Learner characteristics predict performance and confidence in e-learning: An analysis of user behavior and self-evaluation

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 records 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 had lower serialist and higher surface processing scores. Learners with higher deep strategy and need for cognition scores were more confident in their learning, whilst the reverse held true 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.