were hesitant to switch away from their initial answer and that students did consider both their own confidence and their partner's confidence when making their final decision, in accord with basic research about confidence in decision making. More broadly, the data reveal that peer discussion helped students select the correct answer by prompting them to create new knowledge. The benefit to student accuracy that arises when students discuss their answers with a partner is a "process gain", in which working in a group yields better performance than can be predicted from individuals' performance alone.

Peer instruction is specific evidence-based instructional strategy that is well-known and widely used, particularly in physics (Henderson & Dancy, 2009). In fact, peer instruction has been advocated as a part of best methods in science classrooms (Beatty, Gerace, Leonard, & Dufresne, 2006; Caldwell, 2007; Crouch & Mazur, 2001; Newbury & Heiner, 2012; Wieman et al., 2009) and over a quarter of university physics professors report using peer instruction (Henderson & Dancy, 2009). In peer instruction, instructors pose a challenging question to students, students answer the question individually, students discuss their answers with a peer in the class, and finally students answer the question again. There are variations of peer instruction in which instructors show the class's distribution of answers before discussion (Nielsen, Hansen-Nygård, & Stav, 2012; Perez et al., 2010), in which students' answers are graded for participation or for correctness (James, 2006), and in which instructors' norms affect whether peer instruction offers opportunities for answer-seeking or for sense-making (Turpen & Finkelstein, 2007).

Despite wide variations in its implementation, peer instruction consistently benefits student learning. Switching classroom structure from didactic lectures to one centered around peer instruction improves learners' conceptual understanding (Duncan, 2005; Mazur, 1997), reduces student attrition in difficult courses (Lasry, Mazur, & Watkins, 2008), decreases failure rates (Porter, Bailey-Lee, & Simon, 2013), improves student attendance (Deslauriers, Schelew, & Wieman, 2011), and bolsters student engagement (Lucas, 2009) and attitudes to their course (Beekes, 2006). Benefits of peer instruction have been found across many fields, including physics (Mazur, 1997; Pollock, Chasteen, Dubson, & Perkins, 2010), biology (Knight, Wise, & Southard, 2013; Smith, Wood, Krauter, & Knight, 2011), chemistry (Brooks & Koretsky, 2011), physiology (Cortright, Collins, & DiCarlo, 2005; Rao & DiCarlo, 2000), calculus (Lucas, 2009; Miller, Santana-Vega, & Terrell, 2007), computer science (Porter et al., 2013), entomology (Jones, Antonenko, & Greenwood, 2012), and even philosophy (Butchart, Handfield, & Restall, 2009). Additionally, benefits of peer instruction have been found at prestigious private universities, two-year community colleges (Lasry et al., 2008), and even high schools (Cummings & Roberts, 2008). Peer instruction benefits not just the specific questions posed during discussion, but also improves accuracy on later similar problems (e.g., Smith et al., 2009).

One of the consistent empirical hallmarks of peer instruction is that students' answers are more frequently correct following discussion than preceding it. For example, in introductory computer science courses, post-discussion performance was higher on 70 out of 71 questions throughout the semester (Simon, Kohanfars, Lee, Tamayo, & Cutts, 2010). Further, gains in performance from discussion are found on many different types of questions, including recall, application, and synthesis questions (Rao & DiCarlo, 2000). Performance improvements are found because students are more likely to switch from an incorrect answer to the correct answer than from the correct answer to an incorrect answer. In physics, 59% of incorrect answers switched to correct following discussion, but only 13% of correct answers switched to incorrect (Crouch & Mazur, 2001). Other research on peer instruction shows the same patterns: 41% of incorrect answers are switched to correct ones, while only 18% of correct answers are switched to incorrect (Morgan & Wakefield, 2012). On qualitative problem-solving questions in physiology, 57% of incorrect answers switched to correct after discussion, and only 7% of correct answers to incorrect (Giuliodori, Lujan, & DiCarlo, 2006).

There are two explanations for improvements in pre-discussion to post-discussion accuracy. First, switches from incorrect to correct answers may be driven by selecting the answer from the peer who is more confident. When students discuss answers that disagree, they may choose whichever answer belongs to the more confident peer. Evidence about decision-making and advice-taking substantiates this account. First, confidence is correlated with correctness across many settings and procedures (Finley, Tullis, & Benjamin, 2010). Students who are more confident in their answers are typically more likely to be correct. Second, research examining decision-making and advice-taking indicates that (1) the less confident you are, the more you value others' opinions (Granovskiy, Gold, Sumpter, & Goldstone, 2015; Harvey & Fischer, 1997; Yaniv, 2004a, 2004b; Yaniv & Choshen-Hillel, 2012) and (2) the more confident the advisor is, the more strongly they influence your decision (Kuhn & Sniezek, 1996; Price & Stone, 2004; Sah, Moore, & MacCoun, 2013; Sniezek & Buckley, 1995; Van Swol & Sniezek, 2005; Yaniv, 2004b). Consequently, if students simply choose their final answer based upon whoever is more confident, accuracy should increase from pre-discussion to post-discussion. This explanation suggests that switches in answers should be driven entirely by a combination of one's own initial confidence and one's partner's confidence. In accord with this confidence view, Koriat ( 2015) shows that an individual's confidence typically reflects the group's most typically given answer. When the answer most often given by group members is incorrect, peer interactions amplify the selection of and confidence in incorrect answers. Correct answers have no special draw. Rather, peer instruction merely amplifies the dominant view through differences in the individual's confidence.

In a second explanation, working with others may prompt students to verbalize explanations and verbalizations may generate new knowledge. More specifically, as students discuss the questions, they need to create a common representation of the problem and answer. Generating a common representation may compel students to identify gaps in their existing knowledge and construct new knowledge (Schwartz, 1995). Further, peer discussion may promote students' metacognitive processes of detecting and correcting errors in their mental models. Students create more new knowledge and better diagnostic tests of answers together than alone. Ultimately, then, the new knowledge and improved metacognition may make the correct answer appear more compelling or coherent than incorrect options. Peer discussion would draw attention to coherent or compelling answers, more so than students' initial confidence alone and the coherence of the correct answer would prompt students to switch away from incorrect answers. Similarly, Trouche, Sander, and Mercier ( 2014) argue that interactions in a group prompt argumentation and discussion of reasoning. Good arguments and reasoning should be more compelling to change individuals' answers than confidence alone. Indeed, in a reasoning task known to benefit from careful deliberation, good arguments and the correctness of the answers change partners' minds more than confidence in one's answer (Trouche et al., 2014). This explanation predicts several distinct patterns of data. First, as seen in prior research, more students should switch from incorrect answers to correct than vice versa. Second, the intrinsic coherence of the correct answer should attract students, so the likelihood of switching answers would be predicted by the correctness of an answer above and beyond differences in initial confidence. Third, initial confidence in an answer should not be as tightly related to initial accuracy as final confidence is to final accuracy because peer discussion should provide a strong test of the coherence of students' answers. Fourth, because the coherence of an answer is revealed through peer discussion, student confidence should increase more from pre-discussion to post-discussion when they agree on the correct answers compared to agreeing on incorrect answers.

Here, we examined the predictions of these two explanations of peer instruction across six different classes. We specifically examined whether changes in answers are driven exclusively through the confidence of the peers during discussion or whether the coherence of an answer is better constructed and revealed through peer instruction than on one's own. We are interested in analyzing cognitive processes at work in a specific, but common, implementation of classroom-based peer instruction; we do not intend to make general claims about all kinds of peer instruction or to evaluate the long-term effectiveness of peer instruction. This research is the first to analyze how confidence in one's answer relates to answer-switching during peer instruction and tests the impact of peer instruction in new domains (i.e., psychology and educational psychology classes).

Method

Participants

Students in six different classes participated as part of their normal class procedures. More details about these classes are presented in Table 1. The authors served as instructors for these classes. Across the six classes, 208 students contributed a total of 1657 full responses to 86 different questions.

