Abstract
4 Rounds (4R) training method is practiced in industrial office site for reducing accidents caused by human factors. The 4R method enables to raise hazard-prediction capability of worker such as coping, decision-making to avoid danger situation. The workers as trainees train on their own by finding hazards which lurked in the hazard prediction training (KYT in Japanese) sheet. However, there is a large problem that a single trainee cannot train oneself using 4R method because the training of 4R method needs instruction of expert as human instructor. To solve that problem, we aim to develop hazard prediction training system. The advantage of this system enables trainee to train oneself anytime/anywhere using 4R method. In this research paper, we reports about our proposal of training system, the development of subsystem which based on machine learning to evaluate trainee's answer correct or not, and reports the result of evaluation experimental that showed the average accuracy was 63.0±22.9 [%].
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 283-286 |
| Number of pages | 4 |
| ISBN (Print) | 9781479999583 |
| DOIs | |
| Publication status | Published - Jan 6 2016 |
| Event | 4th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2015 - Okayama, Japan Duration: Jul 12 2015 → Jul 16 2015 |
Other
| Other | 4th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2015 |
|---|---|
| Country | Japan |
| City | Okayama |
| Period | 7/12/15 → 7/16/15 |
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Keywords
- e-learning
- machine learning
- natural language processing
- training
ASJC Scopus subject areas
- Information Systems
- Computer Networks and Communications
- Computer Science Applications
- Computer Vision and Pattern Recognition
Cite this
Automatic Evaluation Methods of Trainee's Answers to Develop a 4R Risk Prediction Training System. / Minowa, Hirotsugu; Fujimoto, Hiromi; Takeuchi, Koichi.
Proceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015. Institute of Electrical and Electronics Engineers Inc., 2016. p. 283-286 7373916.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Automatic Evaluation Methods of Trainee's Answers to Develop a 4R Risk Prediction Training System
AU - Minowa, Hirotsugu
AU - Fujimoto, Hiromi
AU - Takeuchi, Koichi
PY - 2016/1/6
Y1 - 2016/1/6
N2 - 4 Rounds (4R) training method is practiced in industrial office site for reducing accidents caused by human factors. The 4R method enables to raise hazard-prediction capability of worker such as coping, decision-making to avoid danger situation. The workers as trainees train on their own by finding hazards which lurked in the hazard prediction training (KYT in Japanese) sheet. However, there is a large problem that a single trainee cannot train oneself using 4R method because the training of 4R method needs instruction of expert as human instructor. To solve that problem, we aim to develop hazard prediction training system. The advantage of this system enables trainee to train oneself anytime/anywhere using 4R method. In this research paper, we reports about our proposal of training system, the development of subsystem which based on machine learning to evaluate trainee's answer correct or not, and reports the result of evaluation experimental that showed the average accuracy was 63.0±22.9 [%].
AB - 4 Rounds (4R) training method is practiced in industrial office site for reducing accidents caused by human factors. The 4R method enables to raise hazard-prediction capability of worker such as coping, decision-making to avoid danger situation. The workers as trainees train on their own by finding hazards which lurked in the hazard prediction training (KYT in Japanese) sheet. However, there is a large problem that a single trainee cannot train oneself using 4R method because the training of 4R method needs instruction of expert as human instructor. To solve that problem, we aim to develop hazard prediction training system. The advantage of this system enables trainee to train oneself anytime/anywhere using 4R method. In this research paper, we reports about our proposal of training system, the development of subsystem which based on machine learning to evaluate trainee's answer correct or not, and reports the result of evaluation experimental that showed the average accuracy was 63.0±22.9 [%].
KW - e-learning
KW - machine learning
KW - natural language processing
KW - training
UR - http://www.scopus.com/inward/record.url?scp=84964403681&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84964403681&partnerID=8YFLogxK
U2 - 10.1109/IIAI-AAI.2015.301
DO - 10.1109/IIAI-AAI.2015.301
M3 - Conference contribution
AN - SCOPUS:84964403681
SN - 9781479999583
SP - 283
EP - 286
BT - Proceedings - 2015 IIAI 4th International Congress on Advanced Applied Informatics, IIAI-AAI 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -