Meaningful posts and online learning in Blackboard across four cohorts of adult learners

  • Authors:
  • Sarah Ransdell

  • Affiliations:
  • -

  • Venue:
  • Computers in Human Behavior
  • Year:
  • 2013

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Abstract

In the present study, meaningful posts were tracked in Blackboard in a longitudinal study of a graduate statistics course in order to predict online learning. In previous research by the present author, digital immigrants from a baby-boomer cohort fare better than digital natives due to social reliance and meaningful posts. Meaningful posts include discussion comments that reflect meaning-based engagement with the course material. Students with optimal patterns and types of discussion participation do better than those students who just follow a point system of quantity-based engagement. Students were given three behavioral assessments and then monitored for meaningful posts and successful online behavior using the tracking features within Blackboard. Results were analyzed using a multiple regression and showed that a significant percentage of online learning is predicted by meaningful posts and homework performance while total online activity does not uniquely predict learning outcomes. Students with more meaningful posts show more engagement with the online materials and better learning than those with less meaningful posts.