Materials

The instructors of the courses developed multiple-choice questions related to the ongoing course content. Questions were aimed at testing students' conceptual understanding, rather than factual knowledge. Consequently, questions often tested whether students could apply ideas to new settings or contexts. An example of a cognitive psychology question used is: Which is a fixed action pattern (not a reflex)?

1. Knee jerks up when patella is hit

2. Male bowerbirds building elaborate nests [correct]

3. Eye blinks when air is blown on it

4. Can play well learned song on guitar even when in conversation

Procedure

The procedures for peer instruction across the six different classes followed similar patterns. Students were presented with a multiple-choice question. First, students read the question on their own, chose their answer, and reported their confidence in their answer on a scale of 1 "Not at all confident" to 10 "Highly confident". Students then paired up with a neighbor in their class and discussed the question with their peer. After discussion, students answered the question and reported the confidence for a second time. The course instructor indicated the correct answer and discussed the reasoning for the answer after all final answers had been submitted. Instruction was paced based upon how quickly students read and answered questions. Most student responses counted towards their participation grade, regardless of the correctness of their answer (the last question in each of the cognitive psychology classes was graded for correctness).

There were small differences in procedures between classes. Students in the cognitive psychology classes input their responses using classroom clickers, but those in other classes wrote their responses on paper. Further, students in the cognitive psychology classes explicitly reported their partner's answer and confidence, while students in other classes only reported the name of their partner (the partners' data were aligned during data recording). The cognitive psychology students then were required to mention their own answer and their confidence to their partner during peer instruction; students in other classes were not required to tell their answer or their confidence to their peer. Finally, the questions appeared at any point during the class period for the cognitive psychology classes, while the questions typically happened at the beginning of each class for the other classes.

Results

Analytic strategy

Data are available on the OpenScienceFramework: https://mfr.osf.io/render?url=https://osf.io/5qc46/?action=download%26mode=render.

For most of our analyses we used linear mixed-effects models (Baayen, Davidson, & Bates, 2008; Murayama, Sakaki, Yan, & Smith, 2014). The unit of analysis in a mixed-effect model is the outcome of a single trial (e.g., whether or not a particular question was answered correctly by a particular participant). We modeled these individual trial-level outcomes as a function of multiple fixed effects - those of theoretical interest - and multiple random effects - effects for which the observed levels are sampled out of a larger population (e.g., questions, students, and classes sampled out of a population of potential questions, students, and classes).

Linear mixed-effects models solve four statistical problems involved with the data of peer instruction. First, there is large variability in students' performance and the difficulty of questions across students and classes. Mixed-effect models simultaneously account for random variation both across participants and across items (Baayen et al., 2008; Murayama et al., 2014). Second, students may miss individual classes and therefore may not provide data across every item. Similarly, classes varied in how many peer instruction questions were posed throughout the semester and the number of students enrolled. Mixed-effects models weight each response equally when drawing conclusions (rather than weighting each student or question equally) and can easily accommodate missing data. Third, we were interested in how several different characteristics influenced students' performance. Mixed effects models can include multiple predictors simultaneously, which allows us to test the effect of one predictor while controlling for others. Finally, mixed effects models can predict the log odds (or logit) of a correct answer, which is needed when examining binary outcomes (i.e., correct or incorrect; Jaeger, 2008).

We fit all models in R using the lmer() function of the lme4 package (Bates, Maechler, Bolker, & Walker, 2015). For each mixed-effect model, we included random intercepts that capture baseline differences in difficulty of questions, in classes, and in students, in addition to multiple fixed effects of theoretical interest. In mixed-effect models with hundreds of observations, the t distribution effectively converges to the normal, so we compared the t statistic to the normal distribution for analyses involving continuous outcomes (i.e., confidence; Baayen, 2008). P values can be directly obtained from Wald z statistics for models with binary outcomes (i.e., correctness).

Does accuracy change through discussion?

First, we examined how correctness changed across peer discussion. A logit model predicting correctness from time point (pre-discussion to post-discussion) revealed that the odds of correctness increased by 1.57 times (95% confidence interval (conf) 1.31-1.87) from pre-discussion to post-discussion, as shown in Table 2. In fact, 88% of students showed an increase or no change in accuracy from pre-discussion to post-discussion. Pre-discussion to post-discussion performance for each class is shown in Table 3. We further examined how accuracy changed from pre-discussion to post-discussion for each question and the results are plotted in Fig. 1. The data show a consistent improvement in accuracy from pre-discussion to post-discussion across all levels of initial difficulty.

Fig. 1.

The relationship between pre-discussion accuracy (x axis) and post-discussion accuracy (y axis). Each point represents a single question. The solid diagonal line represents equal pre-discussion and post-discussion accuracy; points above the line indicate improvements in accuracy and points below represent decrements in accuracy. The dashed line indicates the line of best fit for the observed data

We examined how performance increased from pre-discussion to post-discussion by tracing the correctness of answers through the discussion. Figure 2 tracks the percent (and number of items) correct from pre-discussion to post-discussion. The top row shows whether students were initially correct or incorrect in their answer; the middle row shows whether students agreed or disagreed with their partner; the last row show whether students were correct or incorrect after discussion. Additionally, Fig. 2 shows the confidence associated with each pathway. The bottow line of each entry shows the students' average confidence; in the middle white row, the confidence reported is the average of the peer's confidence.

Fig. 2.

The pathways of answers from pre-discussion (top row) to post-discussion (bottom row). Percentages indicate the portion of items from the category immediately above in that category, the numbers in brackets indicate the raw numbers of items, and the numbers at the bottom of each entry indicate the confidence associated with those items. In the middle, white row, confidence values show the peer's confidence. Turquoise indicates incorrect answers and yellow indicates correct answers

Broadly, only 5% of correct answers were switched to incorrect, while 28% of incorrect answers were switched to correct following discussion. Even for the items in which students were initially correct but disagreed with their partner, only 21% of answers were changed to incorrect answers after discussion. However, out of the items where students were initially incorrect and disagreed with their partner, 42% were changed to the correct answer.

Does confidence predict switching?

Differences in the amount of switching to correct or incorrect answers could be driven solely by differences in confidence, as described in our first theory mentioned earlier. For this theory to hold, answers with greater confidence must have a greater likelihood of being correct. To examine whether initial confidence is associated with initial correctness, we calculated the gamma correlation between correctness and confidence in the answer before discussion, as shown in the first column of Table 4. The average gamma correlation between initial confidence and initial correctness (mean (M) = 0.40) was greater than zero, t (160) = 8.59, p < 0.001, d  = 0.68, indicating that greater confidence was associated with being correct.

Changing from an incorrect to a correct answer, then, may be driven entirely by selecting the answer from the peer with the greater confidence during discussion, even though most of the students in our sample were not required to explicitly disclose their confidence to their partner during discussion. We examined how frequently students choose the more confident answer when peers disagree. When peers disagreed, students' final answers aligned with the more confident peer only 58% of the time. Similarly, we tested what the performance would be if peers always picked the answer of the more confident peer. If peers always chose the more confident answer during discussion, the final accuracy would be 69%, which is significantly lower than actual final accuracy (M = 72%, t (207) = 2.59, p = 0.01, d  = 0.18). While initial confidence is related to accuracy, these results show that confidence is not the only predictor of switching answers.

Does correctness predict switching beyond confidence?

