The Relationship Between Instructor Socio-Epistemological Orientations and Student

1. The Relationship Between Instructor Socio-Epistemological Orientations and Student Satisfaction with Indicators of the Community of Inquiry Framework Phil Ice Zehra Akyol Randy Garrison 7th Annual Hawaii International Conference on Education

2. Introduction ~ An Overview of the Community of Inquiry Framework Randy Garrison, Ph.D. University of Calgary

3. Background • Studies have emphasized the importance of community as a key factor in successful online/blended learning (Conrad, 2005; Haythornthwaite & Kazmer, 2004; Rovai, 2002). • Sense of community is found to be significantly associated with perceived learning (Shea, 2006; Shea, Li, & Pickett, 2006). • Community of Inquiry Framework provides a well structured guideline to create an effective and sustained learning community (Arbaugh, 2008). • (Garrison, Anderson & Archer, 2000)

4. Community of Inquiry • The importance of a community of inquiry is that, while the objective of critical reflection is intellectual autonomy, in reality, critical reflection is “thoroughly social and communal”. • (Lipman, 1991)

5. Value of a Framework • A theoretical framework takes us beyond craft know how and recipes. • Theoretical frameworks provide order and allow us to understand complex situations in greater depth. • This increases adaptability to new contexts and environments. • Survey instrument consisting of 34 items validated in 2008

6. Community of Inquiry Framework Cognitive Presence The extent to which learners are able to construct and confirm meaning through sustained reflection and discourse in a critical community of inquiry. Social Presence The ability of participants in CMC to project themselves socially and emotionally, as well as the degree to which they feel socially and emotionally connected to others Teaching Presence The design, facilitation and direction of cognitive and social processes for the purpose of realizing personally meaningful and educationally worthwhile learning outcomes.

7. CoI Categories/Indicators

8. Socio-Epistemological Orientations • Social – Group vs. Individual • Epistemological • Objectivist – lower order thought processes vis-à-vis Bloom’s Taxonomy • Constructivist – higher order thought processes vis-à-vis Bloom’s Taxonomy • Student satisfaction and perceptions of Community may be impacted by the instructors Socio-Epistemological orientation – as projected in content and interactivityDirect Instruction • (Arbaugh & Benbunnan-Fich, 2006)

9. The Study and It’s Context ~ Zehra Akyol Middle East Technical University

10. Setting and Coding • American Public University System – fully online institution • Eight undergraduate and eight graduate level courses were coded for epistemological orientations • Lower three levels of Bloom’s coded as objectivist • Higher three levels of Bloom’s coded as constructivist • Coding of all course activities and discussions • Majority of indicators determined classification

11. Sample and Data Collection • CoI Survey administered for six course terms in all sections of courses that were coded • N = 4397 • Undergraduate – 2576 • Graduate – 1821 • Factor Analysis ran: • Overall • By level • By course • By five year age bands • By clusters – defined by school

12. Research Question • Does epistemological orientation influence factor loading patterns? • Are other variables responsible for factor loading patterns? • Impetus – despite validation of the CoI in 2008, a few subsequent factor analyses have produced a two factor solution • Anecdotal evidence – two factor solution appeared among groups where the emphasis was on training as opposed to true knowledge acquistion

13. Findings, Observations And Directions for Future Research ~ Phil Ice, Ed.D. American Public University System

14. Factor Analysis • The following slides represent an expected three factor solution • Produced in the original validation of the CoI survey instrument and the majority of subsequent analyses

18. Findings I • Factor analysis of all courses combined produced a three factor solution • Factor analysis of all undergraduate courses combined produced a three factor solution • Factor analysis of all graduate courses combined produced a three factor solution • Factor analysis of individual courses (n range of 221 - 405) produced a three factor solution • Factor analysis by school produced three factor solutions

19. Findings II • Age banding 18 - 22, 23 - 27, 28 - 32, 33 - 37, 38 - 42, 43 - 47, 48 - 52, 53 - 57, 58 – 62 • Undergraduate maximum age band = 43 – 47 • Graduate minimum age band = 23 – 27

20. Findings III • Factor analysis by age band • 18 - 22 produce a 2 factor solution regardless of epistemological orientation or course level • 23 - 37 produce 3 factor solution regardless of epistemological orientation or course level • 38 - 62 overall produce a 3 factor solution overall • 38 - 47 produce a 2 factor solution when the epistemological orientation is objectivist • 38 - 47 produce a 3 factor solution when the epistemological orientation is contructivist • 48 - 62 produce a 2 factor solution regardless of epistemological orientation or course level

21. Observations • Students between 23 - 37 appear to find ways to collaborate or view learning as a collaborative process regardless of level • Students 18 - 22 appear to view teaching and cognitive presence as the same construct regardless of course orientation • Students 48 - 62 appear to view teaching and cognitive presence as the same construct • Students 38 - 47 appear to be influenced by the epistemological orientation of course materials and activities

22. Future Research I • How does the perception of learning activities differ between students 23 – 27 years old and their peers • Why do students 18 - 22 not transfer native social networking and collaboration skills to learning • How can life skills be used to leverage learning for students 48 - 62 years old • Why is epistemological orientation significant for students 38 - 47 and not other age groupings

23. Future Research II • Multi-institutional data • Substantial qualitative work • Hierarchical linear modeling

24. Thank You! ~ Phil Ice, Ed.D. pice@apus.edu Zehra Akyol zehraakyol@gmail.com Randy Garrison, Ph.D. garrison@ucalgary.ca