Use Data for Education
Take Li Deyu’s Self-reported Texts of Two Demotions as an Example
- DOI
- 10.2991/978-94-6463-242-2_36How to use a DOI?
- Keywords
- Education and teaching; Teachers and students; LIWC; Character psychology
- Abstract
In the education and teaching of linguistics, psychology, literature, history and other related fields, teachers and students usually analyze the psychology and image of characters by studying the historical background and the author’s life experience. Given the limited language text data available for analysis and the long longitudinal time span, however, teachers and students cannot establish an objective understanding of the characters’ psychology, nor can they form a good grasp of the characters’ images. As a result, the conclusion concerning character psychology in daily education and teaching reflects a more subjective tendency, which is characterized by the self-subjective analysis of teachers and students. Based on the foregoing content, teachers and students should consider and use some ways to explore the objective psychological characteristics of characters in education and teaching. Consequently, this study takes Li Deyu’s psychological characteristics, a major figure of the “Niu–Li Factional Strife” in the late Tang Dynasty, as an example, based on the language big data and the Classical Chinese version of Linguistic Inquiry and Word Count (CC-LIWC) as research methods, aiming to clarify the significance of this research to relevant education and teaching. To this end, after sorting out the language text data related to the characters, this research utilizes data analysis to explore the psychology of Li Deyu, so as to obtain objective data. Li Deyu, as the leader of the Li faction, had twice served as prime minister and twice been demoted, with his political career full of ups and downs. With Li Deyu’s self-reported texts after his two demotions as the research content, this research encoded them into two distinct groups: Group A and Group B. Meanwhile, the CC-LIWC, an independently-developed program for text analysis, was utilized to conduct a word frequency analysis. Relevant research findings demonstrated that words expressing anger and dissatisfaction were observed to be more prevalent in Li Deyu’s self-reported texts after the second demotion than after the first, the frequency of words conveying sadness decreased after the second demotion. The results indicated that Li Deyu was more inclined to become angry and resentful after the second demotion than the first. It can be seen that during the education and teaching of language, psychology, and other related fields, teachers and students can refer to the research methods in this paper to analyze the psychology and images of the characters, thus leading to more objective and realistic education and teaching methodologies. Furthermore, this research holds significant benefits in nurturing students’ spirit of exploration in diversified aspects, such as using language text data and psycho-semantic dictionaries to quantitatively analyze character psychology and the group culture of a specific era or region comprising multiple characters.
- 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
TY - CONF AU - Qian Wang AU - Tingshao Zhu PY - 2023 DA - 2023/09/22 TI - Use Data for Education BT - Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023) PB - Atlantis Press SP - 287 EP - 300 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-242-2_36 DO - 10.2991/978-94-6463-242-2_36 ID - Wang2023 ER -