Reflective learning with complex problems in a visualization-based learning environment with expert support

Abstract Effective learning through problem solving is difficult to realize as problem solving often involves complex processes that are inaccessible to novices. It is important to make the complex process visible to novices and provide them with necessary support throughout the tasks. This study proposes a computer-based learning environment that allows learners to capture their problem-solving process in a visual format for effective thinking and reflection. Moreover, expert support is incorporated to improve self-reflection by allowing learners to identify the difference between their performance and that of the expert. This study adopted a pretest-posttest control group design. The experimental group used the visualization-based learning environment involving expert support, while the control group used the visualization-based learning environment without expert support. Forty-five senior year medical students completed the study with five diagnostic problem-solving tasks in four weeks. The results showed that the inclusion of expert support made the visualization-based reflective learning environment more effective in improving learners’ problem-solving performance, supporting their construction of knowledge from problem-solving tasks, and improving their confidence and satisfaction with the learning experience.

[1]  Jeroen Janssen,et al.  Effects of representational guidance during computer-supported collaborative learning , 2008, ICLS.

[2]  A. Neville Problem-Based Learning and Medical Education Forty Years On , 2008, Medical Principles and Practice.

[3]  Minhong Wang,et al.  Computer-based learning environments for deep learning in inquiry and problem-solving contexts , 2016 .

[4]  Ravi Paul,et al.  Analyzing the structure of expert knowledge , 2006, Inf. Manag..

[5]  Cynthia K.Y. Yiu,et al.  Qualitative and quantitative analysis of the students’ perceptions to the use of 3D electronic models in problem-based learning , 2017 .

[6]  Diana H J M Dolmans,et al.  The Maastricht Clinical Teaching Questionnaire (MCTQ) as a Valid and Reliable Instrument for the Evaluation of Clinical Teachers , 2010, Academic medicine : journal of the Association of American Medical Colleges.

[7]  Frank Fischer,et al.  Internal and external scripts in computer-supported collaborative inquiry learning , 2007, Learning and Instruction.

[8]  Nian-Shing Chen,et al.  Connecting problem-solving and knowledge-construction processes in a visualization-based learning environment , 2013, Comput. Educ..

[9]  Clinton Golding,et al.  Teaching clinical reasoning by making thinking visible: an action research project with allied health clinical educators , 2014, BMC Medical Education.

[10]  Lisa Hartling,et al.  Problem-based learning in pre-clinical medical education: 22 years of outcome research , 2010, Medical teacher.

[11]  Noel Entwistle,et al.  Promoting deep learning through teaching and assessment: conceptual frameworks and educational contexts. , 2000 .

[12]  M. Wong,et al.  The effects of problem-based learning during medical school on physician competency: a systematic review , 2008, Canadian Medical Association Journal.

[13]  Chris Dede,et al.  Design of a Three-Dimensional Cognitive Mapping Approach to Support Inquiry Learning , 2017, J. Educ. Technol. Soc..

[14]  J. Dewey Experience and Education , 1938 .

[15]  Paul A. Kirschner,et al.  Ten Steps to Complex Learning: A Systematic Approach to Four-Component Instructional Design , 2007 .

[16]  Bei Yuan,et al.  Deep Learning towards Expertise Development in a Visualization-based Learning Environment , 2017, J. Educ. Technol. Soc..

[17]  Emil Petrusa,et al.  Tracking Development of Clinical Reasoning Ability Across Five Medical Schools Using a Progress Test , 2011, Academic medicine : journal of the Association of American Medical Colleges.

[18]  Brian J. Reiser,et al.  Scaffolding Complex Learning: The Mechanisms of Structuring and Problematizing Student Work , 2004, The Journal of the Learning Sciences.

[19]  Jun Liu,et al.  Visualizing complex processes using a cognitive-mapping tool to support the learning of clinical reasoning , 2016, BMC medical education.

[20]  Richard E. Clark,et al.  Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching , 2006 .

