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APR2 POD 2012

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APR2 POD 2012

  1. 1. The Effects of Virtual Labs and Cooperative Learning in Anatomy Instruction Andy Saltarelli, Ph.D. ASSETT University of Colorado – Boulder William Saltarelli, Ph.D. College of Health Professions Central Michigan University Cary Roseth, Ph.D. College of Education Michigan State University POD Conference 2012, Seattle, WA
  2. 2. Game Plan Backstory (The Partnership) Story (The Research)
  3. 3. Backstory – Why Change?
  4. 4. Backstory – Why Change?
  5. 5. Backstory – Why Change?
  6. 6. Backstory – Partnering
  7. 7. Backstory – Partnering Practitioner Edu Tech Edu Psy
  8. 8. Backstory – Theory -Social Interdependence Theory (Deutsch, 1949, 1973; Johnson & Johnson, 1989) - 40 Years of Research (Johnson & Johnson, 2007): - Achievement  .55 (ES) - Self-Esteem  .42 (ES) - Peer Relationships  .42 (ES) - Perspective Taking  .44 (ES)
  9. 9. Backstory Authentic Pedagogical “problem” Interdisciplinary Partnership, T&L Research Support Theory Testing, Iterative Approach
  10. 10. Story – Human Anatomy  300 students per semester  4 credit course  15 cadaver-based lab sections taught by 7 GAs  1 large lecture and 2 labs per week  Grade of D, E or Withdrawal ~30%  Feeder/Weeder Course
  11. 11. Story - Study #1 Simulated Lab Cadaver Lab APR Only Cadaver Lab VS Only Lab Conclusions: Results: Cadaver-only students performed better than APR-only Explanation: Technology pre-training & student perceptions of software were poor Solution: Infuse active learning (e.g., cooperative learning) to ameliorate observed negative effects of simulation software
  12. 12. Tech Integration Problem
  13. 13. Tech Integration ECAR 2012
  14. 14. Tech Integration TPACK (Mishra & Koehler, 2006; tpack.org)
  15. 15. Tech Integration TPACK UPS Comercial - http://vimeo.com/14182460
  16. 16. Current Study Experimental-control design: 2 Instructional Technology (APR, Cadaver) X 2 Cooperative Learning (Jigsaw, No Jigsaw) Jigsaw Individual APR APR APR Software + + Jigsaw Individual Cadaver Cadaver Cadaver + + Only Jigsaw Individual
  17. 17. Method  Participant Flow  N = 250 in 15 lab sections randomly to 1 of 4 conditions Jigsaw Individual APR 4 sections 4 sections Software N=73 N=63 Cadaver 4 sections 3 sections Only N=71 N=43
  18. 18. Current Study Jigsaw + APR Software
  19. 19. Current Study Individual + APR Software
  20. 20. Current Study
  21. 21. Independent Variables Virtual Labs via Simulation Software Cooperative Learning via Jigsaw Anatomy & Physiology Revealed 3.0 (APR) (Aronson, 1978, 2011)
  22. 22. Dependent Variable  Achievement:  Quiz Grade, 1-Week Retention (6-items; α = .78 )  Intrinsic Motivation (Ryan, 1982):  Relatedness (8-items; α = .88), Interest (7-items; α = .92), Value (7-items; α = .93)  Social Interdependence (Johnson & Norem-Hebeisen, 1977):  Cooperation (7-items; α = .89), Competition (7-items; α = .93), Individualism (7-items; α = .86)  Task-technology fit (Goodhue, 1998):  Presentation (2-items; α = .94)
  23. 23. Results: Achievement Result: Students who participated in the jigsaw activity performed better than those that didn’t on the 1-week retention quiz. (Wilks's λ=.97, F(1,218) p = .04)
  24. 24. Results: Achievement Result: No difference between APR and cadaver-only study on the 1-week retention quiz.
  25. 25. Results: Motivation Result: Students who participated in the jigsaw activity had higher motivation* than those who didn’t participate. *F=5.96, P=.01
  26. 26. Results: Motivation Result: Students who studied with APR in lab had lower motivation* than cadaver-only students. *F=28.83, P<.001
  27. 27. Results: Motivation Result: Results suggest* that the jigsaw activity ameliorated decreases in motivation observed in the APR group. *Jig x APR Interaction, F = 6.57, p = .01
  28. 28. Results: Task-technology Fit Result: Students’ perceptions of task-technology fit was greater in jigsaw over individual learning. *Wilks's λ=.95, F(1,213) p < .01
  29. 29. Study #2 – Results Qualitative (Regarding Jigsaw Activity): •I liked how I was able to teach and be taught at the same time. •Iliked teaching my objectives to others. It helped me learn more in depth. •Iliked this activity because it allows us to work together more and receive feedback from each other. •I enjoyed teaching the material to others. It makes it so I have to master it in order to teach it. •Thegroup activity helped me get more involved and learn different ways to study the material.
  30. 30. Conclusions Jigsaw cooperative learning provides clear advantages over traditional, individual lab learning methods in anatomy instruction Results suggest that jigsaw cooperative learning ameliorates the initial negative effects of introducing new virtual software The positive effects of cooperative learning pedagogy appear to “spill over” onto students’ perceptions of technology
