Leveraging Canvas Data for the Assessment of Students in Online Discussion.

In Term 4 of 2018, the Online Learning course in the School of Education apportioned 30% of the final mark to participation in MyUni discussion boards. The rationale behind this was outlined in the course modules.

“Collaborative Learning is based on the idea that learning occurs as the result of interaction between members of a learning community and that there is an inherent social aspect to constructing new knowledge.”

The students posted over 600 times to the discussion boards with an average of around 12 posts each, creating a large body of content that needed to be assessed. In order to make this more manageable, Associate Professor Ed Palmer enlisted the help of the Learning Analytics team at Learning Enhancement and Innovation. MyUni records data in relation to every facet of a course in approximately 100 separate tables. Discussion data was extracted from the database and used to build a table that showed for each student in discussion;

• Total number of posts,
• Average size of post in bytes (where 7 bytes is roughly equal to 1 word),
• Smallest post in bytes,
• Largest post in bytes,
• First post and
• Last post.

Whilst it was still necessary to read the posts to assess them qualitatively, the data made it easy to see who had been active, how active they had been and when that activity had occurred.

If you plan to grade discussions in the future don’t forget that leveraging the data can reduce the workload involved in assessing students’ contributions.

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