Discussion may reveal information about the correctness of answers by generating new knowledge and testing the coherence of each possible answer. To test whether the correctness of an answer added predictive power beyond the confidence of the peers involved in discussion, we analyzed situations in which students disagreed with their partner. Out of the instances when partners initially disagreed, we predicted the likelihood of keeping one's answer based upon one's own confidence, the partner's confidence, and whether one's answer was initially correct. The results of a model predicting whether students keep their answers is shown in Table 5. For each increase in a point of one's own confidence, the odds of keeping one's answer increases 1.25 times (95% conf 1.13-1.38). For each decrease in a point of the partner's confidence, the odds of keeping one's answer increased 1.19 times (1.08-1.32). The beta weight for one's confidence did not differ from the beta weight of the partner's confidence, χ ² = 0.49, p  = 0.48. Finally, if one's own answer was correct, the odds of keeping one's answer increased 4.48 times (2.92-6.89). In other words, the more confident students were, the more likely they were to keep their answer; the more confident their peer was, the more likely they were to change their answer; and finally, if a student was correct, they were more likely to keep their answer.

To illustrate this relationship, we plotted the probability of keeping one's own answer as a function of the difference between one's own and their partner's confidence for initially correct and incorrect answers. As shown in Fig. 3, at every confidence level, being correct led to equal or more frequently keeping one's answer than being incorrect.

Fig. 3.

The probability of keeping one's answer in situations where one's partner initially disagreed as a function of the difference between partners' levels of confidence. Error bars indicate the standard error of the proportion and are not shown when the data are based upon a single data point

As another measure of whether discussion allows learners to test the coherence of the correct answer, we analyzed how discussion impacted confidence when partners' answers agreed. We predicted confidence in answers by the interaction of time point (i.e., pre-discussion versus post-discussion) and being initially correct for situations in which peers initially agreed on their answer. The results, displayed in Table 6, show that confidence increased from pre-discussion to post-discussion by 1.08 points and that confidence was greater for initially correct answers (than incorrect answers) by 0.78 points. As the interaction between time point and initial correctness shows, confidence increased more from pre-discussion to post-discussion when students were initially correct (as compared to initially incorrect). To illustrate this relationship, we plotted pre-confidence against post-confidence for initially correct and initially incorrect answers when peers agreed (Fig. 4). Each plotted point represents a student; the diagonal blue line indicates no change between pre-confidence and post-confidence. The graph reflects that confidence increases more from pre-discussion to post-discussion for correct answers than for incorrect answers, even when we only consider cases where peers agreed.

Fig. 4.

The relationship between pre-discussion and post-discussion confidence as a function of the accuracy of an answer when partners agreed. Each dot represents a student

If students engage in more comprehensive answer testing during discussion than before, the relationship between confidence in their answer and the accuracy of their answer should be stronger following discussion than it is before. We examined whether confidence accurately reflected correctness before and after discussion. To do so, we calculated the gamma correlation between confidence and accuracy, as is typically reported in the literature on metacognitive monitoring (e.g., Son & Metcalfe, 2000; Tullis & Fraundorf, 2017). Across all students, the resolution of metacognitive monitoring increases from pre-discussion to post-discussion ( t (139) = 2.98, p = 0.003, d = 0.24; for a breakdown of gamma calculations for each class, see Table 4). Confidence was more accurately aligned with accuracy following discussion than preceding it. The resolution between student confidence and correctness increases through discussion, suggesting that discussion offers better coherence testing than answering alone.

Discussion

To examine why peer instruction benefits student learning, we analyzed student answers and confidence before and after discussion across six psychology classes. Discussing a question with a partner improved accuracy across classes and grade levels with small to medium-sized effects. Questions of all difficulty levels benefited from peer discussion; even questions where less than half of students originally answered correctly saw improvements from discussion. Benefits across the spectrum of question difficulty align with prior research showing improvements when even very few students initially know the correct answer (Smith et al., 2009). More students switched from incorrect answers to correct answers than vice versa, leading to an improvement in accuracy following discussion. Answer switching was driven by a student's own confidence in their answer and their partner's confidence. Greater confidence in one's answer indicated a greater likelihood of keeping the answer; a partner's greater confidence increased the likelihood of changing to their answer.

Switching answers depended on more than just confidence: even when accounting for students' confidence levels, the correctness of the answer impacted switching behavior. Across several measures, our data showed that the correctness of an answer carried weight beyond confidence. For example, the correctness of the answer predicted whether students switched their initial answer during peer disagreements, even after taking the confidence of both partners into account. Further, students' confidence increased more when partners agreed on the correct answer compared to when they agreed on an incorrect answer. Finally, although confidence increased from pre-discussion to post-discussion when students changed their answers from incorrect to the correct ones, confidence decreased when students changed their answer away from the correct one. A plausible interpretation of this difference is that when students switch from a correct answer to an incorrect one, their decrease in confidence reflects the poor coherence of their final incorrect selection.

Whether peer instruction resulted in optimal switching behaviors is debatable. While accuracy improved through discussion, final accuracy was worse than if students had optimally switched their answers during discussion. If students had chosen the correct answer whenever one of the partners initially chose it, the final accuracy would have been significantly higher (M = 0.80 (SD = 0.19)) than in our data (M = 0.72 (SD = 0.24), t (207) = 6.49, p < 0.001, d = 0.45). While this might be interpreted as "process loss" (Steiner, 1972; Weldon & Bellinger, 1997), that would assume that there is sufficient information contained within the dyad to ascertain the correct answer. One individual selecting the correct answer is inadequate for this claim because they may not have a compelling justification for their answer. When we account for differences in initial confidence, students' final accuracy was better than expected. Students' final accuracy was better than that predicted from a model in which students always choose the answer of the more confident peer. This over-performance, often called "process gain", can sometimes emerge when individuals collaborate to create or generate new knowledge (Laughlin, Bonner, & Miner, 2002; Michaelsen, Watson, & Black, 1989; Sniezek & Henry, 1989; Tindale & Sheffey, 2002). Final accuracy reveals that students did not simply choose the answer of the more confident student during discussion; instead, students more thoroughly probed the coherence of answers and mental models during discussion than they could do alone.

Students' final accuracy emerges from the interaction between the pairs of students, rather than solely from individuals' sequestered knowledge prior to discussion (e.g. Wegner, Giuliano, & Hertel, 1985). Schwartz ( 1995) details four specific cognitive products that can emerge through working in dyads. Specifically, dyads force verbalization of ideas through discussion, and this verbalization facilitates generating new knowledge. Students may not create a coherent explanation of their answer until they engage in discussion with a peer. When students create a verbal explanation of their answer to discuss with a peer, they can identify knowledge gaps and construct new knowledge to fill those gaps. Prior research examining the content of peer interactions during argumentation in upper-level biology classes has shown that these kinds of co-construction happen frequently; over three quarters of statements during discussion involve an exchange of claims and reasoning to support those claims (Knight et al., 2013). Second, dyads have more information processing resources than individuals, so they can solve more complex problems. Third, dyads may foster greater motivation than individuals. Finally, dyads may stimulate the creation of new, abstract representations of knowledge, above and beyond what one would expect from the level of abstraction created by individuals. Students need to communicate with their partner; to create common ground and facilitate discourse, dyads negotiate common representations to coordinate different perspectives. The common representations bridge multiple perspectives, so they lose idiosyncratic surface features of individuals' representation. Working in pairs generates new knowledge and tests of answers that could not be predicted from individuals' performance alone.

