Medical Problem-based Learning Research Articles

Revitalizing Pedagogy in a Medical Problem-Based Learning (PBL) Curriculum

The Medical Programme at Linköping University, committed to Problem-Based Learning (PBL) and interprofessional education, confronted the necessity for pedagogical revitalization due to an upsurge in student numbers, alterations in national physician licensing criteria, and an organizational framework shift. In response to these challenges, stakeholders conducted a comprehensive systematic self-assessment to navigate a course toward a sustainable and contemporary pedagogical transformation. The methodology employed in this assessment involved a systematic examination of scientific pedagogical literature, policy documents, educational materials, and schedules. Additionally, valuable insights were gathered through teacher and student surveys. Key findings underscore the importance of a balanced approach that grants students more time for self-study and reflection. Enhancing tools and methodologies for constructive alignment is crucial to achieve equilibrium in both theoretical and practical training settings. Moreover, establishing seamless collaborations between the university and teaching hospitals is deemed essential for faculty development and the long-term competence within both organizations. The self-assessment underscored the critical importance of continuous evaluation in medical educational settings. The approach not only ensures the ongoing relevance of the curricula but also cultivates an environment conducive to student-centred teaching and learning. This, in turn, prepares students for lifelong learning and the diverse challenges in their future medical profession.

The quality of group interactions in medical problem–based learning in China: the roles of intercultural sensitivity and group ethnic composition

BackgroundChinese universities are increasingly recruiting foreign students, and problem-based learning (PBL) is an effective approach to integrating those students. This study focuses on the role of intercultural sensitivity and group ethnic composition on the quality of group interaction in medical problem-based learning in China.MethodsThis paper reports an investigation of the differences in three types of group interaction (exploratory questions, cumulative reasoning, and handling conflict) among 139 s-year medical undergraduates from two backgrounds (Chinese and foreign) in a PBL setting. The roles of intercultural sensitivity, group ethnic composition, and students’ personal characteristics including age, gender and ethnicity on students’ perceptions of the three types of interaction were quantitatively analyzed. A 35-item questionnaire and demographic survey were administered to second year medical undergraduates.ResultsThe results indicated that group ethnic composition was a significant negative predictor while intercultural sensitivity was a strong positive predictor of group interactions involving exploratory questions and cumulative reasoning. In addition, group heterogeneity in terms of age and ethnicity were significant predictors of group interaction.ConclusionsThe findings of this study provide insights for strategically designing effective multiethnic group learning environments that encourage interaction and collaboration.

Interactive Knowledge Construction in Medical Problem-Based Learning: A Corpus-Based Study

Introduction: Due to methodological limitations, process-oriented studies have analyzed a group or fragments of problem-based learning (PBL) tutorial talk. Studies that examined several PBL tutorial talk and profile talk data into linguistic categories within a mixed methods analysis are scarce. The study aims to describe the knowledge construction processes of graduate entry medical students at Derby medical school PBL hybrid curriculum in the United Kingdom.

Interactive Conversational Words as Markers of Knowledge-Negotiation in Medical Problem-Based Learning Transcripts: A Corpus-Based Study

Background: The study aims to provide a more global understanding of the knowledge-negotiation interactions occurring in problem-based learning tutorials by analysing interactive conversational words (ICWs) as structural markers of students’ interactional boundaries. Methods: We used Wmatrix 3 software to extract frequent ICWs from 253,145 word-corpus compiled from professionally transcribed transcripts of 56 first-year medical students and seven facilitators. The concordance lines of the frequent ICWs were thematically analysed to define their functions. Extracts of verbal exchanges were provided to illustrate how the knowledge negotiation unfolded. Chi-square statistics were used to quantitatively compare the ICWs frequencies across the tutorial sessions. A significant p-value was set at less than 0.05. Results: Overall, the ICWs were least prevalent in the second tutorial session. Affirmation ICWs were more prevalent than other types of ICWs across the tutorial sessions. The ICWs served seventeen frequent functions of which acknowledgement, confirming and addition predominated. The students frequently discussed subject matter content, and the discussion was of exploratory nature. There were several incomplete and sentence-completion statements. Conclusion: The corpus-based analysis provides a complementary perspective on the verbal interactions occurring in the PBL tutorials in practice. The students’ verbal exchanges were collaborative and exploratory, but the students seemed to have had turn-taking problems. The implications of the study are that the corpus-based methodology could be used to explore several PBL research questions including those previously explored non-linguistically. The PBL discourse, as a means of initiating medical students into professional practice, requires monitoring to ensure compliance with educational theory and policy

Developing Clinical Reasoning Skills Through Argumentation With the Concept Map Method in Medical Problem-Based Learning

