상세 보기
Deep Learning Suggestions for Analyzing Student Activity Data
- Park, Hyeonghu;
- Lee, Tacklim;
- Cho, Keonhee;
- Jang, Hyeonwoo;
- Park, Sehyun
Citations
WEB OF SCIENCE
8Citations
SCOPUS
0초록
In this study, eight data are collected data. Eight data were obtained through surveys and interviews, and some data were analyzed after being obtained through smart wearable devices. Traditional learning model amount are effectively learned through algorithms with the help of various sensors and Artificial Intelligent. Therefore, this study suggests learning activities based on the deep-learning instruction model as a method for teaching to improve data analytic thinking ability. Models analyze learning activity data design a model of the data through the observation of a given data.
키워드
Learning systems; Artificial intelligent; Data design; Learning Activity; Smart wearables; Traditional learning; Deep learning
- 제목
- Deep Learning Suggestions for Analyzing Student Activity Data
- 저자
- Park, Hyeonghu; Lee, Tacklim; Cho, Keonhee; Jang, Hyeonwoo; Park, Sehyun
- 발행일
- 2020-09
- 유형
- Proceedings Paper
- 저널명
- 2020 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN (ICCE-TAIWAN)
- 언어
- ENG
- 출판사
- IEEE
- 발행국가
- 미국
- ISSN
- P 2381-5779