More broadly, teachers often put students in groups so that they can learn from each other by giving and receiving help, recognizing contradictions between their own and others' perspectives, and constructing new understandings from divergent ideas (Bearison, Magzamen, & Filardo, 1986; Bossert, 1988-1989; Brown & Palincsar, 1989; Webb & Palincsar, 1996). Giving explanations to a peer may encourage explainers to clarify or reorganize information, recognize and rectify gaps in understandings, and build more elaborate interpretations of knowledge than they would have alone (Bargh & Schul, 1980; Benware & Deci, 1984; King, 1992; Yackel, Cobb, & Wood, 1991). Prompting students to explain why and how problems are solved facilitates conceptual learning more than reading the problem solutions twice without self-explanations (Chi, de Leeuw, Chiu, & LaVancher, 1994; Rittle-Johnson, 2006; Wong, Lawson, & Keeves, 2002). Self-explanations can prompt students to retrieve, integrate, and modify their knowledge with new knowledge; self-explanations can also help students identify gaps in their knowledge (Bielaczyc, Pirolli, & Brown, 1995; Chi & Bassock, 1989; Chi, Bassock, Lewis, Reimann, & Glaser, 1989; Renkl, Stark, Gruber, & Mandl, 1998; VanLehn, Jones, & Chi, 1992; Wong et al., 2002), detect and correct errors, and facilitate deeper understanding of conceptual knowledge (Aleven & Koedinger, 2002; Atkinson, Renkl, & Merrill, 2003; Chi & VanLehn, 2010; Graesser, McNamara, & VanLehn, 2005). Peer instruction, while leveraging these benefits of self-explanation, also goes beyond them by involving what might be called "other-explanation" processes - processes recruited not just when explaining a situation to oneself but to others. Mercier and Sperber ( 2019) argue that much of human reason is the result of generating explanations that will be convincing to other members of one's community, thereby compelling others to act in the way that one wants.

Conversely, students receiving explanations can fill in gaps in their own understanding, correct misconceptions, and construct new, lasting knowledge. Fellow students may be particularly effective explainers because they can better take the perspective of their peer than the teacher (Priniski & Horne, 2019; Ryskin, Benjamin, Tullis, & Brown-Schmidt, 2015; Tullis, 2018). Peers may be better able than expert teachers to explain concepts in familiar terms and direct peers' attention to the relevant features of questions that they do not understand (Brown & Palincsar, 1989; Noddings, 1985; Vedder, 1985; Vygotsky, 1981).

Peer instruction may benefit from the generation of explanations, but social influences may compound those benefits. Social interactions may help students monitor and regulate their cognition better than self-explanations alone (e.g., Jarvela et al., 2015; Kirschner, Kreijns, Phielix, & Fransen, 2015; Kreijns, Kirschner, & Vermeulen, 2013; Phielix, Prins, & Kirschner, 2010; Phielix, Prins, Kirschner, Erkens, & Jaspers, 2011). Peers may be able to judge the quality of the explanation better than the explainer. In fact, recent research suggests that peer instruction facilitates learning even more than self-explanations (Versteeg, van Blankenstein, Putter, & Steendijk, 2019).

Not only does peer instruction generate new knowledge, but it may also improve students' metacognition. Our data show that peer discussion prompted more thorough testing of the coherence of the answers. Specifically, students' confidences were better aligned with accuracy following discussion than before. Improvements in metacognitive resolution indicate that discussion provides more thorough testing of answers and ideas than does answering questions on one's own. Discussion facilitates the metacognitive processes of detecting errors and assessing the coherence of an answer.

Agreement among peers has important consequences for final behavior. For example, when peers agreed, students very rarely changed their answer (less than 3% of the time). Further, large increases in confidence occurred when students agreed (as compared to when they disagreed). Alternatively, disagreements likely engaged different discussion processes and prompted students to combine different answers. Whether students weighed their initial answer more than their partner's initial answer remains debatable. When students disagreed with their partner, they were more likely to stick with their own answer than switch; they kept their own answer 66% of the time. Even when their partner was more confident, students only switched to their partner's answer 50% of the time. The low rate of switching during disagreements suggests that students weighed their own answer more heavily than their partner's answer. In fact, across prior research, deciders typically weigh their own thoughts more than the thoughts of an advisor (Harvey, Harries, & Fischer, 2000; Yaniv & Kleinberger, 2000).

Interestingly, peers agreed more frequently than expected by chance. When students were initially correct (64% of the time), 78% of peers agreed. When students were initially incorrect (36% of the time), peers agreed 43% of the time. Pairs of students, then, agree more than expected by a random distribution of answers throughout the classroom. These data suggest that students group themselves into pairs based upon likelihood of sharing the same answer. Further, these data suggest that student understanding is not randomly distributed throughout the physical space of the classroom. Across all classes, students were instructed to work with a neighbor to discuss their answer. Given that neighbors agreed more than predicted by chance, students seem to tend to sit near and pair with peers that share their same levels of understanding. Our results from peer instruction reveal that students physically locate themselves near students of similar abilities. Peer instruction could potentially benefit from randomly pairing students together (i.e. not with a physically close neighbor) to generate the most disagreements and generative activity during discussion.

Learning through peer instruction may involve deep processing as peers actively challenge each other, and this deep processing may effectively support long-term retention. Future research can examine the persistence of gains in accuracy from peer instruction. For example, whether errors that are corrected during peer instruction stay corrected on later retests of the material remains an open question. High and low-confidence errors that are corrected during peer instruction may result in different long-term retention of the correct answer; more specifically, the hypercorrection effect suggests that errors committed with high confidence are more likely to be corrected on subsequent tests than errors with low confidence (e.g., Butler, Fazio, & Marsh, 2011; Butterfield & Metcalfe, 2001; Metcalfe, 2017). Whether hypercorrection holds for corrections from classmates during peer instruction (rather than from an absolute authority) could be examined in the future.

The influence of partner interaction on accuracy may depend upon the domain and kind of question posed to learners. For simple factual or perceptual questions, partner interaction may not consistently benefit learning. More specifically, partner interaction may amplify and bolster wrong answers when factual or perceptual questions lead most students to answer incorrectly (Koriat, 2015). However, for more "intellective tasks," interactions and arguments between partners can produce gains in knowledge (Trouche et al., 2014). For example, groups typically outperform individuals for reasoning tasks (Laughlin, 2011; Moshman & Geil, 1998), math problems (Laughlin & Ellis, 1986), and logic problems (Doise & Mugny, 1984; Perret-Clermont, 1980). Peer instruction questions that allow for student argumentation and reasoning, therefore, may have the best benefits in student learning.

The underlying benefits of peer instruction extend beyond the improvements in accuracy seen from pre-discussion to post-discussion. Peer instruction prompts students to retrieve information from long-term memory, and these practice tests improve long-term retention of information (Roediger III & Karpicke, 2006; Tullis, Fiechter, & Benjamin, 2018). Further, feedback provided by instructors following peer instruction may guide students to improve their performance and correct misconceptions, which should benefit student learning (Bangert-Drowns, Kulik, & Kulik, 1991; Thurlings, Vermeulen, Bastiaens, & Stijnen, 2013). Learners who engage in peer discussion can use their new knowledge to solve new, but similar problems on their own (Smith et al., 2009). Generating new knowledge and revealing gaps in knowledge through peer instruction, then, effectively supports students' ability to solve novel problems. Peer instruction can be an effective tool to generate new knowledge through discussion between peers and improve student understanding and metacognition.

Acknowledgements

Not applicable.

Authors' contributions

JGT collected some data, analyzed the data, and wrote the first draft of the paper. RLG collected some data, contributed significantly to the framing of the paper, and edited the paper. The authors read and approved the final manuscript.

Authors' information

JGT: Assistant Professor in Educational Psychology at University of Arizona. RLG: Chancellor's Professor in Psychology at Indiana University.

Funding

No funding supported this manuscript.

Availability of data and materials

As described below, data and materials are available on the OpenScienceFramework: https://mfr.osf.io/render?url=https://osf.io/5qc46/?action=download%26mode=render.

Ethics approval and consent to participate

The ethics approval was waived by the Indiana University Institutional Review Board (IRB) and the University of Arizona IRB, given that these data are collected as part of normal educational settings and processes.

Consent for publication

No individual data are presented in the manuscript.

Competing interests

The authors declare that they have no competing interests.

Footnotes

Publisher's Note

References

1. Baayen, R. H. (2008). Analyzing linguistic data: A practical introduction to statistics. Cambridge: Cambridge University Press.

