APR2 POD 2012


Published on

  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide
  • 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
  • APR2 POD 2012

    1. 1. The Effects of Virtual Labs andCooperative 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 PlanBackstory(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. BackstoryAuthentic Pedagogical “problem”Interdisciplinary Partnership, T&LResearch SupportTheory 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 LabConclusions:Results: Cadaver-only students performed better than APR-onlyExplanation: Technology pre-training & student perceptions ofsoftware were poorSolution: Infuse active learning (e.g., cooperative learning) toameliorate 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 IntegrationTPACK 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 StudyJigsaw + APR Software
    19. 19. Current StudyIndividual + APR Software
    20. 20. Current Study
    21. 21. Independent VariablesVirtual 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: AchievementResult: Students who participated in the jigsaw activityperformed better than those that didn’t on the 1-weekretention quiz. (Wilkss λ=.97, F(1,218) p = .04)
    24. 24. Results: AchievementResult: No difference between APR and cadaver-only studyon the 1-week retention quiz.
    25. 25. Results: MotivationResult: Students who participated in the jigsaw activity hadhigher motivation* than those who didn’t participate. *F=5.96,P=.01
    26. 26. Results: MotivationResult: Students who studied with APR in lab had lowermotivation* than cadaver-only students. *F=28.83, P<.001
    27. 27. Results: MotivationResult: Results suggest* that the jigsaw activity ameliorateddecreases in motivation observed in the APR group. *Jig x APRInteraction, F = 6.57, p = .01
    28. 28. Results: Task-technology FitResult: Students’ perceptions of task-technology fit wasgreater in jigsaw over individual learning. *Wilkss λ=.95, F(1,213) p < .01
    29. 29. Study #2 – ResultsQualitative (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 indepth.•Iliked this activity because it allows us to work together more andreceive feedback from each other.•I enjoyed teaching the material to others. It makes it so I have tomaster it in order to teach it.•Thegroup activity helped me get more involved and learn differentways to study the material.
    30. 30. ConclusionsJigsaw cooperative learning provides clear advantagesover traditional, individual lab learning methods inanatomy instructionResults suggest that jigsaw cooperative learningameliorates the initial negative effects of introducingnew virtual softwareThe positive effects of cooperative learning pedagogyappear to “spill over” onto students’ perceptions oftechnology
    31. 31. Special ThanksJim Therrell & the Faculty Center for InnovativeTeaching at Central Michigan University
    32. 32. ReferencesAronson, 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, fromhttp://articles.latimes.com/2008/may/26/nation/na-cadavers26Deutsch, 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 learninganatomy 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 theinstruction 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 intothe 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.htmlResnick, M., Berg, R., & Eisenberg, M. (2000). Beyond black boxes: Bringing transparency and aesthetics back to scientific investigation. Journal of the LearningSciences, 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 aunified 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 directexperience at sea. Journal of Research in Science Teaching, 43(1), 25–42.
    33. 33. Image CreditsCoffee - 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 – Boulderassett.colorado.edu | andysaltarelli.com | @ajsalts