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Using Computer-Simulated Case-Based Scenarios to Improve Learning

Using Computer-Simulated Case-Based Scenarios to Improve Learning. David M. Segal PhD Assistant Professor. Department of Health Professions College of Health & Public Affairs University of Central Florida. Case-based Learning.

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Using Computer-Simulated Case-Based Scenarios to Improve Learning

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  1. Using Computer-Simulated Case-Based Scenarios to Improve Learning David M. Segal PhD Assistant Professor Department of Health Professions College of Health & Public Affairs University of Central Florida

  2. Case-based Learning The effectiveness of case-based instruction in education is supported by a significant body of research Teaching health science students how to work in teams in the classroom with members of varying experience and skill levels offers valuable real-life simulated learning which will better prepare them for the healthcare workplace Students with strong critical thinking skills make better clinical decisions Focus shifts towards higher order processing skills rather than merely content How can we assess context-specific critical learning? How can technology mediate this?

  3. Pedagogy Poll Question • How many use the following teaching methods to deliver your content? • case-based learning • problem-based learning • team-based learning • collaborative learning • web-based instruction (WebCT, Blackboard) • other

  4. CBL Poll Question • What system do you use to implement case-based teaching? • paper-based • word • powerpoint • wimba • animations • immersive (second-life, active worlds) • mannequins • standardized patients • role-plays (students)

  5. What is critical thinking? • Students demonstrate the ability to think by being able to: • Analyze complex issues and make informed decisions; • Synthesize information in order to arrive at reasoned conclusions; • Evaluate the logic, validity, and relevance of data; • Solve challenging problems; • Use knowledge and understanding to generate and explore new questions; • Distinguish between observation and inference; • Identify the axioms/assumptions in any argument and judge their validity; • Identify the nature of the reasoning being used. Know when inductive or deductive reasoning is required; • Use circular reasoning to reflect on decisions.

  6. Program Decision-Making Learning Outcomes • Demonstrate proficiency with scientific content • Demonstrate critical thinking skills in critically evaluating context-specific data for relevance, consistency, and fidelity • Demonstrate proficient decision-making skills to determine the best diagnosis and treatment for simulated patient • Demonstrate proficiency with integration of scientific content to identify the etiology, pathogenesis, clinical manifestations, diagnosis, and treatment for patient • Demonstrate information fluency by retrieving, interpreting, and critically evaluating published literature for most relevant evidence-based scientific studies • Articulate clinical expertise by communicating the risks and benefits for different courses of action to treat patients

  7. Kim et al, Medical Education, 40:867-876, 2006

  8. Coursework • Intro to Pharmacology HSC 3157 450 students Online • Pathophysiology HSC 4550 150 students f2f • Medical Pharmacology 1 HSC 4148 80 students f2f • 680 students FALL • Intro to Pharmacology HSC 3157 450 students Online • Pathophysiology HSC 4550 150 students Online • Medical Pharmacology 2 HSC 4149 45 students Online • Pathology/Pharmacology PHT 5306 35 students f2f • 680 students SPRING • Intro to Pharmacology HSC 3157 150 students Online • 150 students SUMMER ANNUAL TOTAL: 1,510 students

  9. WebCT Limitations How can you assess critical thinking and decision making skills in WebCT environment? How can you implement critical thinking exercises in large online classes? How can you grade asynchronous activities with large online classes? How can you conduct group collaborative work with text-based synchronous chatrooms?

  10. Patient Case Library Over 300 cases are available Initial history, additional history, differential diagnosis, laboratory & diagnostics, diagnosis, treatment, subsequent history Primary System disorders Immunity (25) Oxygen transport (15) Cardiopulmonary (35) Fluid/electrolyte (15) Acid-base (15) Renal/bladder (35) Urogenital (30) Gastrointestinal (35) Endocrinology (25) Musculoskeletal (35) Integumentary (20) Neurological (35)

  11. MyCaseSpace CBL dynamic, interactive, learning management system Virtual characters Library (50 avatars, 9 languages, 6 races, genders, 6 facial gestures) Multi-nodal cases Self-assessment Reflective learning Student-centered learning Critical thinking and decision-making triggers and activities Curriculum learning objectives and competencies mapping

  12. Familial Case Studies

  13. Improved Clinical Decision-Making Outcomes using Case study Learning SIMULATED CASES RESULTS Pre- and post-examinations of clinical case scenarios Group I: 11 +/- 2% (p<0.001) Group II: 19 +/- 3% (p<0.001) Group III: 31 +/- 4% (p<0.001) *positive improvements in scores relative to control group IV Group I: Online static text case scenarios (n=200) Group II: Online interactive case scenarios (n=200) Group III: Online interactive virtual character case scenarios (n=200)Group IV: No case scenario training (control; n=200)

  14. Improved Clinical Decision-Making Outcomes using Case study Learning Post-usage survey results participant opinions about validity, performance characteristics, and utility for training 1. Are the scenarios enjoyable? 2. Do the scenarios address important clinical competencies? 3. Do participants view the simulation as a learning tool? 4. Is improved technical fidelity required for authenticity? 5. Was the session realistic? * statistically significant difference (p<0.001) * * * * * * * * * * Group I: Online static text case scenarios Group II: Online interactive case scenarios Group III: Online interactive virtual character case scenarios Group IV: No case scenario training (control) strongly agree agree or disagree strongly disagree

  15. Sequential Decision-Making Processing Initial history 5% 8% Diagnosis Additional history 23% 92% Treatments 45% 54% 52% 62% Differential diagnosis Laboratory & diagnostics 30%

  16. Reflective Thinking Decision-Making Case Simulation Scoring Means by Iterations 1: 35 +/- 10% 2: 48 +/- 12% 3: 55 +/- 10% 4: 69 +/- 8% 5: 78 +/- 9% 6: 83 +/- 6% 7: 85 +/- 5% 8: 91 +/- 5% 9: 94 +/- 5%

  17. Collaborative Technology Poll Question • What technology have you used to promote collaborative learning in • your students? • classroom paper-based • videoconferencing • classroom response systems • immersive environment • other

  18. iLinc Virtual classroom Inter-disciplinary, inter-institutional Team-based Cooperative Active learning Synchronous interactions Group discussions with Q&A Virtual Grand Rounds

  19. Multi-disciplinary Collaborative Groups Individual case work Group I: Medical Pharmacology 1 (n=29) 16 +/- 6% Group II: Medical Pharmacology 2 (n=24) 18 +/- 8% Group III: Pathophysiology (n=25) 26 +/- 8% Collaborative case work Group IV: Pathophysiology/Med Pharm 1 (n=80) 37 +/- 8% Group V: Pathophysiology/Med Pharm 2 (n=80) 44 +/- 6%

  20. RESULTS: Students prefer computer simulated case studies for convenient access, collaboration, and varied attributes Cases can be designed with multi-nodal decision points to enhance interactive experience Improvements in student critical thinking and decision-making skills are observed in cases which are relevant and realistic cases compared to challenging and engaging attributes Most significant improvements observed in cases with basic science and clinical aspects Computer-simulated case scenarios can be developed for any discipline using this system and these case-building concepts Contact: David Segal, PhD dsegal@mail.ucf.edu

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