sloan 2011 learning presence
DESCRIPTION
Using Learning Presence to Uncover Self-Regulation in the Community of Inquiry Model. Sloan Online Learning Conference November 2011 Suzanne Hayes, Empire State College SUNY Peter Shea, University at Albany SUNY Sedef Smith, Indiana University of Pennsylvania Jason Vickers, University at Albany SUNYTRANSCRIPT
Using Learning Presence to Uncover Self-Regulation in the
Community of Inquiry Model
Suzanne Hayes, Empire State College*Peter Shea, University at Albany*
Sedef Smith, Indiana University of PennsylvaniaJason Vickers, University at Albany
*State University of New York
Review of Community of Inquiry Model Learning Presence as a new construct to
explain online learner self-regulation LP in collaborative and non-collaborative
activities Using social network analysis to examine LP
patterns among students
Presentation
Community of Inquiry Model (CoI) of Garrison, Anderson & Archer, 2000
Most widely cited theory in study of online learning
Explains what takes place in an online course Based on interaction
Conceptual Framework
Shea & Bidjerano, 2010
What is the CoI Model?
All three elements needed to create a meaningful online learning experience (Garrison, Anderson & Archer, 2000)
* Triggering event* Exploration* Integration* Resolution
Looked to the literature of self-regulated learning (SRL)
Zimmerman’s research (2000, 2001) takes into account individual cognition and social interaction
SRL evident in students who exhibit agency in directing thoughts, emotions, motivations, behaviors and strategies in the service of their learning
What else does a successful online learner contribute ?
Revised CoI model with Learner Presence
Shea & Bidgerano (2010) proposed new CoI element called LP
Based on large scale survey research they found that LP was strongly correlated with SP, TP & CP
Examined two undergraduate courses Looked outside threaded discussions to
examine other learning activities Identified a problem in applying existing CoI
codes to student interaction in a series of small group debate preparation areas
Used Zimmerman and others to develop a LP coding scheme
Study 2: What do students actually do?
Shea, Hayes, Uzuner & Vickers, et al. (In press). Learning presence: additional research on a new conceptual element within the Community of Inquiry (CoI) framework. Internet and Higher Education.
Learning Presence in Preparation Areas versus Discussion Areas
All Prep Areas Debate Discussion0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Avg Student LP - Combined Debate Prep. v. Debate Discussion - Course B
FP
MO
SU
MO
More LP in collaborative areas with group products
FP = Forethought & PlanningMO = MonitoringSU = Strategy Use
Current study
A graduate level required research methods blended course delivered during Fall 2010 term
18 doctoral students divided into teams Each team assigned to lead module on research
method of their choice Teams worked with instructor to select readings,
activities and discussion questions 1 full class discussion and option to select either
video/discussion on field notes or interviewing Reporting today on preliminary LP results
Phase 1: Quantitative Content Analysis
Focused on online discussion transcripts and learning journals from a two-week long course module
Coded all Week 2 discussions and module learning journal for LP
Refined our original LP coding scheme Realigned with Zimmerman’s (2000) three phase
cyclical model of SRL (Planning, Performance and Reflection)
LP: Forethought/Planning Indicators
FP1 Setting goals FP2 Planning FP3 Coordinating, delegating or assigning tasks
LP: Performance Indicators
Strategy Use◦ S1 Seeking/offering
help◦ S2 Recognizing a gap
in knowledge ◦ S3 Reviewing◦ S4 Noting outcome
expectations◦ S5 Seeking/offering
additional information
Monitoring ◦ M1 Checking for
understanding◦ M2 Identifying problems◦ M3 Noting completion of
tasks◦ M4 Evaluating quality of
products or process◦ M5 Monitoring and taking
corrective action◦ M6 Appraising interest or
engagement ◦ M7 Recognizing learning
behaviors of self or group◦ M8 Advocating effort or focus◦ M9 Noting use of strategies
LP: Reflection Indicators Added
R1 Change in thinking R2 Causal attribution of results to personal
or group performance
SNA measures nature of relationships between actors (students) in a network (online discussion or course)
Examines “ties” between participants Represented as a network graph i.e. “who
talks to who” and “how often” Helps us understand
How complete the network is Who is central to the network and who is isn’t Patterns of participation based on certain
characteristics
Phase 2: Social Network Analysis
