by Kadir Kozan 1

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

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

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

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

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

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

WHY? 8

The CoI Framework 9

CL Theory 10

Working Memory 11

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

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

What if an assumption is violated? 14

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

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

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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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), 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), 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), Baddeley, Alan (2003): Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4, 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),

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 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), 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), Gutting, G. (2012, May 17). How reliable are the social sciences? The New York Times. Retrieved from 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),

References Kozan, K., & Richardson, J. (2014). Interrelationships between and among the presences. Internet and Higher Education, 21, 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, 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 ). 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), 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), Sweller, J. (2010). Element interactivity and intrinsic, extraneous and germane cognitive load. Educational Psychology Review, 22, 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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