  31. 31. Special Thanks Jim Therrell & the Faculty Center for Innovative Teaching at Central Michigan University
  32. 32. References Aronson, E. (1978). The jigsaw classroom. Beverly Hills, CA: Sage. Aronson, E., & Patnoe, S. (2011). Cooperation in the Classroom: The Jigsaw Method, 3rd Edition (3rd ed.). Pinter & Martin Ltd. Colella, V. (2000). Participatory simulations: Building collaborative understanding through immersive dynamic modeling. The Journal of the Learning Sciences, 9(4), 471-500. Correll, D. (2008). For human dissection needs, the body count is low - Los Angeles Times. Retrieved December 11, 2009, from http://articles.latimes.com/2008/may/26/nation/na-cadavers26 Deutsch, M. (1949). A theory of cooperation and competition. Human Relations, 2, 129–152. Deutsch, M. (1973). The resolution of conflict. New Haven, CT: Yale University Press. Garg, A. X., Norman, G. R., Eva, K. W., Spero, L., & Sharan, S. (2002). Is there any real virtue of virtual reality?: The minor role of multiple orientations in learning anatomy from computers. Academic Medicine, 77(10), S97-S99. Goldstone, R. L., & Son, J. Y. (2005). The transfer of scientific principles using concrete and idealized simulations. Journal of the Learning Sciences, 14(1), 69–110. James, D. R. C., Purkayastha, S., Athanasiou, T., Shafiq, O., Paraskevas, P., & Darzi, A. (2004). Anatomy: The future teaching of undergraduates. Hospital Medicine, 65, 681–685. Johnson, D. W., & Johnson, R. T. (2009). Energizing learning: The instructional power of conflict. Educational Researcher, 38, 37–51. Johnson, D. W., & Johnson, R. T. (1989). Cooperation and competition: Theory and research. Edina, MN: Interaction. Johnson, D., Johnson, R., & Smith, K. (2007). The State of Cooperative Learning in Postsecondary and Professional Settings. Educational Psychology Review, 19(1), 15–29. Keedy, A. W., Durack, J. C., Sandhu, P., Chen, E. M., O’Sullivan, P. S., & Breiman, R. S. (2011). Comparison of traditional methods with 3D computer models in the instruction of hepatobiliary anatomy. Anatomical Sciences Education, 4, 84-91. Lindgren, R., & Schwartz, D. L. (2009). Spatial learning and computer simulations in science. International Journal of Science Education, 31(3), 419–438. Hisley, K, Anderson, L, Smith, S, Kavic, S, Tracy, J. (2008). Coupled physical and digital cadaver dissection followed by a visual test protocol provides insights into the nature of anatomical knowledge and its evaluation. Anatomical Science Education, 1, 27-40. Nicholson, D. T., Chalk, C., Funnell, W. R. J., & Daniel, S. J. (2006). Can virtual reality improve anatomy education? A randomised controlled study of a computer- generated three-dimensional anatomical ear model. Medical Education, 40, 1081-1087. Pear, R. (2009). Shortage of doctors an obstacle to Obama goals. Retrieved December 11, 2009 from http://www.nytimes.com/2009/04/27/health/policy/27care.html Resnick, M., Berg, R., & Eisenberg, M. (2000). Beyond black boxes: Bringing transparency and aesthetics back to scientific investigation. Journal of the Learning Sciences, 9(1), 7-30. Saltarelli, A. Saltarelli, W. & Roseth, C. (2012). Under review, Journal of Educational Psychology. Teo, T. (Ed.). (2011). Technology Acceptance in Education: Research and Issues. Sense Publishers. Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the Technology Acceptance Model. Information Systems Research, 11(4), 365. Venkatesh, V., Morris, M. G., Davis, G. B., Davis, F. D., DeLone, W., McLean, E., Jarvis, C. B., et al. (2003). User acceptance of information technology: Toward a unified view. Management Information Systems Quarterly, 27, 425–478. Winn, W., Stahr, F., Sarason, C., Fruland, R., Oppenheimer, P., & Lee, Y. L. (2006). Learning oceanography from a computer simulation compared with direct experience at sea. Journal of Research in Science Teaching, 43(1), 25–42.
  33. 33. Image Credits Coffee - http://www.flickr.com/photos/zedworks/ Frustration - http://www.flickr.com/photos/sharynmorrow/ Spare Change - http://www.flickr.com/photos/kicey/
  34. 34. Andy Saltarelli, Ph.D. ASSETT University of Colorado – Boulder assett.colorado.edu | andysaltarelli.com | @ajsalts

Editor's Notes

  • Faculty development-faculty research -- What does it look like? Feel like? How do you get there? Do a jigsaw? Some sort of response?
  • Faculty development-faculty research -- What does it look like? Feel like? How do you get there? Do a jigsaw? Some sort of response?
  • Do Venn diagram
  • Average effect sizes
  • DEW = GRADE OF D, E, OR WITHDRAWAL

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