Complex software training: Harnessing and optimizing video instruction

This article investigates the design and effect of optimized video for statistics instruction. In addition, the use of video reviews to further optimize video instruction is examined. A Demonstration-Based Training (DBT) model was proposed and followed for the construction of the video. The videos were tested in a university-level statistics course. Students were randomly assigned to an experimental condition with demonstration and review videos and control condition with only demonstration videos. Video activity was logged to collect engagement data (coverage and commitment), and a knowledge and performance test were administered. The data showed that the videos were successful at gaining and maintaining the motivation and attention of students. Knowledge scores were moderate and there was no main effect for condition. Regression analysis showed overall coverage and review commitment were predictors for knowledge scores. Performance scores remained high when compared to the previous cohort, however there was a significant positive difference in the current study. There was no main effect for condition on performance scores. The DBT-model and its implementation in the videos was considered successful. In addition, it is suggested that video instruction can play an important role in statistics courses where theory and practice are separated. Proposes a framework for designing Demonstration-Based Training videos.Illustrates the design of videos for theory and practice in statistics education.Investigates and discusses the contribution of review videos for retention.

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