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    • Revista IJIMAI
    • 2024
    • vol. 8, nº 5, march 2024
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    • vol. 8, nº 5, march 2024
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    Ethical Implications and Principles of Using Artificial Intelligence Models in the Classroom: A Systematic Literature Review

    Autor: 
    Tang, Lin
    ;
    Su, Yu-Sheng
    Fecha: 
    03/2024
    Palabra clave: 
    artificial intelligence; classroom; education; ethical implications; ethical principles; systematic literature review; IJIMAI
    Revista / editorial: 
    International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)
    Citación: 
    Tang, L. & Su, Y.S. (2024). "Ethical Implications and Principles of Using Artificial Intelligence Models in the Classroom: A Systematic Literature Review", International Journal of Interactive Multimedia and Artificial Intelligence, vol. 8, issue Special issue on Generative Artificial Intelligence in Education, no. 5, pp. 25-36. https://doi.org/10.9781/ijimai.2024.02.010
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/16210
    DOI: 
    https://doi.org/10.9781/ijimai.2024.02.010
    Open Access
    Resumen:
    The increasing use of artificial intelligence (AI) models in the classroom not only brings a large number of benefits, but also has a variety of ethical implications. To provide effective education, it is now necessary to understand the ethical implications of using AI models in the classroom, and the principles for avoiding and addressing these ethical implications. However, existing research on the ethical implications of using AI models in the classroom is rather sparse, and a holistic overview is lacking. Therefore, this study seeks to offer an overview of research on the ethical implications, ethical principles and the future research directions and practices of using AI models in the classroom through a systematic literature review. Out of 1,445 initially identified publications between 2013 and 2023, 32 articles were included for final coding analysis, identified using explicit inclusion and exclusion criteria. The findings revealed five main ethical implications, namely algorithmic bias and discrimination, data privacy leakage, lack of transparency, decreased autonomy, and academic misconduct, with algorithmic bias being the most prominent (i.e., the number of existing studies is the most), followed by privacy leakage, whereas decreased autonomy and academic misconduct were relatively understudied; and six main ethical principles, namely fairness, privacy, transparency, accountability, autonomy and beneficence, with fairness being the most prominent ethical principle (i.e., the number of existing studies is the most), followed by privacy, while autonomy and beneficence were relatively understudied. Future directions of research are given, and guidelines for future practice are provided: (1) further substantive discussion, understanding and solution of ethical implications are required; (2) the precise mechanism of ethical principles of using AI models in the classroom remains to be elucidated and extended to the implementation phase; and (3) the ethical implications of the use of AI models in the classroom require accurate assessment.
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