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Ethical Analysis of Ethical Issues and Countermeasures in Education in the Era of Artificial Intelligence

作者:Zhao Xiao Chun

院校:Hengshui University, Hengshui, China

摘要:The integration of artificial intelligence (AI) in education has revolutionized teaching and learning methodologies, offering personalized experiences and efficient resource management. However, this technological advancement has also surfaced a plethora of ethical concerns that necessitate careful consideration. This paper delves into the ethical issues arising from AI applications in education, such as data privacy, algorithmic bias, educational equity, and the evolving role of teachers. Through a comprehensive analysis, we identify the challenges and propose strategic countermeasures to mitigate these ethical dilemmas. Case studies from both domestic and international contexts are employed to illustrate real-world applications and the associated ethical decision-making processes. The paper concludes with a summary of findings, policy recommendations, and an outlook on future research directions, emphasizing the need for a balanced approach that respects both technological innovation and ethical standards in educational AI deployment.

关键词

Artificial Intelligence; Educational Ethics; Data Privacy; Algorithmic Bias; Educational Equity; Teacher Role Evolution

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参考

References

[1] Smith, J. (2023). “The Impact of Artificial Intelligence on Student Privacy in Education.” Journal of Educational Technology, 15(2), 123-145.

[2] Lee, M., & Kim, H. (2022). “Algorithmic Bias in Educational AI Systems: A Case Study.” International Journal of Artificial Intelligence in Education, 10(4), 567-585.

[3] Brown, L. (2021). “Promoting Educational Equity through AI: Challenges and Opportunities.” Educational Research Review, 16, 78-92.

[4] Johnson, A., & Patel, N. (2023). “Teacher Professional Development in the Age of AI: A Review.” Journal of Teacher Education, 34(1), 45-62.

[5] Zhang, Y., & Liu, J. (2022). “Data Privacy Policies in AI-Driven Education: A Comparative Analysis.” Journal of Information Ethics, 31(3), 204-220.

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