This study aims to explore the effects of argumentation with the concept map method during medical problem-based learning (PBL) on individual clinical reasoning. Individual clinical reasoning ability was assessed through problem-solving performance and arguments that students constructed during individual clinical reasoning processes. Toulmin’s model of argument was utilized as a structure for arguments. The study also explored whether there would be any differences between the firstand second-year medical students. Ninety-five medical students participated in this study, and they took two PBL modules. During PBL, they were asked as a group to construct concept maps based on their argumentation about a case under discussion. Before and after each PBL, they were asked to write individual clinical problem-solving tests. One-way, within-subjects ANOVAs were conducted to examine the quality of arguments and clinical problem-solving performance in three individual tests. The results provided evidence that utilizing argumentation with the concept map method during PBL positively affects the development of clinical reasoning skills by individual students.

Update on research and application of problem-based learning in medical science education.

Problem-based learning (PBL) is a unique form of pedagogy dedicated to developing students' self-learning and clinical practice skills. After several decades of development, although applications vary, PBL has been recognized all over the world and implemented by many medical schools. This review summarizes and updates the application and study of PBL in medical education through the literature published between 1993 and early 2017. It focuses on understanding real medical PBL courses and ways to improve PBL to achieve better learning outcomes. PBL aims to develop lifelong skills to solve practical problems rather than limiting learning to theoretical knowledge. To achieve this goal, strict and reasonable procedures need to be designed and implemented. Rigorous monitoring and timely feedback and evaluation are indispensable to constant improvements and perfecting of the process. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(2):186-194, 2018.

Effects of tutor performance and collective efficacy on learner performance and satisfaction in medical problem-based learning

Effects of tutor performance and collective efficacy on learner performance and satisfaction in medical problem-based learning

Context impact of clinical scenario on knowledge transfer and reasoning capacity in a medical problem-based learning curriculum

ABSTRACTSince 2000, the faculty of Medicine at the University of Liège has integrated problem-based learning (PBL) seminars from year two to seven in its seven-year curriculum. The PBL approach has been developed to facilitate students’ acquisition of reasoning capacity. This contextualized learning raises the question of the de- and re-contextualization process and its development during medical education. The aim is to assess transfer capacity of knowledge acquired through contextualized learning. A script concordance test (SCT) to assess clinical reasoning was administered to 104 volunteer students from year three to six of the Faculty of Medicine, and to a reference panel. The SCT has been created to measure, in a standardized way, reasoning capacity for ill-defined clinical problems. We used clinical cases from PBL seminars related to endocrinology from the third- and fifth-year (APP [Apprentissage Par Problèmes] and ARC [Apprentissage du Raisonnement Clinique] seminars). Two SCT scenarios aiming at the same learning objectives were created: one in the original learning context and one in a different, new context. Irrespective of the learning context, the reference panel showed higher scores than all groups of students. Students in year five and six obtained higher scores than younger students. A significant difference was also found in relation to the context (original/new) of the question. Higher scores were unexpectedly obtained for questions related to ARC cases than APP cases and in new contexts versus original ones, irrespective of the study level. The highest score was obtained for fifth-year cases in a new context. This study shows that from third year, students are able to transfer the knowledge acquired throughout PBL seminars for application to questions with information out of the learning context. Moreover, reasoning capacity grows with experience, irrespective of the process of transfer.

Needs analysis on the development of evidence‐based practice in an undergraduate problem‐based learning context

ABSTRACTEvidence‐based practice (EBP) is a formal information behavior recently imposed on healthcare providers, which emphasizes the incorporation of the best research evidence into the delivery of patient care. Internationally, policies that require both healthcare practice and the educational environment under which health science students are educated to be evidence based are on the rise. In medical and health sciences curricula, EBP and problem‐based learning (PBL) are often seen as synonymous, as traditional medical PBL requires students to seek out research evidence related to posed clinical problems. However, students in an undergraduate radiography program exhibit difficulties in implementing EBP, despite successful completion of a PBL course. This study describes the findings of a needs analysis undertaken to better understand the issues hindering the development of effective evidence‐based decision making skills in the PBL context.

Longitudinal assessment of progress in reasoning capacity and relation with self-estimation of knowledge base

The aim of the study was to investigate progress in reasoning capacity and knowledge base appraisal in a longitudinal analysis of data from summative evaluation throughout a medical problem-based learning curriculum. The scores in multidisciplinary discussion of a clinical case and multiple choice questionnaires (MCQs) were studied longitudinally for 213 students from years 2 to 5. The capacity of core knowledge delimitation was calculated as the difference between the levels of average ascertainment degrees given for correct and incorrect answers at MCQ. For both multidisciplinary discussion of a clinical case evaluation and self-estimation of core knowledge, the capacity increases throughout the curriculum. The reasoning capacity assessed through multidisciplinary discussion of a clinical case is positively correlated with MCQ scores and the capacity to discriminate the mastered core knowledge. In conclusion, this study indicates that self-estimation of core knowledge is associated with an increase in reasoning performance through a well-organised knowledge base. Since that ability is related to success or failure, it is suggested that student awareness about delimitation of mastered core knowledge is considered as part of learning.

