Proposal Title

Can Online Threaded Discussions Foster Deep Learning?

Proposal Abstract

This session will first present the results of a two year research study on interaction in online threaded discussions that was assessed using the Community of Inquiry (CoI) framework. The data collected represents postings from over 150 students on over 2000 discussion topics from 10 sections of the same 100% online course, taught by the same faculty member, over a two year period. Data was analyzed using a peer reviewed coding sheet based on the CoI framework. Participants in the study were current students who were enrolled in a 100% online graduate degree program. The study reveals key factors in designing and facilitating threaded discussions that will foster deep learning.

The session will also facilitate a discussion on how to use the CoI framework to assess and enhance the learning associated with online threaded discussions. Finally, an open discussion will be provided where participants can share useful techniques and tools that participants have found to help foster deeper learning in online threaded discussions and begin to examine them using the CoI model.

Session Goals

1) Explain the connection between the CoI framework and deep learning in online threaded Discussions.

2) Discuss the importance of analyzing interaction in online threaded discussions.

3) Review the results of a two year study on interaction in online threaded discussions using the CoI framework.

4) Identify techniques and tools to help improve interaction in online threaded discussions at the colleges and universities represented in the session.

Location

Room 1005

Publication Type and Release Option

Presentation (Open Access)

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Mar 27th, 11:00 AM Mar 27th, 11:45 AM

Can Online Threaded Discussions Foster Deep Learning?

Room 1005

This session will first present the results of a two year research study on interaction in online threaded discussions that was assessed using the Community of Inquiry (CoI) framework. The data collected represents postings from over 150 students on over 2000 discussion topics from 10 sections of the same 100% online course, taught by the same faculty member, over a two year period. Data was analyzed using a peer reviewed coding sheet based on the CoI framework. Participants in the study were current students who were enrolled in a 100% online graduate degree program. The study reveals key factors in designing and facilitating threaded discussions that will foster deep learning.

The session will also facilitate a discussion on how to use the CoI framework to assess and enhance the learning associated with online threaded discussions. Finally, an open discussion will be provided where participants can share useful techniques and tools that participants have found to help foster deeper learning in online threaded discussions and begin to examine them using the CoI model.

Session Goals

1) Explain the connection between the CoI framework and deep learning in online threaded Discussions.

2) Discuss the importance of analyzing interaction in online threaded discussions.

3) Review the results of a two year study on interaction in online threaded discussions using the CoI framework.

4) Identify techniques and tools to help improve interaction in online threaded discussions at the colleges and universities represented in the session.