Learner Characteristics predict Performance and Confidence in e-Learning: An Analysis of User Behaviour and Self-evaluation
Debora Jeske, Christian Stamov-Roßnagel, Joy Backhaus, Jacobs University Bremen, Germany
Journal of Interactive Learning Research Volume 25, Number 4, ISSN 1093-023X Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
We examined the role of learner characteristics as predictors of four aspects of e-learning performance, including knowledge test performance, learning confidence, learning efficiency, and navigational effectiveness. We used both self-reports and log file record to compute the relevant statistics. Regression analyses showed that both need for cognition and serialist preference predicted test performance. Participants needed less time to complete the e-module when they also had low serialist preference when learning and had higher use of surface strategies. Learners with higher deep strategy and need for cognition scores were more confident in their learning, whilst the reverse held for learners who scored high on surface strategy use. Also, learners with higher surface strategy use showed less active navigation patterns. Age did not predict any outcome except performance efficiency. The results therefore support the importance of including self-reported learner characteristics and educational background in addition to log file information.
Jeske, D., Stamov-Roßnagel, C. & Backhaus, J. (2014). Learner Characteristics predict Performance and Confidence in e-Learning: An Analysis of User Behaviour and Self-evaluation. Journal of Interactive Learning Research, 25(4), 509-529. Waynesville, NC: Association for the Advancement of Computing in Education (AACE).
© 2014 Association for the Advancement of Computing in Education (AACE)