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The impact of artificial intelligence on learner–instructor interaction in online learning

📅 October 25, 2021 👤 Kyoungwon Seo, Joice Tang, Ido Roll et al. 📖 International Journal of Educational Technology in Higher Education 📊 704 citations

🤖 Plain-English Summary

Artificial intelligence (AI) systems offer effective support for online learning and teaching, including personalizing learning for students, automating instructors' routine tasks, and powering adaptive assessments. These findings have implications for the design of AI systems to ensure explainability, human-in-the-loop, and careful data collection and presentation.

🔑 Key Findings

  • However, while the opportunities for AI are promising, the impact of AI systems on the culture of, norms in, and expectations about interactions between students and instructors are still elusive.
  • In online learning, learner-instructor interaction (inter alia, communication, support, and presence) has a profound impact on students' satisfaction and learning outcomes.
  • Thus, identifying how students and instructors perceive the impact of AI systems on their interaction is important to identify any gaps, challenges, or barriers preventing AI systems from achieving their intended potential and risking the safety of these interactions.

💡 Why This Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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📋 Article Details

Category 🤖 Artificial Intelligence
Published Oct 25, 2021
Journal International Journal of Educational Technology in Higher Education
Authors Kyoungwon Seo, Joice Tang, Ido Roll, Sidney Fels, Dongwook Yoon
DOI 10.1186/s41239-021-00292-9
Citations 704
Source OpenAlex

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