学生自评AI能力影响风险认知，能力越低越担心个人学习问题。
Artificial Intelligence Competence of K-12 Students Shapes Their AI Risk Perception: A Co-occurrence Network Analysis
- 通过共现网络分析学生对AI能力与风险的自我评估关系。
- 低能力者关注创造力下降、批判思维缺失等个人风险，高能力者更担忧系统性偏差与作弊。
- 研究建议将AI素养纳入中小学课程，促进公平教育应用。
随着人工智能（AI）日益融入教育，理解学生对AI风险的认知至关重要，以支持负责任且有效的应用。本研究通过对芬兰163名中学生（K-12上层中学阶段）进行共现分析，考察了自评AI能力与风险感知之间的关系。学生报告了在系统性、制度性和个人层面的AI相关担忧。结果表明，自评能力较低的学生更关注个人与学习相关的风险，如创造力减弱、批判性思维缺失及滥用；而能力较高的学生则更关注系统性与制度性风险，如偏见、不准确性和作弊行为。这些差异表明，学生的自评AI能力与其对人工智能教育应用（AIED）中风险与机遇的评估密切相关。研究强调，教育机构需将AI素养纳入课程体系，加强教师指导，并为政策制定提供依据，以实现个性化使用和公平融合。
原文摘要 · Abstract (English)
As artificial intelligence (AI) becomes increasingly integrated into education, understanding how students perceive its risks is essential for supporting responsible and effective adoption. This research aimed to examine the relationships between perceived AI competence and risks among Finnish K-12 upper secondary students (n = 163) by utilizing a co-occurrence analysis. Students reported their self-perceived AI competence and concerns related to AI across systemic, institutional, and personal domains. The findings showed that students with lower competence emphasized personal and learning-related risks, such as reduced creativity, lack of critical thinking, and misuse, whereas higher-competence students focused more on systemic and institutional risks, including bias, inaccuracy, and cheating. These differences suggest that students' self-reported AI competence is related to how they evaluate both the risks and opportunities associated with artificial intelligence in education (AIED). The results of this study highlight the need for educational institutions to incorporate AI literacy into their curricula, provide teacher guidance, and inform policy development to ensure personalized opportunities for utilization and equitable integration of AI into K-12 education.
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