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Complex software training: Harnessing and optimizing video instruction

机译:复杂的软件培训:利用和优化视频教学

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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 arid 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. (C) 2017 Elsevier Ltd. All rights reserved.
机译:本文研究了用于统计教学的优化视频的设计和效果。此外,还检查了使用视频评论进一步优化视频教学的情况。提出了一个基于演示的训练(DBT)模型,并遵循该模型来构建视频。这些视频在大学一级的统计课程中进行了测试。将学生随机分配到带有演示和复习视频的实验条件下,并仅通过演示视频来复习控制条件。记录视频活动以收集参与度数据(覆盖率和承诺度),并进行知识和性能测试。数据显示,这些视频成功地获得并保持了学生的动力和注意力。知识得分中等,对病情没有主要影响。回归分析表明,总体覆盖率和审查承诺是知识得分的预测指标。与以前的队列相比,绩效得分仍然很高,但是在当前研究中存在显着的积极差异。条件对绩效得分没有主要影响。视频中的DBT模型及其实现被认为是成功的。另外,建议视频教学可以在理论和实践相分离的统计学课程中发挥重要作用。 (C)2017 Elsevier Ltd.保留所有权利。

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