2. Bearison DJ, Magzamen S, Filardo EK. Sociocognitive conflict and cognitive growth in young children. Merrill-Palmer Quarterly. 1986;32(1):51-72. [Google Scholar]

3. Bossert ST. Cooperative activities in the classroom. Review of Research in Education. 1988;15:225-252. [Google Scholar]

4. Brown AL, Palincsar AS. Guided, cooperative learning and individual knowledge acquisition. In: Resnick LB, editor. Knowing, learning, and instruction: essays in honor of Robert Glaser. Hillsdale: Erlbaum; 1989. pp. 393-451. [Google Scholar]

5. Chi M, VanLehn KA. Meta-cognitive strategy instruction in intelligent tutoring systems: How, when and why. Journal of Educational Technology and Society. 2010;13:25-39. [Google Scholar]

6. Chi MTH, Bassock M. Learning from examples via self-explanations. In: Resnick LB, editor. Knowing, learning, and instruction: Essays in honor of Robert Glaser. Hillsdale: Erlbaum; 1989. pp. 251-282. [Google Scholar]

7. Chi MTH, de Leeuw N, Chiu MH, LaVancher C. Eliciting self-explanations improves understanding. Cognitive Science. 1994;18:439-477. [Google Scholar]

8. Cummings K, Roberts S. A study of peer instruction methods with school physics students. In: Henderson C, Sabella M, Hsu L, editors. Physics education research conference. College Park: American Institute of Physics; 2008. pp. 103-106. [Google Scholar]

9. Duncan D. Clickers in the classroom: How to enhance science teaching using classroom response systems. San Francisco: Pearson/Addison-Wesley; 2005. [Google Scholar]

10. Finley JR, Tullis JG, Benjamin AS. Metacognitive control of learning and remembering. In: Khine MS, Saleh IM, editors. New science of learning: Cognition, computers and collaborators in education. New York: Springer Science & Business Media, LLC; 2010. [Google Scholar]

11. Laughlin PR. Group problem solving. Princeton: Princeton University Press; 2011. [Google Scholar]

12. Mazur E. Peer instruction: A user's manual. Upper Saddle River: Prentice Hall; 1997. [Google Scholar]

13. Mercier H, Sperber D. The enigma of reason. Cambridge: Harvard University Press; 2019. [Google Scholar]

14. Morgan JT, Wakefield C. Who benefits from peer conversation? Examining correlations of clicker question correctness and course performance. Journal of College Science Teaching. 2012;41(5):51-56. [Google Scholar]

15. Newbury P, Heiner C. Ready, set, react! getting the most out of peer instruction using clickers. 2012. [Google Scholar]

16. Noddings N. Small groups as a setting for research on mathematical problem solving. In: Silver EA, editor. Teaching and learning mathematical problem solving. Hillsdale: Erlbaum; 1985. pp. 345-360. [Google Scholar]

17. Perret-Clermont AN. Social Interaction and Cognitive Development in Children. London: Academic Press; 1980. [Google Scholar]

18. Pollock SJ, Chasteen SV, Dubson M, Perkins KK. The use of concept tests and peer instruction in upper-division physics. In: Sabella M, Singh C, Rebello S, editors. AIP conference proceedings. New York: AIP Press; 2010. p. 261. [Google Scholar]

19. Porter L, Bailey-Lee C, Simon B. SIGCSE '13: Proceedings of the 44th ACM technical symposium on computer science education. New York: ACM Press; 2013. Halving fail rates using peer instruction: A study of four computer science courses; pp. 177-182. [Google Scholar]

20. Priniski JH, Horne Z. Crowdsourcing effective educational interventions. In: Goel AK, Seifert C, Freska C, editors. Proceedings of the 41st annual conference of the cognitive science society. Austin: Cognitive Science Society; 2019. [Google Scholar]

21. Simon B, Kohanfars M, Lee J, Tamayo K, Cutts Q. Proceedings of the 41st SIGCSE technical symposium on computer science education. 2010. Experience report: peer instruction in introductory computing. [Google Scholar]

22. Steiner ID. Group processes and productivity. New York: Academic Press; 1972. [Google Scholar]

23. Turpen, C., & Finkelstein, N. (2007). Understanding how physics faculty use peer instruction. In L. Hsu, C. Henderson, & L. McCullough (Eds.), Physics education research conference, (pp. 204-209). College Park: American Institute of Physics.

24. Vedder P. Cooperative learning: A study on processes and effects of cooperation between primary school children. Westerhaven: Rijkuniversiteit Groningen; 1985. [Google Scholar]

25. Vygotsky LS. The genesis of higher mental functioning. In: Wertsch JV, editor. The concept of activity in Soviet psychology. Armonk: Sharpe; 1981. pp. 144-188. [Google Scholar]

26. Webb NM, Palincsar AS. Group processes in the classroom. In: Berliner DC, Calfee RC, editors. Handbook of educational psychology. New York: Macmillan Library Reference USA: London: Prentice Hall International; 1996. pp. 841-873. [Google Scholar]

27. Wegner DM, Giuliano T, Hertel P. Cognitive interdependence in close relationships. In: Ickes WJ, editor. Compatible and incompatible relationships. New York: Springer-Verlag; 1985. pp. 253-276. [Google Scholar]

28. Wieman C, Perkins K, Gilbert S, Benay F, Kennedy S, Semsar K, et al. Clicker resource guide: An instructor's guide to the effective use of personalresponse systems (clickers) in teaching. Vancouver: University of British Columbia; 2009. [Google Scholar]

Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

As described below, data and materials are available on the OpenScienceFramework: https://mfr.osf.io/render?url=https://osf.io/5qc46/?action=download%26mode=render.

Articles from Cognitive Research: Principles and Implications are provided here courtesy of Springer

# data[].attributes.attachment_link.title
Why does peer instruction benefit student learning?

# data[].attributes.attachment_link.description
In peer instruction, instructors pose a challenging question to students, students answer the question individually, students work with a partner in the class to discuss their answers, and finally students answer the question again. A large body of ...

# data[].attributes.body
For my higher-level thinking strategy, I chose Problem-Based Learning (PBL). PBL can be utilized on many different educational platforms and is a style of learning that requires communication, problem-solving and critical thinking skills. This style of learning can be used in any discipline of  nursing especially in the emergency department. Problem-solving and critical thinking are essential during emergencies, as interventions must be continuously assessed for their effectiveness. Simulations serve as an excellent method to further develop critical thinking skills. Utilizing high-fidelity mannequins, facilitators can modify vital signs and responses to various treatments, enabling participants to engage in communication and collaborative problem-solving. Conducting a debriefing session following a simulation exercise is beneficial for fostering critical thinking skills. Asking questions such as "What is another intervention that could be done if the blood pressure did not respond to the initial bolus of fluids?" or "What does it mean if you are unable to get a number to record for a rectal temperature?" encourages deeper analysis. Education is a continuous journey, and multiple methodologies can lead to achieving a conclusion. As the field of emergency medicine progresses, integrating innovative educational strategies such as PBL ensures that clinicians are adequately prepared to deliver the highest standard of care in the most demanding situations.

# data[].attributes.body
One effective teaching strategy for promoting higher-order thinking in nursing education is Simulation-Based Learning (SBL). This approach uses realistic, controlled scenarios (either with mannequins or virtual simulations) where students can assess, make decisions, and act in a way that mirrors real-life clinical situations. SBL promotes critical thinking, problem-solving, and decision-making by challenging students to apply theoretical knowledge in a practical setting. For example, students might need to make a quick decision in high-pressure scenarios, such as managing a deteriorating patient during a code situation. The debriefing session after each simulation encourages students to reflect on their choices, analyze their actions, and improve their clinical judgment.

The rationale behind SBL is that it provides a safe environment for students to make mistakes and learn from them without putting real patients at risk. This hands-on, immersive experience pushes students beyond basic memorization into higher-order skills, such as synthesizing information and evaluating interventions. Additionally, it can be adapted for both novice and advanced learners and provides opportunities for interprofessional collaboration. Simulation is an invaluable tool for reinforcing critical thinking and preparing students for real-world clinical challenges.

