Future AIHEd research should give greater attention to ethics, methodological rigour, context, and interdisciplinary collaboration¶

Strategy · All strategies
Evidence · 1 claim (1 for) · 1 study (1 review), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

The review's forward-looking recommendation is that future AIHEd primary and secondary research address the gaps it identified: "a need for greater ethical, methodological, and contextual considerations within future research, alongside interdisciplinary approaches to AIHEd application". Concretely, this includes reporting inter-rater reliability, providing full search strings and coding schemes, undertaking quality assessment, reflecting on limitations, and extending interdisciplinary collaboration beyond the field's current domestic-only, STEM-skewed authorship. Suggestions are provided to guide both future primary and secondary research.

Design Implications¶

Context¶

Requirements¶

• Review teams able to adopt systematic synthesis guidance (e.g., PRISMA) and report methods in complete detail for trustworthiness and replicability

Constraints¶

• The recommendation arises from a corpus published 2018 to July 2023 that excluded generative-AI reviews, non-English publications, and informal learning settings

Target Learners¶

• higher education students
• AIHEd researchers and review teams

Target Learning Goals¶

• improving the ethical and methodological quality of AI applications and evidence synthesis in higher education

Claims¶

• Most reviews reporting neurophysiological AI use stressed the need for further ethical considerations, including participant consent and transparent development [+W]

Related Strategies¶

• Prioritize real-world testing of AI tools in university settings, environmental impact measurement, and integrated ethical-sustainability policies
• Prioritise equity-centred approaches, methodological diversity, contextual specificity, implementation science and interdisciplinary collaboration in GenAI research
• Future shared story reading research should extend to nonfiction texts, inclusive settings, and include practicality statements
• Future team-learning change research should use mixed methods with more than three measurement points in short intervals

Examples¶

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Key Sources¶

• Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Pham, P., Chong, S. W. & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: a call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-023-00436-z