Pedagogical moves and student thinking in technology-mediated medical problem-based learning: Supporting novice-expert shift

Technology‐mediated simulation is often used in medical problem‐based learning (PBL) approaches to offer authentic contexts and immersive engagement for learning. However, critiques argue that these approaches are lacking in the structure necessary to support productive learning—that they often result in mindless doing without the thinking processes needed that lead to deeper understanding and expertise. This paper presents data from a technology‐mediated simulation, called HMS MEDscience, to demonstrate: (1) that it effectively leads to greater expert reasoning—evident through responses in content knowledge and problem‐solving ability that more closely aligned with a rubric of expert responses to the same questions; (2) through a series of case studies, the implicit pedagogical moves the teachers make to support students' thinking processes. Significant pre‐ to posttest gains indicate more expert reasoning. In addition, classroom videos indicate shifts from novice toward more expert medical science reasoning and illustrate the fine‐grained supporting moves that teachers use to guide students' thinking toward more expert understanding of the problem space. This study highlights the importance of the thinking processes that students engage in as they participate in technology‐mediated PBL and the accompanying teacher attention to student thinking through supporting pedagogical moves. Practitioner NotesWhat is already known about this topic Technology‐mediated problem‐based learning (PBL) can invite an immersive experience for learners to engage with authentic problems.Broad framing for effective PBL includes features such as structured group work, a tutorial process for structuring knowledge and action plans, constructive investigation, and cognitive mentorship.The results on PBL have been mixed depending upon how it is enacted. It typically takes very skilled teachers and additional inherent structure.What this paper adds It demonstrates that novice‐expert shifts are possible in high school students' reasoning about technology‐supported, medical‐based problem solving.It reveals six nuanced thinking scaffolds that teachers used to support students' shift toward the more expert conceptions.It identifies seven thinking moves that students engaged in during the problem‐solving context.Implications for practice and/or policy It alerts practitioners to the need to attend to the pedagogical moves that they employ to support student thinking.It demonstrates the importance of the thinking processes that students engage in as they participate in technology‐mediated PBL.It demonstrates that successful learning in technology‐mediated PBL contexts is accompanied by teacher attention to student thinking and supporting pedagogical maneuvers. [ABSTRACT FROM AUTHOR] uracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[1]  Brian R. Belland,et al.  A Conceptual Framework for Organizing Active Learning Experiences in Biology Instruction , 2012 .

[2]  J. Sim,et al.  Saturation in qualitative research: exploring its conceptualization and operationalization , 2017, Quality & Quantity.

[3]  Janet L. Kolodner,et al.  Problem-Based Learning Meets Case-Based Reasoning in the Middle-School Science Classroom: Putting Learning by Design(tm) Into Practice , 2003 .

[4]  J. Gordon,et al.  Using immersive healthcare simulation for physiology education: initial experience in high school, college, and graduate school curricula. , 2011, Advances in physiology education.

[5]  Johannes Strobel,et al.  When is PBL More Effective? A Meta-synthesis of Meta-analyses Comparing PBL to Conventional Classrooms , 2009 .

[6]  J. F. Kelley,et al.  An iterative design methodology for user-friendly natural language office information applications , 1984, TOIS.

[7]  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 .

[8]  Cindy E. Hmelo-Silver,et al.  Goals and Strategies of a Problem-based Learning Facilitator , 2006 .

[9]  Serife Ak,et al.  The role of technology-based scaffolding in problem-based online asynchronous discussion , 2016, Br. J. Educ. Technol..

[10]  Bei Yuan,et al.  Reflective learning with complex problems in a visualization-based learning environment with expert support , 2018, Comput. Hum. Behav..

[11]  Eleni A. Kyza,et al.  Reflective inquiry: enabling group self-regulation in inquiry-based science using the progress portfolio tool , 2002, CSCL.

[12]  Exploration of a method to analyze group interactions in problem-based learning , 2004, Medical teacher.

[13]  Roger L. Kneebone,et al.  The role of medical simulation technologies for outreach activities in secondary school education: A workshop for prospective medical students , 2013, Br. J. Educ. Technol..

[14]  Krista Glazewski,et al.  Scaffolding and supporting use of information for ambitious learning practices , 2019, Information and Learning Sciences.

[15]  Carolyn Penstein Rosé,et al.  Towards an Agile Approach to Adapting Dynamic Collaboration Support to Student Needs , 2014, International Journal of Artificial Intelligence in Education.

[16]  Richard K. Coll,et al.  The role of models/and analogies in science education: implications from research , 2005 .

[17]  Derek C. Briggs,et al.  Experimental and Quasi-Experimental Studies of Inquiry-Based Science Teaching , 2012 .

[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]  Minhong Wang,et al.  Improving the learning of clinical reasoning through computer-based cognitive representation , 2014, Medical education online.

[20]  Jeffrey B Cooper,et al.  Bringing Good Teaching Cases “To Life”: A Simulator-Based Medical Education Service , 2004, Academic medicine : journal of the Association of American Medical Colleges.

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

[22]  Heisawn Jeong,et al.  Development of Group Understanding via the Construction of Physical and Technological Artifacts , 2013 .

[23]  J. Elliott,et al.  Teaching Medical Error Disclosure to Residents Using Patient-Centered Simulation Training , 2014, Academic medicine : journal of the Association of American Medical Colleges.

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

[25]  Chris Dede,et al.  Using a three‐dimensional thinking graph to support inquiry learning , 2018 .

[26]  Allan Collins,et al.  THE COMPUTER AS A TOOL FOR LEARNING THROUGH REFLECTION , 1986 .

[27]  Susanne P. Lajoie,et al.  Scaffolding problem-based learning with CSCL tools , 2010, Int. J. Comput. Support. Collab. Learn..