Transforming Education in the AI Era: A Technology–Organization–Environment Framework Inquiry into Public Discourse

Jinqiao Zhou, Hongfeng Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

The advent of generative artificial intelligence (GAI) technologies has significantly influenced the educational landscape. However, public perceptions and the underlying emotions toward artificial intelligence-generated content (AIGC) applications in education remain complex issues. To address this issue, this study employs LDA network public opinion topic mining and SnowNLP sentiment analysis to comprehensively analyze over 40,000 comments collected from multiple social media platforms in China. Through a detailed analysis of the data, this study examines the distribution of positive and negative emotions and identifies six topics. The study further utilizes visual tools such as word clouds and heatmaps to present the research findings. The results indicate that the emotional polarity across all topics is characterized by a predominance of positive emotions over negative ones. Moreover, an analysis of the keywords across the six topics reveals that each has its own emphasis, yet there are overlaps between them. Therefore, this study, through quantitative methods, also reflects the complex interconnections among the elements within the educational ecosystem. Additionally, this study integrates the six identified topics with the Technology–Organization–Environment (TOE) framework to explore the broad impact of AIGC on education from the perspectives of technology, organization, and environment. This research provides a novel perspective on the emotional attitudes and key concerns of the Chinese public regarding the use of AIGC in education.

Original languageEnglish
Article number3886
JournalApplied Sciences (Switzerland)
Volume15
Issue number7
DOIs
Publication statusPublished - Apr 2025

Keywords

  • AI in education
  • AIGC
  • LDA topic mining
  • SnowNLP sentiment analysis
  • TOE framework
  • public sentiment

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