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<p>As artificial intelligence (AI) reshapes educational and technological landscapes, understanding public online discussions may provide valuable insights into how AI and education are perceived, debated, and interpreted. This study investigated public discourse on AI and education by analyzing 49,641 posts and comments from Reddit and the Artificial Intelligence Stack Exchange, revealing how online communities shape perceptions of AI- and education-related sentiment and practices. Using a mixed-methods approach, combining computational grounded theory and qualitative constant comparison analysis, we identified five key themes: (1) AI Augments Teaching for Pedagogical Innovation, (2) Educators Advocating for Ethical AI Practice, (3) Students Develop Thinking Skills for Knowledge Construction, (4) Equipping Students with AI literacy for a Digitally Transformed Future, and (5) Human Connection and Collaboration for Human-AI Synergy in Learning. These findings highlighted social, ethical, and collaborative dimensions, with implications for policy and digital literacy development. We discussed implications for policy, curriculum design, and institutional strategy to ensure responsible and impactful adoption of AI technologies.</p>

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Exploring public discourse on artificial intelligence for teaching and learning: a social-computational mixed-methods analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月1日

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  • Chih-Pu Dai,
  • Nuodi Zhang,
  • Min Liu

摘要

As artificial intelligence (AI) reshapes educational and technological landscapes, understanding public online discussions may provide valuable insights into how AI and education are perceived, debated, and interpreted. This study investigated public discourse on AI and education by analyzing 49,641 posts and comments from Reddit and the Artificial Intelligence Stack Exchange, revealing how online communities shape perceptions of AI- and education-related sentiment and practices. Using a mixed-methods approach, combining computational grounded theory and qualitative constant comparison analysis, we identified five key themes: (1) AI Augments Teaching for Pedagogical Innovation, (2) Educators Advocating for Ethical AI Practice, (3) Students Develop Thinking Skills for Knowledge Construction, (4) Equipping Students with AI literacy for a Digitally Transformed Future, and (5) Human Connection and Collaboration for Human-AI Synergy in Learning. These findings highlighted social, ethical, and collaborative dimensions, with implications for policy and digital literacy development. We discussed implications for policy, curriculum design, and institutional strategy to ensure responsible and impactful adoption of AI technologies.