2014年
Development of a Teaching Material that Can Motivate Students to Learn Control Engineering and Image Processing
2014 IEEE 17TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING (CSE)
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- 開始ページ
- 413
- 終了ページ
- 419
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1109/CSE.2014.104
- 出版者・発行元
- IEEE
The purpose of this study is to develop a teaching material that can motivate students to learn control engineering and image processing. The teaching material is designed based on the ARCS (Attention, Relevance, Confidence and Satisfaction) model, which is widely used in developing teaching materials. A low cost small-scale helicopter, called "AR.Drone", is used as a control object in the teaching material. In the control process, the images captured from the AR.Drone's frontal camera are sent to a control computer via Wi-Fi. The computer, then, detects the target color from the images, and sends the control input from PID controller back to the AR.Drone to track that color. With this teaching material, students can know as much about control engineering and image processing by tuning the parameters using in PID control and image processing, and observing the responses of the AR.Drone.
In order to verify the effectiveness of the proposed teaching material, we allowed first-year technical college students, who know nothing about control engineering and image processing, to take our lecture. Then, we did a questionnaire on their interests in the two techniques after the lecture. The result showed that over 80% of them realized the interest of learning these two techniques.
In order to verify the effectiveness of the proposed teaching material, we allowed first-year technical college students, who know nothing about control engineering and image processing, to take our lecture. Then, we did a questionnaire on their interests in the two techniques after the lecture. The result showed that over 80% of them realized the interest of learning these two techniques.
- リンク情報
- ID情報
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- DOI : 10.1109/CSE.2014.104
- Web of Science ID : WOS:000380512100069