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Short Intervention of Self-study-Videos in a Safety Engineering Learning Arrangement: An Investigation of Effects on Learning Performance and Motivation

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Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management (HCII 2023)

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Abstract

Several publications claim positive effects of learning videos - in addition to indications of increased motivation among learners, studies suggest that learning performance can be increased [13]. With a focus on digital transformation, this paper will consider a self-study-video in the field of university education. The content of the investigated self-study-video is a central model of occupational safety: the design model of protective measures. The presented short intervention was designed as self-study-video based on an existing textbook chapter. Besides the evaluation of design elements, it was investigated which effects learning videos may have on the motivation and learning performance of students learning the design model. Students of the University of Wuppertal were the sample for the intervention. The study population were Safety Engineering students, who visit the lecture “basics of occupational safety”. Ninety students attended all steps of the experiment (treatment group n = 44; textbook-group n = 46). The self-study-video has a significant effect on the increase of knowledge and the video-group seems to be more successful than the textbook-group in the post-test. However, the self-study-video is not as motivating as expected, caused by the design of the self-study-video with a computer-generated voice.

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Acknowledgement

We would like to thank Peer Leske2 for his support in the statistical analysis.

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Correspondence to Julia Waldorf .

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Waldorf, J. et al. (2023). Short Intervention of Self-study-Videos in a Safety Engineering Learning Arrangement: An Investigation of Effects on Learning Performance and Motivation. In: Duffy, V.G. (eds) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. HCII 2023. Lecture Notes in Computer Science, vol 14028. Springer, Cham. https://doi.org/10.1007/978-3-031-35741-1_43

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  • DOI: https://doi.org/10.1007/978-3-031-35741-1_43

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