by Kadir Kozan 1 Research Problem RationaleSignificanceWhy Conceptual Frameworks Data Collection amp Analysis Validity Limitations 2 Research Problem TP CP SP CL CL cognitive load CP cognitive presence ID: 480772
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Predictive validity of teaching, social and cognitive presence for cognitive load
by Kadir Kozan
1Slide2
Research ProblemRationale/Significance/Why?Conceptual Frameworks
Data Collection & Analysis Validity Limitations
2Slide3
Research Problem
TP
CP
SP
CL
CL: cognitive load; CP: cognitive presence;
SP: Social presence; TP: teaching presence
3Slide4
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?
4Slide5
Perceived learningLearner 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
5Slide6
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?
6Slide7
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
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WHY?
8Slide9
The CoI Framework
9Slide10
CL Theory
10Slide11
Working Memory
11Slide12
Data Collection
Correlational Prediction DesignContext: A fully online LDT program + 4 elective courses
Purposive samplingParticipants: off-campus professionals
Instrumentation:
The CL survey
The CoI survey
Learning satisfaction & Perceived Learning Survey
Demographics Survey
Participants
Instructors
12Slide13
Data Analysis
Differences between the courses/sections: 2-way ANOVASResearch Questions: Standard + Hierarchical Regression
Bonferroni adjustment
p =
.016
Assumptions:
No outliers (IVs & DVs)
No Multicollinearity and Singularity
Normality, Linearity, & Homoscedasticity
Independence of errors
13Slide14
What if an assumption is violated?
14Slide15
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
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Validity
16
Controlling for important variables (LS & PL)
Is this a real CoI?
Temporal precedence
History Effect
Low Temporal validity
CROSS VALIDATIONSlide17
Limitations
Purposive sampling = similar programs onlyLow ecological validity
Elective coursesSubjective rating scalesCorrelational not cause-and-effect
Fixed order of the surveys
17Slide18
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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), 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.
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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.
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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.
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