Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)

<Previous Article In Volume
Next Article In Volume>

Data-Driven Precision Teaching Practice in Blended Learning

Authors
Peizhong Xie1, *, Junjie Jiang1, Xin Wei1
1School of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, 210003, Jiangsu, China
*Corresponding author. Email: cas@njupt.edu.cn
Corresponding Author
Peizhong Xie
Available Online 22 September 2023.
DOI
10.2991/978-94-6463-242-2_24How to use a DOI?
Keywords
blended learning; precision teaching; teaching process; teaching practice
Abstract

The development of new-generation information technology and the gradual promotion of digital education have facilitated the application of precision teaching. Given the widespread promotion of blended learning in institutions of higher learning, this paper explores how professional subject teachers can use information technology teaching platforms to carry out precision teaching practice based on blended learning data. A diagram of the transmission of precision teaching learning data is also provided, which shows a precision teaching process and teaching assessment plan consisting of five stages: pre-course assessment, teaching design, classroom teaching, personalized guidance, and post-course evaluation. Data-driven precision teaching in blended learning can improve learning effectiveness, satisfaction, efficiency, and autonomous learning ability. The conclusion is supported by student survey data and exam results, demonstrating the effectiveness of data-driven precision teaching in blended learning.

Copyright
© 2024 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.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)
Series
Atlantis Highlights in Computer Sciences
Publication Date
22 September 2023
ISBN
978-94-6463-242-2
ISSN
2589-4900
DOI
10.2991/978-94-6463-242-2_24How to use a DOI?
Copyright
© 2024 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.

Cite this article

risenwbib
TY  - CONF
AU  - Peizhong Xie
AU  - Junjie Jiang
AU  - Xin Wei
PY  - 2023
DA  - 2023/09/22
TI  - Data-Driven Precision Teaching Practice in Blended Learning
BT  - Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)
PB  - Atlantis Press
SP  - 198
EP  - 208
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-242-2_24
DO  - 10.2991/978-94-6463-242-2_24
ID  - Xie2023
ER  -