# data[].attributes.attachment_link.title
Simulation in Clinical Nursing Education

# data[].attributes.attachment_link.description
Simulation constitutes a teaching method and a strategy for learning and understanding theoretical knowledge and skills in the nursing and medical field. To review and present modern data related to this issue. Literature review of data related to…

# data[].attributes.body
I chose to discuss peer-led debriefs after simulations because they’ve made a noticeable difference in how we reflect and learn as a team. When debriefs are led by peers, the environment tends to feel more relaxed and open, which encourages honest feedback and deeper discussion. It’s easier to talk through what went well and what didn’t without fear of judgment. These sessions help build confidence, communication, and critical thinking in a way that feels supportive and collaborative. He et al. (2024) found that peer-led debriefing was just as effective as instructor-led sessions in improving performance and learning outcomes in simulation training, which supports what I’ve seen in practice.

# data[].attributes.attachment_link.title
Peer-led versus instructor-led structured debriefing in high-fidelity simulation: a mixed-methods study on teaching effectiveness - BMC Medical Education

# data[].attributes.attachment_link.description
Background Debriefing is the essential element of simulation teaching. Peer-led structured debriefing simulations could be a suitable approach because of the peers’ similarity in age and experience to the students. The purpose of this study was to compare the teaching effectiveness of peer-led debriefing versus instructor-led debriefing in high-fidelity simulation scenarios. Methods The study used a mixed-method approach, integrating quasi-experimental and qualitative components. A total of 88 third-year nursing students were randomly distributed into the instructor-led or peer-led group, with equal sample sizes in both cohorts. The study compared knowledge acquisition, simulation performance, student satisfaction and self-confidence in learning, and debriefing experience between the two groups. In addition, interviews were conducted with students in the peer-led group after the course. Results The scores of students’ simulation performance scale were higher in the peer-led group than in the instructor-led group, and both groups made significant gains in knowledge. The peer-led group and instructor-led group demonstrated similar performance in terms of knowledge, simulated performance, reporting experience, student satisfaction, and learning confidence. The semi-structured interview results indicated that students in the peer-led group expressed approval of peer facilitators. Conclusions Our study demonstrated that students in the peer-led group showed better performance in the simulation, and both groups demonstrated improved knowledge. Thus, with the premise of peers receiving training, the peer-led simulation teaching method can be regarded as a supplementary strategy for simulation teaching to enrich the form of simulation teaching and improve the effectiveness of simulation teaching.

# data[].attributes.body
What if Scenarios?

One teaching strategy that I have found helpful in the past when working with students or precepting nurses is the “What if?” scenario. This scenario is an inquiry-based learning strategy where you propose a hypothetical situation, often counter to or a significant alteration of a known problem. Students then have to explore the potential consequences of this change. For example, someone might ask what you would do if your patient's neurological assessment were not regular. What if the patient's blood pressure was too low? The latter scenario would require an understanding of why a patient's blood pressure might be low and what potential treatments are available for this condition. This would require an understanding of different patient disease processes, how medication can affect blood pressure, whether the patient is experiencing bleeding, and whether the patient needs fluids or medication. This involves higher-level thinking because a student must first deeply understand the existing situation and concept before beginning to synthesize the change. They must break down the components of the original scenario to determine how this event would alter the scenario. They must evaluate the potential likelihood of different outcomes. They need to make judgments about which consequences are most impactful and be able to justify their reasoning. This also requires higher-level thinking, as the student must understand whether any pre-existing algorithms or protocols can assist in their reasoning. They must also see if these protocols would benefit the patient's current situation. Often, what-if scenarios can push students to consider situations from different perspectives. This requires them to step outside their viewpoint and consider the motivations and constraints of the new scenario. I like to use these assessments with students as they foster intellectual curiosity and encourage students to see concepts not as static, but as part of a dynamic system.

# data[].attributes.attachment_caption
Nursing Case Study for Pediatric Asthma | NRSNG Nursing Course

# data[].attributes.body
Case Study

For my higher-level learning strategy, I chose case studies. I have enjoyed the exercise of case studies both as a nursing student and now as an RN, for their engaging nature. Case studies can be beneficial, as they allow nursing students to take information they have learned and apply it to real-world or realistic situations or scenarios. Students are challenged to not only to recall information, but to utilize and engage with the material to solve the problem(s) of the case. They require reflection of choices made by the learner, which aligns with metacognition, which is thinking about thinking. Additionally, students are able to solve problems without any harm to patients. Another benefit is that there are limited barriers to the utilization of case studies, as they are accessible to in-person and virtual learning, and are not prohibitively expensive. Attached to this post, I have included an example of an online virtual case study. In this example, audio explaining the scenario is given, followed by questions to prompt learners. Students are able to click through the different stages of the case study, following the development of the patient’s condition. As educators, we can utilize this format in the classroom to guide students towards set points in the study, encouraging students to reach those points through independent thinking and class discourse. When paired with a safe learning environment, case studies can promote retention and even future application of knowledge in future real-life situations.

# data[].attributes.attachment_link.title
Nursing Case Study for Pediatric Asthma | NRSNG Nursing Course

# data[].attributes.attachment_link.description
Anthony is a 6-yr-old male patient brought to the pediatric ER with a history of asthma since he came home from the NICU as an infant. He lives with his parents, Bob and Josh, who adopted him after fostering him from age 4 months. They have tried the usual nebulizer treatments but Anthony is not […]

# data[].attributes.body
Higher level thinking requires the building from basic cognition into complex thinking processes. It goes beyond knowledge of material and ventures into applying said material broadly, even using the baseline material to create new ways of thinking. One teaching strategy that helps to promote this advanced thinking is that of developing a professional identity through journaling. As an instructor of nursing students in the classroom setting, when tests would be graded, I would offer an incentive for students to earn a percentage of points back by reflecting on questions they got wrong. To properly reflect, the students would have to address the questions they got wrong by writing a brief 3-5 sentence summary including what caused them to choose the wrong answer, what the actual correct answer is based on their research, and how it now makes sense to them. From there, I would offer that for every question addressed, 1 point would be added back to the student’s grade. Using this strategy, students would feel they have a second chance to improve their grade (which is what most nursing students are mainly concerned about) while also improving their confidence and knowledge on a tricky topic for them. What do you think?

# data[].attributes.body
Higher level thinking strategies- Jigsawing

For this assignment, I found many of the learning and teaching strategies to be quite interesting, but for this assignment I chose using collaborative or cooperative learning. Collaborative learning is student centered and is defined as students organizing a faculty-led assignment, whereas cooperative learning is more faculty centered (Billings & Halstead, 2024). Some examples of collaborative or cooperative learning include stump your partner, fishbowl debate, think-pair-share, graffiti wall and jigsawing. After reading about all these examples, I was most fascinated with jigsawing, which is a technique in which classroom activities are organized in a way that students depend on each other to be successful (Billings & Halstead). In jigsawing, students are placed into groups where they need to solve an aspect of an assignment and then present to the class. Once every group is finished, they will collaborate to synthesize results (Billings & Halstead). Implementing this teaching strategy involves breaking students into “home groups” consisting of three to give students and then assigning an expert in each group. The “expert groups” can consist of three-ten members, and there should be time designated for them to become experts in their topic to then go back to their “home units” to share what they learned. Applying this type of teaching strategy when teaching about a code or emergency situation could be very beneficial. When I first read about this strategy, it strikes me as what real-life nursing can look like during a code or an emergency, each team member is working on their task at hand and coming together to synthesize their collaborative efforts.

This teaching strategy promotes higher level thinking as it is active and reflective learning and encourages teamwork. It helps build comprehension, improves communication skills, and problem-solving skills (Billings & Halstead, 2024). Jigsawing also promotes self-efficacy and confidence as students are required to problem solve at a smaller level, to educate and synthesize on a larger scale. The development of these skills helps the student with higher level learning and are crucial in future nursing practice.