Generated social network graph combining 3 discussions from Module 6 week 2 using Usenet software
Overlaid student LP measures from QCA
Phase 2: Social Network Analysis
Inter-Rater Reliability for QCA Paired coders practiced to establish baseline IRR Used Holsti’s Coefficient of Reliability (CR) Completed initial coding; Reported Initial IRR Negotiated differences; Reported Negotiated IRR
Coding Initial IRR Negotiation Negotiated IRR
Inter-Rater Reliability for QCA
Holsti’s CR
Module 6 Activity Pre Post
Week 2 Discussion 1 0.73 1.00
Week 2 Discussion 2 0.81 1.00
Week 2 Discussion 3 0.88 1.00
Learning Journal 0.69 1.00
For exploratory research we targeted .70 +
Discussion and Journal LP Compared
Module 6 Week 2
Network Graph: Week 2 Discussions
Students with Highest Discussion LP
Students with Highest Journal LP
Facilitators vs. Non-Facilitators
Occurrences of LP Indicators
Average LP Indicators
Student Facilitators S02, S09, S13, S19 30 7.5
Rest of Class 14 other students 73 5.2
Student facilitators demonstrate higher average LP in discussions
Based on Combined LP in Journals and Discussions in Module 6 Week 2
Facilitator’s Discussion LPRankings byLP Occurrence
S05 8S13 8S09 7S15 6… ….S02 4S19 3
Facilitators’ Journal LPRankings byLP Occurrence
S02 5S05 3S06 3S18 3… ….S09 1S13 1S19 1
Facilitators generally at the center of the network due to strength of connections
Demonstrated higher levels of LP (monitoring and strategy use)
Facilitators appeared to have lower relative LP in learning journals
But some students who appear to be less active in discussion have higher journal LP
Not surprising to find higher levels of monitoring and reflection in journals.
Preliminary Observations
Doctoral students Preliminary data based on one week from
one module Need results from other CoI measures SP,
TP, CP Possible relationship between LP and CP, LP
and TP when instructional activity shifted to learners
Limitations/Future Research
Asking students to take on instructional responsibilities may offer promise in terms of enhancing self-regulation
Preliminary results are consistent with prior research that points to benefits of having students assume facilitator role in discussions (Baran & Correia, 2009; Gilbert & Dabbah, 2005; Seo, 2007)
Implications for Practice
May need to adjust expectations for student facilitators – 3 of their 4 learning journals had lower levels of LP – At what point do students go into overload?
Perhaps activity-based discussions (where students “do” something)* when combined with readings and learning journals may encourage LP.
Implications for Practice
Learning activity design: Make explicit expectations for individual and group use of planning, monitoring, strategy use and reflection
Learning Journals: Ask students to examine their self regulatory processes
Assessment: Incorporate elements of LP into rubrics
Implications for Practice
Baran, E., & Correria, A. (2009). Student-led facilitation strategies in online discussions. Distance Education, 30, 339–361. doi:10.1080/01587910903236510.
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, 87-105. doi: http://dx.doi.org/10.1016/S1096-7516(00)00016-6.
Gilbert, P. & Dabbah, N. (2005). How to structure online discussions for meaningful discourse(2005) British Journal of Educational Technology, 36 (1),5–18
Seo, K. (2007). Utilizing peer moderating in online discussions: Addressing the controversy between teacher moderation and nonmoderation. The American Journal of Distance Education, 21, 21–36. doi:10.1080/08923640701298688.
Shea, P., & Bidjerano, T. (2010). Learning presence: Towards a theory of self-efficacy, self-regulation, and the development of a communities of inquiry in online and blended learning environments. Computers & Education, 55, (4), 1721–1731. doi: http://dx.doi.org/10.1016/j.compedu.2010.07.017Shea, Hayes, Uzuner & Vickers, et al. (In press). Learning presence: additional research on a new conceptual element within the Community of Inquiry (CoI) framework. Internet and Higher Education.
Zimmerman, B. J. (1998). Developing self-fulfilling cycles of academic regulation: An analysis of exemplary instructional models. In D. H. Schunk & B.J. Zimmerman(Eds.), Self-regulated learning: From teaching to self-reflective practice (pp. 1–19). New York: Guilford.
Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13–39). New York: Academic Press.
Zimmernan, B.J. & Schunk, D.H. (2001). Theories of self-regulated learning and academic achievment: An overview and analysis. In B. J. Zimmerman and D.H. Schunk (Eds) Self regulated learning and academic achievement: Theoretical perspectives. (pp.1-36) Mahwah, NJ: Lawrence Erlbaum
Works Cited