Clinical reasoning gains in medical PBL: an UMLS based tutoring system

Problem based learning is becoming widely popular as an effective teaching method in medical education. Paying individual attention to a small group of students in medical problem-based learning (PBL) can place burden on the workload of medical faculty whose time is very costly. Intelligent tutoring systems offer a cost effective alternative in helping to train the students, but they are typically prone to brittleness and the knowledge acquisition bottleneck. Existing tutoring systems accept a small set of approved solutions for each problem scenario stored into the system. Plausible student solutions that lie outside the scope of the explicitly encoded ones receive little acknowledgment from the system. Tutoring hints are also confined to the knowledge space of the approved solutions, leading to brittleness in the tutoring approach. We report the clinical reasoning gains off a tutoring system for medical PBL that employs and represents the widely available medical knowledge source UMLS as the domain ontology. We exploit the structure of the concept hierarchy to expand the plausible solution space and generate hints based on the problem solving context. Evaluation of student learning outcomes led to highly significant learning gains (Mann-Whitney, p < 0.001).

Employing UMLS for generating hints in a tutoring system for medical problem-based learning

While problem-based learning has become widely popular for imparting clinical reasoning skills, the dynamics of medical PBL require close attention to a small group of students, placing a burden on medical faculty, whose time is over taxed. Intelligent tutoring systems (ITSs) offer an attractive means to increase the amount of facilitated PBL training the students receive. But typical intelligent tutoring system architectures make use of a domain model that provides a limited set of approved solutions to problems presented to students. Student solutions that do not match the approved ones, but are otherwise partially correct, receive little acknowledgement as feedback, stifling broader reasoning. Allowing students to creatively explore the space of possible solutions is exactly one of the attractive features of PBL. This paper provides an alternative to the traditional ITS architecture by using a hint generation strategy that leverages a domain ontology to provide effective feedback. The concept hierarchy and co-occurrence between concepts in the domain ontology are drawn upon to ascertain partial correctness of a solution and guide student reasoning towards a correct solution. We describe the strategy incorporated in METEOR, a tutoring system for medical PBL, wherein the widely available UMLS is deployed and represented as the domain ontology. Evaluation of expert agreement with system generated hints on a 5-point likert scale resulted in an average score of 4.44 (Spearman’s ρ=0.80, p<0.01). Hints containing partial correctness feedback scored significantly higher than those without it (Mann Whitney, p<0.001). Hints produced by a human expert received an average score of 4.2 (Spearman’s ρ=0.80, p<0.01).

Scaffolding problem-based learning with CSCL tools

Small-group medical problem-based learning (PBL) was a pioneering form of collaborative learning at the university level. It has traditionally been delivered in face-to-face text-based format. With the advancement of computer technology and progress in CSCL, educational researchers are now exploring how to design digitally-implemented scaffolding tools to facilitate medical PBL. The “deteriorating patient” (DP) role play was created as a medical simulation that extends traditional PBL and can be implemented digitally. We present a case study of classroom usage of the DP role play that examines teacher scaffolding of PBL under two conditions: using a traditional whiteboard (TW) and using an interactive whiteboard (IW). The introduction of the IW technology changed the way that the teacher scaffolded the learning. The IW showed the teacher all the information shared within the various subgroups of a class, broadening the basis for informed classroom scaffolding. The visual records of IW usage demonstrated what students understood and reduced the need to structure the task. This allowed more time for engaging students in challenging situations by increasing the complexity of the problem. Although appropriate scaffolding is still based on the teacher’s domain knowledge and pedagogy experience, technology can help by expanding the scaffolding choices that an instructor can make in a medical training context.

An exploration of the strategic challenges of problem based learning (PBL) in medical education environment: A paradigm shift from traditional lectures

This study was done to explore the challenges of problem-based learning (PBL) in medical education and to propose a framework with implications for practice and learning. The paper uses a total of 24 undergraduate medical students divided into 3 groups who participated in the focus group discussions. A quantitative instrument was used as triangulation to gather data on 18 statements through Likert scale ratings. In addition, semi-structured interviews were conducted with 6 medical PBL facilitators. Quotes from the participants are used to support the key themes and issues that have emerged from the data. Quantitative data are used to support certain important issues. The successful development of PBL will depend on re-establishing the strategic direction of PBL within a certain context, evaluating the social and learning structures associated with power distribution, and providing non-routine rigorous educational systems to enhance learning. Keywords: Problem Based Learning (PBL); medical education; focus group discussion; Malaysia.