Billings, D. M., & Halstead, J. A. (2024). Teaching in nursing: A guide for faculty. Elsevier.

# data[].attributes.body
Teaching Strategy – Socratic Teaching Strategy/Socratic Questioning

The Socratic teaching strategy is a method of engaging students through open-ended questions that promote deeper thinking and reflection. This strategy puts an emphasis on dialogue and critical thinking. Exploration of complex ideas is encouraged by challenging student assumptions and encouraging students to consider the possibilities that may not have aligned with their original assumptions.

Rationale:

Critical thinking is the foundation of nursing practice, and the Socratic teaching strategy would encourage student’s analytical thinking, specifically regarding what is being taught, whether clinically or in the classroom. Nurse educators can prompt students, through open-ended questions, to consider different perspectives that could challenge their own assumptions.  This, in turn, would encourage students to self-reflect and assess their own beliefs and values. Socratic questioning also encourages students to articulate how they are thinking through and analyzing situations. Clinical reasoning skills are enhanced, and collaboration skills are developed. Students are actively engaged, leading to higher retention and increased understanding of complex processes. I see this teaching strategy working well when discussing patients, either through case studies or in the clinical setting through clinical debriefing, who have different socioeconomic statuses or cultural backgrounds than the student. Pushing students to challenge their own assumptions or beliefs would position nurses to provide holistic patient-centered care in an increasingly diverse population.

# data[].attributes.attachment_link.readable_text
As a nursing instructor, using effective questioning techniques can significantly enhance students' clinical judgment skills. Thoughtful and strategic questioning encourages critical thinking, reflection, and the application of theoretical knowledge to real-world patient care scenarios. Here are some strategies to use questioning effectively in nursing education to improve students' clinical judgment:

1. Open-Ended Questions: Encourage students to think deeply and critically by asking open-ended questions. These questions do not have a single right answer and require students to explore different perspectives and possibilities. For example, instead of asking, "What is the correct nursing intervention for this patient?" ask, "How would you approach this patient's care, considering their current condition and medical history?"

2. Case-Based Questions: Present students with real or hypothetical patient cases and ask them to analyze the situation and propose appropriate nursing interventions. Discuss the rationale behind their choices and encourage them to consider potential outcomes and complications.

3. Socratic Questioning: Use the Socratic method to guide students through a series of thought-provoking questions that lead them to arrive at conclusions independently. This approach helps students develop their critical thinking abilities and enhances their clinical judgment skills.

4. Why-How-What Approach: When discussing patient care plans or clinical decisions, follow the "why-how-what" approach. Start by asking why a specific intervention is chosen, then explore how it will be implemented, and finally, discuss what outcomes are expected. This method encourages students to consider the rationale behind their actions and the impact on patient care.

5. Predicting and Evaluating Outcomes: Encourage students to predict potential patient outcomes based on their proposed interventions. Ask follow-up questions to explore the possible positive and negative consequences of their decisions. This exercise helps students connect their actions to patient well-being and safety.

6. Reflective Questions: After clinical experiences, simulations, or case studies, use reflective questions to help students assess their performance and clinical judgment. Ask them to identify what went well, what challenges they faced, and how they could improve their decision-making in similar situations.

7. Ethical Dilemmas: Present students with ethical dilemmas commonly encountered in nursing practice. Engage them in discussions about how their clinical judgment and decision-making process may be influenced by ethical considerations.

8. Group Discussions and Peer Learning: Encourage group discussions where students can share their perspectives and learn from each other. Peer learning fosters collaboration and exposes students to diverse viewpoints, enriching their clinical judgment abilities.

9. Real-Time Decision-Making: During clinical rotations, challenge students to think on their feet by asking questions about patient care in real-time. This exercise simulates the fast-paced nature of nursing practice and helps students develop quick and effective clinical judgment.

10. Feedback and Follow-up: Provide constructive feedback on students' responses to questions and track their progress over time. Follow up on previous discussions to reinforce learning and allow students to demonstrate how they have integrated feedback into their clinical judgment process.

Examples of Questions you can Ask to Help Students with Clinical Judgment

1. "How would you prioritize the nursing interventions for this patient, considering their current condition and medical history?"

2. "What are some potential factors that could be contributing to this patient's symptoms, and how would you go about further assessing them?"

3. "Describe your thought process when determining whether to escalate care for a patient who is showing signs of deterioration."

4. "In this patient scenario, what are some alternative approaches you could consider for pain management, and how would you decide which one to implement?"

5. "Imagine you encounter a patient whose cultural beliefs differ significantly from your own. How would you approach providing patient-centered care while respecting their cultural preferences?"

6. "When dealing with a complex wound, how do you decide on the most appropriate dressing and wound care regimen for the patient?"

7. "Describe the steps you would take to ensure medication safety when administering high-risk medications to multiple patients simultaneously."

8. "In a situation where a patient's values and preferences conflict with the treatment plan, how would you handle the ethical dilemma?"

9. "What information would you seek from the patient and their family to better understand their psychosocial needs and support systems?"

10. "Discuss your approach to gathering evidence-based practice resources when facing a new and unfamiliar patient condition."

11. "How would you adapt your communication style when providing education to a patient with limited health literacy?"

12. "When preparing for a patient handoff, what critical information would you include to ensure continuity of care?"

13. "In a rapidly changing clinical situation, how do you maintain situational awareness and make swift but informed decisions?"

14. "When encountering a potential medication error, what immediate actions would you take, and how would you prevent similar incidents in the future?"

15. "Explain how you would assess the effectiveness of a patient's treatment plan and modify it based on their progress."

16. If you implement this specific nursing intervention for the patient, what are the potential short-term and long-term outcomes you would expect to see?"

17. "What are some of the potential complications that could arise from the medication regimen you've suggested, and how would you monitor the patient for these adverse effects?"

18. "Based on the patient's current condition and response to treatment, what do you anticipate will be the next steps in their care plan?"

19. "Imagine the patient's family has concerns about the proposed surgical procedure. How would you address their fears and help them understand the potential benefits and risks involved?"

20. "Considering the patient's comorbidities and medications, what potential drug interactions should you be vigilant about when adding a new medication to their regimen?"

21. "If you choose not to intervene in this particular patient case, what are the potential implications for the patient's health and well-being?"

22. "You've administered a potent pain medication to a post-operative patient. How would you evaluate its effectiveness, and what alternative pain management strategies might you consider if the patient's pain persists?"

23. "The patient is refusing a crucial diagnostic test. What are the possible outcomes of this decision, and how would you approach this situation to ensure the patient receives appropriate care?"

24. "Considering the patient's age and underlying health conditions, how might their recovery differ from a younger patient with a similar diagnosis?"

25. "The patient's lab results show abnormalities in their liver function. What implications might this have for their medication management and overall treatment plan?"

26. "You suspect the patient is experiencing a medication side effect not previously documented. How would you further investigate this, and what steps would you take to prevent further complications?"

27. "You're planning to discharge the patient with a chronic condition. How would you assess their readiness for self-care management, and what could happen if they struggle to adhere to their treatment plan?"

28. "If you decide to use an alternative communication approach with a non-responsive patient, how would you evaluate the effectiveness of this intervention?"

29. "The patient's vital signs indicate a subtle decline in their condition. What actions would you take immediately, and what outcomes are you hoping to achieve by intervening promptly?"

30. "You suspect the patient may be experiencing a psychological response to their diagnosis. How might addressing their emotional well-being impact their overall recovery and treatment outcomes?"

Remember that the goal of questioning in nursing education is not just to test students' knowledge but to guide them in developing their clinical judgment skills. Creating a supportive and inquisitive learning environment empowers students to think critically and make sound decisions that positively impact patient outcomes.

References

Craig, J. L., & Page, G. (1981). The questioning skills of nursing instructors. Journal of Nursing Education, 20(5), 18-23.

