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Gale Parchoma, University of Saskatchewan

Tracking the development of a learning community: A study of pedagogical strategies for supporting students in engaging in content and forming a learning community. Gale Parchoma, University of Saskatchewan. Research Team.

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Gale Parchoma, University of Saskatchewan

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  1. Tracking the development of a learning community: A study of pedagogical strategies for supporting students in engaging in content and forming a learning community Gale Parchoma, University of Saskatchewan

  2. Research Team • In collaboration with Ben Daniel (Interdisciplinary Studies) and Chris Brooks (Computer Science) • With the support of the LORNET research team in University of Saskatchewan’s ARIES lab.

  3. Purpose of the Study The purpose of this study is to compare student communication patterns across variant pedagogical approaches in order to determine if particular instructional strategies result in similar or different communication patterns. We were looking for evidence of: • Student engagement with content • Evidence of community building / evidence of individuals building social capital within their peer group • Student engagement in course discussions • Quality of postings

  4. Participants 20 students in a 4th year education course. This course is the final required course in the students’ degree program. Much of the course is focused on reflection on internship experiences.

  5. Learning Environment • Blended learning • 3 face-to-face sessions • Everything else online • Blended tools WebCT - Course Content iHelp - Social Negotiation Tools

  6. Pedagogical Approaches:Structure of student activities

  7. Types of Data Collected Qualitative Data: Message Content • Rating system • Each rating was assigned a numerical value • I, as the instructor, rated the quality of each posting • Values used to compare student contributions Quantitative Data: iHelp Sociograms and WebCT student tracking records xxxxx xxxxx

  8. Evidence of student engagement with content…. How often? When ? Data from March 10, 2007. These data sets are not central to the study, but I told students I was gathering them and I used them to encourage students to be engaged with course content.

  9. Data Analysis: Importance We are also interested in the level of influence or importance individual participants have in online environments, and if this changes over time or across pedagogical activities. Importance is somewhat arbitrarily defined as: importance = (# of people who read my postings) (( # of participants + # of lurkers) / total # of postings) We can thus also draw importance power curves.

  10. Instructor’s Intended / Actual Roles Instructor as a moderator The instructor did not actually relinquish importance as soon as planned. Instructor as an observer / facilitator

  11. Giving up on importance

  12. Data Analysis: Frequency & Importance Evidence of student engagement with peer & instructor discussion postings: Over time and across pedagogical approaches Tracking the formation of a learning community. At first, the instructor ensured all postings were read and answered. The instructor relinquished “importance” to student moderators in module 3-1. There are 20 students + 1 instructor in this class. The system is tracking 30 users. bbbbbbbbbbbb Red dots outside the white inner circle, indicate researchers and system administrators rather than students 1 student is not participating

  13. Data Analysis: Quality Scores are normalized each week via adding up each student’s total and then dividing each student’s total by the highest total for that week.

  14. Reading iHelp sociograms. Note that pseudonyms are used. The bigger the font, the greater the quality of the participant’s postings. The sharp-edged lines that connect participants are longer when the participants have fewer connections with other members of the community (i.e., They only ‘talk” with a few others). No line means no one responded to a posting. In the “donut,” the closer the student’s position to the inner black circle, the more postings that student has read. Those whose pseudonyms appear on the black circle, read everything. Student leaders are color-coded.

  15. Student engagement in the communityNote that pseudonyms are used. Week 2 Role Play Week 7 Debate

  16. Results: Weeks 2 and 9 (Role Play) Week 2 Role Play Week 9 Role Play

  17. “Lurkers” – Who is reading how much? We have not yet “done the math,” but we suspect there may be a correlation between high levels of lurking and creating high quality postings.

  18. Results: Weeks 3 & 7Debates Week 3 Week 7

  19. Weeks 4, 5, & 8: Issue Analysis Week 4 Week 5 Week 8

  20. Weeks 10 and 11: Case Studies Week 10 Week 11

  21. Preliminary Findings • I, as the instructor, retained “importance” and influence over class • discussions longer than originally planned. • When I relinquished influence, the learning community among • students immediately began to flourish. • Role plays resulted in lesser connected communities with much more equality among student in terms of the amount of participation from each participant and more equitable quality across postings. • Debates resulted in the most closely connected communities, with strong central leadership by a few participants and notable polarity in the quality of postings. Issue analyses were similar but less pronounced in these effects. • Case studies resulted in patterns of communications among students that were less discernable than role plays, debates, and issues analyses (i.e., somewhere in between the two stronger contrasts).

  22. Thank-you for your consideration of our presentation. Gale Parchoma University of Saskatchewan Saskatoon, SK. Canada

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