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<p>The widespread application of artificial intelligence (AI) in mathematics education presents both significant potential and considerable challenges. Understanding public perceptions is crucial for the effective implementation and long-term success of these technologies. This study aims to explore the hot topics and emotional attitudes toward AI in education, identify trends over time, and analyze how these perceptions evolve, using a Python-based tool to collect 2,905 user comments from YouTube. Employing a dynamic model that integrates topic modeling and sentiment analysis through LDA and IPA models, the analysis reveals significant shifts in public sentiment since the introduction of ChatGPT. Initially marked by strong recognition and enthusiasm, sentiments have transitioned to reservations and a cautious approach as practical challenges emerged. The current blend of anticipation and caution reflects technological advancements and ongoing reassessment of future prospects. These findings underscore the dynamic nature of public sentiment and highlight the need for continuous monitoring to guide educational policies and AI development effectively. Insights from this study are vital for educators, policymakers, and developers aiming to align AI educational tools with public expectations and educational standards.</p>

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Temporal dynamics of public engagement and sentiment in AI-Enabled mathematics education from YouTube, Twitter and TikTok comments

  • 期刊论文

  • 发表日期：

    2025年8月23日

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  • Yixin Chen,
  • Yiming Cao,
  • Shunjie Chen,
  • Tommy Tanu Wijiaya

摘要

The widespread application of artificial intelligence (AI) in mathematics education presents both significant potential and considerable challenges. Understanding public perceptions is crucial for the effective implementation and long-term success of these technologies. This study aims to explore the hot topics and emotional attitudes toward AI in education, identify trends over time, and analyze how these perceptions evolve, using a Python-based tool to collect 2,905 user comments from YouTube. Employing a dynamic model that integrates topic modeling and sentiment analysis through LDA and IPA models, the analysis reveals significant shifts in public sentiment since the introduction of ChatGPT. Initially marked by strong recognition and enthusiasm, sentiments have transitioned to reservations and a cautious approach as practical challenges emerged. The current blend of anticipation and caution reflects technological advancements and ongoing reassessment of future prospects. These findings underscore the dynamic nature of public sentiment and highlight the need for continuous monitoring to guide educational policies and AI development effectively. Insights from this study are vital for educators, policymakers, and developers aiming to align AI educational tools with public expectations and educational standards.