Merisier, S., Larue, C., & Boyer, L. (2018). How does questioning influence nursing students' clinical reasoning in problem-based learning? A scoping review. Nurse education today, 65, 108-115.

Nicholl, H. M., & Tracey, C. A. (2007). Questioning: a tool in the nurse educator's kit. Nurse education in practice, 7(5), 285-292.

Saeed, T., Khan, S., Ahmed, A., Gul, R., Cassum, S. H., & Parpio, Y. (2012). Development of students' critical thinking: the educators' ability to use questioning skills in the baccalaureate programmes in nursing in Pakistan. JPMA. The Journal of the Pakistan Medical Association, 62(3), 200.

# data[].attributes.attachment_link.description
As a nursing instructor, using effective questioning techniques can significantly enhance students' clinical judgment skills. Thoughtful and strategic questioning encourages critical thinking, reflection, and the application of theoretical knowledge to real-world patient care scenarios. Here are some strategies to use questioning effectively in nursing education to improve students' clinical judgment: Open-Ended Questions: Encourage students to...

# data[].attributes.body
The teaching strategy I chose is problem based learning. Problem based learning is a teaching approach where students learn through solving “real world” problems. In the nursing profession, problem based learning is used to encourage critical thinking, communication, teamwork skills, etc.  this promotes higher level thinking because it allows for problem solving and collaboration. As a previous nursing student and even now as a bedside nurse, one of my favorite things to do is be apart of our simulations. The patient population on my unit is very higher acuity and we tend to have a lot of codes/rapids, so one practice we do frequently are code simulations with the entire interdisciplinary team and it helps staff tremendously. As we know, some situations don’t always happen as we expect but having baseline knowledge of how to act in a situation is extremely beneficial. As a future nurse educator, my goal is to incorporate simulations into education for new nurses

# data[].attributes.body
One of the best ways of learning for children is to do so through play. This is commonly accepted  by most elementary educators and children not only build knowledge, but social skills as well. What is not usually recognized, though, is that this method of learning does not stop at childhood. Learning through play continues well into adulthood, and the role of Gamification in learning is well documented by researchers who seek to find innovative and creative methods of building knowledge.  I chose Gamification as my teaching strategy because I have seen it work beautifully as a health educator.  Creating scavenger hunts across campus, using electronic educational game platforms such as Kahoot, Blooket and Quizlet, revamping simple but well-known games like bingo and crossword puzzles - all of these are fantastic ways to engage students, maintain interest, and encourage active learning.  The challenges within games promote creative problem solving skills as well as reinforcing important information and concepts. For example, a crossword puzzle that includes commonly confused medication names not only helps the student remember what they are / how they are used, but reinforces the spelling of the drugs which is extremely important for patient safety. Games like “2 truths and a lie” would allow students to each choose a medical condition, present it to the class,  and challenge fellow students to pick out factual and false information about their topic. There are several ways for  educators to impart lessons through Gamification or “Eduplay,”  most will involve creating situations in which students gain new information, are challenged to recall and apply previously learned facts, or solve problems. One such game could be a “choose your own adventure,” simulated,  virtual-reality style game in which students follow a patient through an illness, use clinical judgement to select  treatments and care, and the story line changes based on the student’s choices. Regarding the games themselves, students can gain new information within the game, students can develop skills through the game based on interaction with others, or students can apply acquired knowledge and skills beyond the game. All three, either alone or together, create an extremely effective means of building collaboration, communication and critical thinking skills.  Higher level thinking is achieved through metacognition; when students are tasked with creating their own games as an assignment to present to the class, they must first reflect on their own thoughts and actions when initially playing the games. They are able to improve their own knowledge by researching creating  new forms of eduplay. As a fun bonus, please feel free to play a quick game that I created for this assignment! Happy learning! https://www.educaplay.com/learning-resources/24154183-pharmacology_puzzle_challenge.html

# data[].attributes.body
Leveraging the Socratic Method to Promote Higher-Level Thinking in Nursing Education

One teaching strategy that has significantly shaped my approach to clinical education is the Socratic Method—a form of inquiry-based instruction that fosters higher-order cognitive engagement through disciplined questioning. Rooted in classical philosophy, this strategy involves posing purposeful, open-ended questions to guide learners in articulating their reasoning, examining assumptions, and refining their understanding of complex concepts.

While I know the Socratic Method of inquiry can be controversial—sometimes perceived as intimidating or overly confrontational if not done thoughtfully—it can be incredibly effective when used in a psychologically safe environment. In nursing education, particularly in clinical or simulation-based settings, this method challenges learners to go beyond rote memorization and engage in deeper reflection, application, and synthesis of knowledge.

For example, instead of asking, “What medication would you administer for hypotension?” I might ask, “What physiological mechanisms might be contributing to this patient’s hypotension, and how do they inform your treatment priorities?” This approach taps into critical thinking domains—analyzing, evaluating, and applying knowledge—skills essential for developing sound clinical judgment.

The Socratic Method aligns closely with Bloom’s Taxonomy by encouraging learners to move beyond remembering and understanding toward analysis, evaluation, and creation. It also complements Benner’s “From Novice to Expert” framework by fostering reflective practice and encouraging progressive clinical reasoning. When facilitated with empathy and respect, this method nurtures intellectual curiosity, diagnostic agility, and professional confidence.

In my experience, learners often report that this method helps them better understand why they make certain decisions, not just what to do—a distinction that often leads to more autonomous and safe nursing practice.

# data[].attributes.attachment_link.title
Socratic Questions Students Must Be Asked Each Clinical to Think More Like a Nurse - KeithRN

# data[].attributes.attachment_link.description
Though Socrates, an ancient Greek philosopher lived over 2500 years ago, his unique style of questions that deepen and analyze thinking can be adapted to strengthen the thinking of nursing students. Learn how to practically this powerful pedagogy in your class or clinical settings!

# data[].attributes.body
Clinical Reasoning Example for Higher Level Thinking in nursing students and new graduate RNs. Anecdotal support through personal experiences as a preceptor, clinical instructor.

# data[].attributes.body
This video discusses teaching strategies that implore the learner to become the teacher, highlighting the Protégé Effect and the rubber duck method.

# data[].attributes.body
The unfolding case study is a teaching method I find genuinely interesting. Instead of presenting the entire patient story at once, the instructor reveals it gradually, making the learning process more engaging. At first, students receive only part of the picture. They receive information such as the chief complaint and vital signs. Starting them off with minimal information encourages them to decide what to assess, prioritize, and anticipate. As new details are revealed, such as changes in the patient’s mental status, lab results, or new-onset symptoms, students have the chance to reassess and adjust their plans. By the end, they have followed the patient’s journey in a way that reflects what a real clinical situation would feel like. This takes the lesson to a higher level because students experience what it is like to face a rapidly changing patient scenario. Rather than having to make critical clinical decisions with minimal prep time, they are given room to think through their actions, understand why they are taking them, and recognize the factors influencing them.

This approach promotes higher-level thinking by highlighting the value of partial information, which prevents students from relying solely on memorized answers. Instead, each new detail prompts them to analyze what has changed, reassess their initial strategy, and integrate this new understanding with what they already know. The dynamic process helps them work through an ever-changing scenario and moves them beyond simple recall into higher-level thinking, where they learn to connect ideas and make decisions even in the face of uncertainty. The method realistically reflects how nurses think in practice, where they must adapt continuously as circumstances change.

If you’re interested in learning more, the National League for Nursing provides free resources on unfolding case studies. Visit their website at https://www.nln.org/education/teaching-resources/professional-development-programsteaching-resourcesace-all/how-to-use-an-unfolding-case-da0fb15c-7836-6c70-9642-ff00005f0421

I’d like to hear your thoughts: Do you think learners benefit more from cases that unfold gradually, or is it better to start with simpler, one-step scenarios?