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<p>This study investigates the relationship between AI ethics literacy and students’ self-rated learning competence using AI by developing a comprehensive framework of AI ethics literacy comprising knowledge, attitude, and competence dimensions. Data were collected from 482 college students through an online questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Key findings reveal that: (1) AI ethics knowledge is primarily characterized by four ethical principles: fairness and inclusivity, privacy protection, human-centricity, and responsibility and accountability; (2) AI ethics knowledge positively influences both AI ethics attitude and competence; and (3) AI ethics attitude and competence significantly enhance students’ self-rated learning competence using AI. This research contributes a novel theoretical framework for understanding AI ethics literacy while providing practical insights for cultivating students’ self-rated learning competence using AI.</p>

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A framework for AI ethics literacy: development, validation, and its role in fostering students’ self-rated learning competence

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月30日

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  • Junfeng Yang,
  • Wenyuan Xie,
  • Junjie Ni

摘要

This study investigates the relationship between AI ethics literacy and students’ self-rated learning competence using AI by developing a comprehensive framework of AI ethics literacy comprising knowledge, attitude, and competence dimensions. Data were collected from 482 college students through an online questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Key findings reveal that: (1) AI ethics knowledge is primarily characterized by four ethical principles: fairness and inclusivity, privacy protection, human-centricity, and responsibility and accountability; (2) AI ethics knowledge positively influences both AI ethics attitude and competence; and (3) AI ethics attitude and competence significantly enhance students’ self-rated learning competence using AI. This research contributes a novel theoretical framework for understanding AI ethics literacy while providing practical insights for cultivating students’ self-rated learning competence using AI.