Ethical AI Use: Understanding Perception of Learning Outcomes and Equity
DOI:
https://doi.org/10.24203/jcv4gx50Keywords:
Artificial Intelligence (AI), learning outcomes, educational equity, and ethical considerationsAbstract
The integration of artificial intelligence (AI) in classrooms has transformed pedagogical and learning practices alike, allowing for greater student academic achievement. However, its ethical implications remain a critical concern, with educational institutions attempting to address (and often circumvent) the use of generative AI in assessment. By analysing existing literature and conducting semi-structured interviews and focus groups discussions with freshmen at a private university in Pakistan, this research qualitatively examines how generative AI tools impact student perceptions and positionality in debates about educational equity, learning outcomes, and ethical engagement with AI. To triangulate the findings, first year students were divided into experimental and control groups, with the former exposed to monthly AI training. Firstly, the findings showed that the use of generative AI, particularly ChatGPT, and subsequent discussions posit AI as both an obstacle and a path to educational equity. Additionally, AI use in universities is negotiated based on one’s positionality, with varying concerns for learning outcomes. There was a difference in trust in AI between the groups, with many vocalising and citing concerns such as algorithmic bias and an uneraseable digital footprint. Moreover, generative AI seems to be positioned differently in ethical understandings, as a personal and institutional ethical problem. This study provides a discussion about the appropriate practices for AI use in education, emphasising the need for clearer guidelines. It also highlights the fast-paced progress of generative AI and how debates and perceptions about these tools are still in their nascent phase.
References
[1] Exponential growth — the science of machine learning & AI. (n.d.). The Science of Machine Learning & AI. https://www.ml-science.com/exponential-growth
[2]Transforming communication through AI innovation. (n.d.). https://www.grammarly.com/ai
[3] Roumeliotis, Konstantinos I.; Tselikas, Nikolaos D. (2023). "ChatGPT and Open-AI Models: A Preliminary Review". Future Internet. 15 (6): 192. doi:10.3390/fi15060192.
[4] ChatGPT and other AI Tools: Implications for teaching and learning. (2024, March 25). Center for Teaching and Learning. https://ctl.prod.acquia.cws.oregonstate.edu/chatgpt-and-other-ai-tools-implications-teaching-and-learning
[5] Without universal AI literacy, AI will fail us. (2022, March 17). World Economic Forum. https://www.weforum.org/stories/2022/03/without-universal-ai-literacy-ai-will-fail-us/
[6] Roshanaei, M., Olivares, H., & Lopez, R. R. (2023). Harnessing AI to Foster equity in Education: Opportunities, challenges, and emerging strategies. Journal of Intelligent Learning Systems and Applications, 15(04), 123–143. https://doi.org/10.4236/jilsa.2023.154009
[7] Chai, F., Ma, J., Wang, Y., Zhu, J., & Han, T. (2024). Grading by AI makes me feel fairer? How different evaluators affect college students’ perception of fairness. Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1221177
[8] Shah, M. (2024, September 19). The deplorable state of Pakistan’s digital divide. Brecorder. https://www.brecorder.com/news/40322876
[9] School, S. L. (2024, June 29). How will AI Impact Racial Disparities in Education? | Stanford Law School. Stanford Law School. https://law.stanford.edu/2024/06/29/how-will-ai-impact-racial-disparities-in-education/
[10] Wu, R., & Yu, Z. (2023). Do AI chatbots improve students learning outcomes? Evidence from a meta‐analysis. British Journal of Educational Technology, 55(1), 10–33. https://doi.org/10.1111/bjet.13334
[11] Alotaibi, N. S., & Alshehri, A. H. (2023). Prospers and Obstacles in Using Artificial Intelligence in Saudi Arabia Higher Education Institutions—The Potential of AI-Based Learning Outcomes. Sustainability, 15(13), 10723. https://doi.org/10.3390/su151310723
[12] Zheng, L., Niu, J., Zhong, L., & Gyasi, J. F. (2021). The effectiveness of artificial intelligence on learning achievement and learning perception: A meta-analysis. Interactive Learning Environments, 31(9), 5650–5664. https://doi.org/10.1080/10494820.2021.2015693
[13] Schiff, D. (2021). Education for AI, not AI for Education: The Role of Education and Ethics in National AI Policy Strategies. International Journal of Artificial Intelligence in Education, 32(3), 527–563. https://doi.org/10.1007/s40593-021-00270-2
[14] Borenstein, J., & Howard, A. (2020). Emerging challenges in AI and the need for AI ethics education. AI And Ethics, 1(1), 61–65. https://doi.org/10.1007/s43681-020-00002-7
[15] Borg, J. S., Sinnott-Armstrong, W., & Conitzer, V. (2024). Moral AI. Penguin Press.
[16] Tang, L., & Su, Y. (2024, March 1). Ethical Implications and Principles of Using Artificial intelligence models in the Classroom: A systematic literature review. https://reunir.unir.net/handle/123456789/16210?show=full
[17] Akgun, S., & Greenhow, C. (2021). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI And Ethics, 2(3), 431–440. https://doi.org/10.1007/s43681-021-00096-7
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