Event Title
Meaningful posts and online learning in Blackboard
Location
Terry
Format
Podium Presentation
Start Date
26-1-2013 2:45 PM
End Date
26-1-2013 3:15 PM
Abstract
INTRODUCTION: Ransdell, Kent, Gaillard-Kenney, and Long (2010) have shown that some students, 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. Ransdell (2010) has also shown that students with optimal patterns and types of discussion participation do better than those students who just follow a point system of quantity-based engagement.
PURPOSE: This study was conducted to determine if meaningful posts as tracked in Blackboard would predict online learning.
METHODOLOGY: Students were given three assessments, ALOC, ICI, and TIPI and then monitored for meaningful posts and successful online behavior during an online graduate health science course.
RESULTS: A multiple regression shows that a significant percentage of online learning is predicted by meaningful posts and homework performance while total online activity does not predict learning outcomes.
CONCLUSIONS: Students with more meaningful posts show more engagement with the online materials and better learning than those with less meaningful posts.
Meaningful posts and online learning in Blackboard
Terry
INTRODUCTION: Ransdell, Kent, Gaillard-Kenney, and Long (2010) have shown that some students, 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. Ransdell (2010) has also shown that students with optimal patterns and types of discussion participation do better than those students who just follow a point system of quantity-based engagement.
PURPOSE: This study was conducted to determine if meaningful posts as tracked in Blackboard would predict online learning.
METHODOLOGY: Students were given three assessments, ALOC, ICI, and TIPI and then monitored for meaningful posts and successful online behavior during an online graduate health science course.
RESULTS: A multiple regression shows that a significant percentage of online learning is predicted by meaningful posts and homework performance while total online activity does not predict learning outcomes.
CONCLUSIONS: Students with more meaningful posts show more engagement with the online materials and better learning than those with less meaningful posts.
