Predictive validity of teaching, social and cognitive presence for cognitive load

1. Predictive validity of teaching, social and cognitive presence for cognitive load by Kadir Kozan

2. Research Problem • Rationale/Significance/Why? • Conceptual Frameworks • Data Collection & Analysis • Validity • Limitations

3. Research Problem TP CP CL SP CL: cognitive load; CP: cognitive presence; SP: Social presence; TP: teaching presence

4. Research Questions • How well TP, CP and SP predict intrinsic/extraneous / germane CL at the end of a fully online learning experience? • What presence is the best predictor of intrinsic/extraneous/ germane CL at the end of a fully online learning experience: social presence, teaching presence, and cognitive presence?

5. 2 important variables • Perceived learning • Learner satisfaction • These relate to both each other and the presences (e.g., Akyol & Garrison, 2008; Arbaugh, 2008; Fredericksen, Pickett, Shea, Pelz and Swan, 2000; Richardson & Swan, 2003; Shea, Li, Swan & Pickett, 2005)

6. Can the presences still predict intrinsic/extraneous/ germane CL significantly at the end of a fully online learning experience after controlling for learner satisfaction and perceived learning? • What presence is the best predictor of intrinsic/ extraneous /germane cognitive load at the end of a fully online learning experience after controlling for learner satisfaction and perceived learning?

7. Hypotheses At the end of a fully online learning experience: • TP + CP + SP CL (Hypothesis 1). • (TP + CP + SP ) – LS CL (Hypothesis 2). • (TP + CP + SP ) – PL CL (Hypothesis 3). • (TP + CP + SP) – (LS + PL) CL

8. WHY?

9. The CoI Framework

10. CL Theory

11. Working Memory

12. Data Collection • Correlational Prediction Design • Context: A fully online LDT program + 4 elective courses • Purposive sampling • Participants: off-campus professionals • Instrumentation: • The CL survey • The CoI survey • Learning satisfaction & Perceived Learning Survey • Demographics Survey • Participants • Instructors

13. Data Analysis • Differences between the courses/sections: 2-way ANOVAS • Research Questions: Standard + Hierarchical Regression • Bonferroni adjustment p = .016 • Assumptions: • No outliers (IVs & DVs) • No Multicollinearity and Singularity • Normality, Linearity, & Homoscedasticity • Independence of errors

14. What if an assumption is violated?

15. Multicollinearity a p < .01(2-tailed) Kozan & Richardson (2014)

16. Validity • Controlling for important variables (LS & PL) • Is this a real CoI? • Temporal precedence • History Effect • Low Temporal validity • CROSS VALIDATION

17. Limitations • Purposive sampling = similar programs only • Low ecological validity • Elective courses • Subjective rating scales • Correlational not cause-and-effect • Fixed order of the surveys

19. References Akyol, Z., & Garrison, D. R. (2008). The development of a community of inquiry over time in an online course: Understanding the progression and integration of social, cognitive and teaching presence. Journal of Asynchronous Learning Networks, 12(3-4), 3-22. Arbaugh, J. B. (2008). Does the community of inquiry framework predict outcomes in online MBA courses? International Review of Research in Open and Distance Learning, 9(2), 1-21. Arbaugh, B., Cleveland-Innes, M., Diaz, S., Ice, P., Garrison, D. R., Richardson, J. C., & Shea, P., & Swan, K. (2008). Developing a community of inquiry instrument: Testing a measure of the Community of Inquiry Framework using a multi-institutional sample. The Internet and Higher Education, 11(3-4), 133-136. Baddeley, Alan (2003): Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4, 829-839. Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: SAGE Publications. Fredericksen, E., Pickett, A., Shea, P., Pelz, W., & Swan, K. (2000). Student satisfaction and perceived learning with online courses: principles and examples from the SUNY learning network. Journal of Asynchronous Learning Networks, 4(2), 7-41.

20. References Garrison, D. R. (2011). E-learning in the 21st century: A framework for research and practice (2nd ed.) [Kindle Fire version]. Retrieved from http://www.amazon.com Garrison, D. R. (2013). Theoretical foundations and epistemological insights of the community of inquiry. In Z. Akyol & D. R. Garrison (Eds.), Educational communities of inquiry: Theoretical framework, research, and practice (pp. 1-11). Hershey, PA: IGI Global. Garrison, D. R., Anderson, T., Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. The Internet and Higher Education, 2(2-3), 87-105. Garrison, D. R., Anderson, T., Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. The American Journal of Distance Education, 15(1), 7-23. Gutting, G. (2012, May 17). How reliable are the social sciences? The New York Times. Retrieved from http://opinionator.blogs.nytimes.com/2012/05/17/how-reliable- are-the-social-sciences/?smid=fb-share Kalyuga, S. (2011). Cognitive load theory: How many types of load does it really need? Educational Psychology Review, 23(1), 1-19.

21. References Kozan, K., & Richardson, J. (2014). Interrelationships between and among the presences. Internet and Higher Education, 21, 68-73. Leppink, J., Paas, F., van Gog, T., van der Vleuten, C. P. M, & van Merriënboer, J. J. G. (2014). Effects of pairs of problems and examples on task performance and different types of cognitive load. Learning and Instruction, 30, 32-42. Matthews, D., Bogle, L., Boles, E., Day, S., & Swan, K. (2013).Developing communities of inquiry in online courses: A design-based approach. In Z. Akyol& D. R. Garrison (Eds.), Educational communities of inquiry: Theoretical framework, research, and practice (pp. 490-508). Hershey, PA: IGI Global. Richardson, J. C., & Swan, K. (2003). Examining social presence in online courses in relation to students` perceived learning and satisfaction. Journal of Asynchronous Learning Networks, 7(1), 68-88. Shea, P., Li, C. S., Swan, K., Pickett, A. (2005). Developing learning community in online asynchronous college courses: The role of teaching presence. Journal of Asynchronous Learning Networks, 9(4), 59-82. Sweller, J. (2010). Element interactivity and intrinsic, extraneous and germane cognitive load. Educational Psychology Review, 22, 123-138. Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. New York: Springer. Tabachnick, B. G. & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Boston: Pearson.