Cognitive Loads in a Distance Training for Trainee Teachers

Abstract

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One of the persistent problems of online and distance learning is how to effectively support students' successful learning outcomes. A promising approach to this issue is to investigate the extent that learning is determined by learner characteristics and skills. This study explores the effects of domain-specific prior knowledge, intrinsic motivation, computer attitude, computer anxiety, and learning management skills on learning in a distance-training course on media pedagogy for teachers. The data were collected from 127 trainee teachers who responded to various questionnaires and completed knowledge tests. We investigated whether the selected characteristics of learners could be used to model five cognitive load assessments that included ratings of content difficulty, learning ease, experienced pressure/tension, effort/importance while learning, and performance in tests. Computer anxiety and computer attitude were significant predictors of content difficulty, learning ease, and experienced pressure/tension. In addition, higher learning-strategy skills reduced ratings of content difficulty. Effort/Importance ratings were best modeled by intrinsic motivation and learning strategy usage. Performance was best predicted by prior knowledge, intrinsic motivation, and computer attitude.

Keywords

• distance training
• teacher training
• higher education
• self-regulated learning
• computer attitude
• computer anxiety