COMET: A Collaborative Tutoring System for Medical Problem-Based Learning

This paper discussed about the developed collaborative intelligent tutoring system for medical PBL called Comet (collaborative medical tutor). Comet uses Bayesian networks to model the knowledge and activity of individual students as well as small groups. It applies generic tutoring algorithms to these models and generates tutorial hints that guide problem solving. An early laboratory study shows a high degree of agreement between the hints generated by Comet and those of experienced human tutors. Evaluations of Comet's clinical-reasoning model and the group reasoning path provide encouraging support for the general framework.

Modeling individual and collaborative problem-solving in medical problem-based learning

Today a great many medical schools have turned to a problem-based learning (PBL) approach to teaching as an alternative to traditional didactic medical education to teach clinical-reasoning skills ...

A Bayesian approach to generating tutorial hints in a collaborative medical problem-based learning system

Today a great many medical schools have turned to a problem-based learning (PBL) approach to teaching. While PBL has many strengths, effective PBL requires the tutor to provide a high degree of personal attention to the students, which is difficult in the current academic environment of increasing demands on faculty time. This paper describes intelligent tutoring in a collaborative medical tutor for PBL. The main contribution of our work is the development of representational techniques and algorithms for generating tutoring hints in PBL group problem solving, as well as the implementation of these techniques in a collaborative intelligent tutoring system, COMET. The system combines concepts from computer-supported collaborative learning with those from intelligent tutoring systems. The system uses Bayesian networks to model individual student clinical reasoning, as well as that of the group. The prototype system incorporates substantial domain knowledge in the areas of head injury, stroke and heart attack. Tutoring in PBL is particularly challenging since the tutor should provide as little guidance as possible while at the same time not allowing the students to get lost. From studies of PBL sessions at a local medical school, we have identified and implemented eight commonly used hinting strategies. In order to evaluate the appropriateness and quality of the hints generated by our system, we compared the tutoring hints generated by COMET with those of experienced human tutors. We also compared the focus of group activity chosen by COMET with that chosen by human tutors. On average, 74.17% of the human tutors used the same hint as COMET. The most similar human tutor agreed with COMET 83% of the time and the least similar tutor agreed 62% of the time. Our results show that COMET's hints agree with the hints of the majority of the human tutors with a high degree of statistical agreement (McNemar test, p=0.652, kappa=0.773). The focus of group activity chosen by COMET agrees with that chosen by the majority of the human tutors with a high degree of statistical agreement (McNemar test, p=0.774, kappa=0.823). Bayesian network clinical reasoning models can be combined with generic tutoring strategies to successfully emulate human tutor hints in group medical PBL.

Lectures in problem-based learning—Why, when and how? An example of interactive lecturing that stimulates meaningful learning

Even though opinions differ as to whether lecturing is compatible with problem-based learning (PBL) or not, lectures are still a common form of instruction in PBL curricula. This paper discusses the lecture in the framework of theories of learning in general and the medical problem-based learning tradition in particular. An example of how theories of learning can be implemented in the lecture hall is presented. Theories that underpin PBL as an educational philosophy rather than as a method of instruction are reviewed. A lecture form, organized in introductory, in depth and application lectures, that responds to important factors for stimulating deep processing of knowledge and meaningful learning is discussed. Examples of and practical points about how to renew and restructure lectures in a way that counteracts surface approaches to learning, teacher centring and student passivity are presented. We argue that, with proper awareness of possible drawbacks of the large format, lectures can be used as valuable tools for learning also in a PBL curriculum.

Modeling Human-Like Robustness in an Intelligent Tutoring System

Intelligent tutoring systems are no different from other knowledge based systems in that they are often plagued by brittleness. Intelligent tutoring systems for problem solving are typically loaded with problem scenarios for which specific solutions are constructed. Solutions presented by students, are compared against these specific solutions, which often leads to a narrow scope of reasoning, where students are confined to reason towards a specific solution. Student solutions that are different from the specific solution entertained by the system are rejected as being incorrect, even though they may be acceptable or close to acceptable. This leads to brittleness in tutoring systems in evaluating student solutions and returning appropriate feedback. In this paper we discuss a few human-like attributes in the context of robustness that are desirable in knowledge based systems. We then present a model of reasoning through which a tutoring system for medical problem-based learning, can begin to exhibit human-like robust behavior in evaluating solutions in a broader context using UMLS, and respond with hints that are mindful of the partial correctness of the student solution.