Deep Learning Suggestions for Analyzing Student Activity Data

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 Ar...

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Main Authors: Park, Hyeonghu, Lee, Tacklim, Cho, Keonhee, Jang, Hyeonwoo, Park, Sehyun
Format: Conference Proceeding
Language:English
Subjects:
Analytical models
Data analysis
Data models
Data visualization
Deep learning
Education
Intelligent sensors
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Lee, Tacklim
Cho, Keonhee
Jang, Hyeonwoo
Park, Sehyun
description 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.
doi_str_mv 10.1109/ICCE-Taiwan49838.2020.9258065
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subjects Analytical models
Data analysis
Data models
Data visualization
Deep learning
Education
Intelligent sensors
title Deep Learning Suggestions for Analyzing Student Activity Data
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