Research and Analysis of Learning Factors Based on the Foundation of Computer Big Data

DOI

10.2991/978-94-6463-192-0_84How to use a DOI?

Keywords

Computer models; Data mining; Higher education research; Data dimensional features

Abstract

In the context of big data from computers, this paper explores Chinese students’ low engagement behaviors in the UK classroom, supported by a foundation of data mining. In detail, it examines some of the current pedagogical reasons taught by Chinese graduate students about silence at the University of Glasgow through the theory of planned behavior. This exploratory study aims to gain a clearer understanding of what causes Chinese students to be silent in UK classrooms. The study also aims to provide innovative strategies for postgraduate lecturers at the University of Glasgow to deal with the silence of Chinese students, even as others teaching Chinese students in the UK encounter the same situation. In this case, it could give more pointed support to better meet the needs of Chinese students. This issue is important because Chinese students’ silence in the classroom is a common phenomenon that has caused some problems for UK educators. This paper applies computerized big data to research that explores factors of student learning, also lays some groundwork for new areas of research with the development of new ways of research.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yiwei Ma
PY  - 2023
DA  - 2023/07/04
TI  - Research and Analysis of Learning Factors Based on the Foundation of Computer Big Data
BT  - Proceedings of the 2023 2nd International Conference on Educational Innovation and Multimedia Technology (EIMT 2023)
PB  - Atlantis Press
SP  - 645
EP  - 650
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-192-0_84
DO  - 10.2991/978-94-6463-192-0_84
ID  - Ma2023
ER  -