doi: 10.18178/ijiet.2018.8.1.1009
Estimating Work Situations from Videos of Practical Training Classes with Assembly Tasks
Kai Okamoto1
,
Koh Kakusho1 ,
Michiya Yamamoto1 ,
Takatsugu Kojima2 ,
Masayuki Murakami3
- 1School of Science and Technology, Kwansei Gakuin University, Sanda, Japan
- 2Faculty of Medicine, Shiga University of Medical Science, Otsu, Japan
- 3Research Center for Multi-Media Education, Kyoto University of Foreign Studies, Kyoto, Japan
Abstract
Our preceding study proposed the possibility of producing video previews that enhance viewer motivations towards assembly work in practical training classes by picking scenes of work situations with good performance from the videos of past classes. In the study, two conceptual attributes for categorizing work situations from the viewpoint of the performance were introduced with reference to previous studies for evaluating productivity of human intellectual work with computers. Based on those two conceptual attributes, our preceding study employed observable features for estimating work situations in the videos and showed that those features seem to reflect the difference of work situations with respect to the conceptual attributes. However, quantitative precision for estimating work situations from those features has not yet been evaluated. Moreover, those observable features are employed without considering whether humans actually pay attention to them. It is also not clear whether videos with work situations sufficient for each of the conceptual attributes actually enhance viewer motivations towards the work. This article clarifies these issues based on our recent experimental results with experimental participants.
Keywords
- Practical training class
- assembly task
- work situation estimation
- observable feature
- physical activity
- mental concentration
How to Cite
Kai Okamoto, Koh Kakusho, Michiya Yamamoto, Takatsugu Kojima, and Masayuki Murakami, "Estimating Work Situations from Videos of Practical Training Classes with Assembly Tasks," International Journal of Information and Education Technology, vol. 8, no. 1, pp. 38-45, 2018. https://doi.org/10.18178/ijiet.2018.8.1.1009
Copyright & License
Copyright © 2018 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).