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Human-AI Collaboration: A Study on Anti-ChatGPT Strategies Employed in Innovative Practical Homework Towards “One-Click-Answer” Issue in AIGC

  • Liu Yiwen,
  • Yang Yahui,
  • Fu Jinrong,
  • Feng Tao,
  • Yin Ting,
  • Xiang Yingxi,
  • Gao Yanxia,
  • Qu Taiguo,
  • Zhang Xian

摘要

ChatGPT as a representative of Artificial Intelligence in Generative Computing (AIGC) has had an impact on higher education. It promotes “human-computer collaboration” in coursework, showing both positive and negative effects. ChatGPT has the potential to provide students with personalized learning support. However, students may become too reliant on these tools and lack independent thinking. Aiming at the above problems, this paper introduces the idea of practical homework resource construction, and provides a series of anti-ChatGPT strategies, which can prevent students ChatGPT’s “one-click answer” from the source. By comparing activities such as teaching effectiveness, questionnaires, and talkback interviews conducted in the pilot course, the data illustrate the effectiveness of the methodology.