1. by Kadir Kozan 1

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

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

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? 4

5. 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) 2 important variables 5

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? 6

7. 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 Hypotheses 7

8. WHY? 8

9. The CoI Framework 9

10. CL Theory 10

11. Working Memory 11

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

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

14. What if an assumption is violated? 14

15. Multicollinearity 15 a p <.01(2-tailed) Kozan & Richardson (2014) Presence Type Teaching Presence Social Presence Cognitive Presence Teaching Presence -.553 a /-.128.826 a /.730 a Social Presence -.663 a /.563 a Cognitive Presence -

16. Validity 16 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 17

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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. 19

20. References Garrison, D. R. (2011). E-learning in the 21 st century: A framework for research and practice (2 nd 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. 20

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. 21

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