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<p>With the development of artificial intelligence technology, it has become increasingly difficult to distinguish between Artificial Intelligence Generated Content (AIGC) and non-AIGC. Inaccuracies in identifying AIGC in higher education may lead to academic misconduct and risks, and the credibility of AIGC is also subject to certain doubts. Users are the direct perceivers of AIGC, and winning their trust is the goal of AI applications. Therefore, exploring the credibility of AIGC holds positive value in higher education. This study designed three specific tasks and collected data from students majoring in educational technology at a normal university through questionnaires. The findings indicate that students only have a 70% success rate in identifying AIGC, and the recognition rate for domain-specific AIGC content may be even worse, with only 60%. Finding also indicated that perceived technological acceptance is the primary factor influencing AIGC credibility and behavioral adoption. Students may also experience AI illusions during AIGC usage, leading to overreliance. This research provides reliable evidence for assessing AIGC credibility in higher education, enhancing students' cognition and application abilities regarding AIGC, and offering insights into promoting effective use of AIGC.</p>

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Can student accurately identify artificial intelligence generated content? an exploration of AIGC credibility from user perspective in education

  • 期刊论文

  • 发表日期：

    2025年2月26日

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  • Yulu Cui,
  • Hai Zhang

摘要

With the development of artificial intelligence technology, it has become increasingly difficult to distinguish between Artificial Intelligence Generated Content (AIGC) and non-AIGC. Inaccuracies in identifying AIGC in higher education may lead to academic misconduct and risks, and the credibility of AIGC is also subject to certain doubts. Users are the direct perceivers of AIGC, and winning their trust is the goal of AI applications. Therefore, exploring the credibility of AIGC holds positive value in higher education. This study designed three specific tasks and collected data from students majoring in educational technology at a normal university through questionnaires. The findings indicate that students only have a 70% success rate in identifying AIGC, and the recognition rate for domain-specific AIGC content may be even worse, with only 60%. Finding also indicated that perceived technological acceptance is the primary factor influencing AIGC credibility and behavioral adoption. Students may also experience AI illusions during AIGC usage, leading to overreliance. This research provides reliable evidence for assessing AIGC credibility in higher education, enhancing students' cognition and application abilities regarding AIGC, and offering insights into promoting effective use of AIGC.