[21]  Marcia C. Linn,et al.  Designing the Knowledge Integration Environment , 2000 .

[22]  T. Gog,et al.  In the eyes of the beholder: How experts and novices interpret dynamic stimuli , 2010 .

[23]  Hannie Gijlers,et al.  Using Concept Maps to Facilitate Collaborative Simulation-Based Inquiry Learning , 2013 .

[24]  Bei Yuan,et al.  Design of a computer-based learning environment to support diagnostic problem solving towards expertise development , 2016 .

[25]  C. Hmelo‐Silver Problem-Based Learning: What and How Do Students Learn? , 2004 .

[26]  Huaiqing Wang,et al.  Intelligent Agent Supported Flexible Workflow Monitoring System , 2002, CAiSE.

[27]  M. Segers,et al.  Effects of problem-based learning: a meta- analysis , 2003 .

[28]  H. Schmidt,et al.  A Cognitive Perspective on Medical Expertise: Theory and Implications , 1990 .

[29]  K. Mann,et al.  Reflection and reflective practice in health professions education: a systematic review , 2009, Advances in health sciences education : theory and practice.

[30]  M. Albanese,et al.  Problem‐based Learning: A Review of Literature on Its Outcomes and Implementation Issues , 1993, Academic medicine : journal of the Association of American Medical Colleges.

[31]  Etienne Wenger,et al.  Situated Learning: Legitimate Peripheral Participation , 1991 .

[32]  Christine Chin,et al.  Learning in Science: A Comparison of Deep and Surface Approaches. , 2000 .

[33]  Henk G. Schmidt,et al.  The Explanation of Clinical Concepts by Expert Physicians, Clerks, and Advanced Students , 1999 .

[34]  J. Keller Motivational Design for Learning and Performance: The ARCS Model Approach , 2009 .

[35]  A. Tversky Features of Similarity , 1977 .

[36]  Jae-Won Moon Reflection in Learning and Professional Development: Theory and Practice , 2005 .

[37]  Susanne P. Lajoie,et al.  Constructing knowledge in the context of BioWorld , 2001 .

[38]  J. Arbaugh Virtual Classroom Characteristics and Student Satisfaction with Internet-Based MBA Courses , 2000 .

[39]  K. A. Ericsson,et al.  Deliberate practice and acquisition of expert performance: a general overview. , 2008, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[40]  Daniel D. Suthers,et al.  Beyond threaded discussion: Representational guidance in asynchronous collaborative learning environments , 2008, Comput. Educ..

[41]  Diana H J M Dolmans,et al.  The development of an instrument for evaluating clinical teachers: involving stakeholders to determine content validity , 2008, Medical teacher.

[42]  Pm Jenkinson,et al.  Cognitive , 2020, Definitions.

[43]  D. Schoen,et al.  The Reflective Practitioner: How Professionals Think in Action , 1985 .

[44]  Roger W Moni,et al.  Student perceptions and use of an assessment rubric for a group concept map in physiology. , 2008, Advances in physiology education.

[45]  C. Hmelo‐Silver,et al.  Scaffolding and Achievement in Problem-Based and Inquiry Learning: A Response to Kirschner, Sweller, and Clark (2006) , 2007 .

[46]  J. Michael Spector,et al.  Highly integrated model assessment technology and tools , 2010, CELDA 2008.

[47]  Minhong Wang,et al.  Guest Editorial: Fostering Deep Learning in Problem-Solving Contexts with the Support of Technology , 2017, J. Educ. Technol. Soc..

[48]  A. Collins,et al.  Situated Cognition and the Culture of Learning , 1989 .

[49]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[50]  Minhong Wang,et al.  Using 3D virtual environments to facilitate students in constructivist learning , 2013, Decis. Support Syst..

[51]  David H. Jonassen,et al.  Instructional design models for well-structured and III-structured problem-solving learning outcomes , 1997 .