AI-Enabled Framework for Program and Course Design in Higher Education
DOI:
https://doi.org/10.65655/4w7x4c19Keywords:
artificial intelligence, innovation in higher education, curriculum design, AI-enabled framework, program development, course development, educational technology, technology-enhanced educationAbstract
Background: Artificial intelligence is reshaping higher education, yet most institutions still rely on ad-hoc experiments rather than a holistic, evidence-based strategy for curriculum innovation. Purpose: This study develops and proposes a comprehensive framework that helps universities integrate AI ethically and systematically into program and course design, ensuring alignment with learner needs, labour-market skills, and quality standards. Methods: Employing an integrative secondary research design, we conducted a structured review of peer-reviewed articles, policy documents, and institutional case studies published between 2018 and 2025. Forty high-quality sources passed rigorous screening for relevance, credibility, and methodological soundness. Extracted data were coded thematically and synthesised into recurring practices, enablers, challenges, and ethical considerations, which collectively informed framework construction. Results: AI adoption in curriculum design is global but uneven; leading institutions report gains in student retention, skills alignment, and design efficiency, while lagging peers cite insufficient faculty training, unclear policies, and ethical concerns. Synthesised findings yielded a three-layer framework: (1) program-level guidance that uses AI analytics for outcome formulation, skills mapping, and curriculum sequencing; (2) course-level guidance that positions AI as a co-designer for content generation, adaptive assessment, and personalised feedback; and (3) cross-cutting foundations covering governance, responsible AI use, quality assurance, capacity building, and sustainability. Conclusions: The proposed framework offers a scalable pathway for data-driven, learner-centred, and ethically responsible curriculum innovation. Its adoption can enhance institutional agility and graduate
References
Ateeq, A., Almuraqab, N. A. S., Alfiras, M., Elastal, M., & BinSaeed, R. H. (2025). The impact of adaptive and interactive AI tools on student learning: From digital literacy to advanced skills. International Journal of Innovative Research and Scientific Studies, 8(6), 961–973. https://doi.org/10.53894/ijirss.v8i6.9775
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, 21(4). https://doi.org/10.1186/s41239-023-00436-z
Cardona, M. A., Rodríguez, R. J., & Ishmael, K. (2023). Artificial intelligence and the future of teaching and learning: Insights and recommendations. U.S. Department of Education.https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf
Chen, M. (2025). The impact of AI-assisted personalized learning on student academic achievement. US-China Education Review A, 15(6), 441–450. https://doi.org/10.17265/2161-623X/2025.06.008
Chu, T. S., & Ashraf, M. (2025). Artificial Intelligence in Curriculum Design: A Data-Driven Approach to Higher Education Innovation. Knowledge, 5(3), 14. https://doi.org/10.3390/knowledge5030014
Complete College America (CCA). (2025, July 22). New playbook shares case studies on how colleges can embed AI into curriculum and instruction. Complete College America. https://completecollege.org/news/new-playbook-shares-case-studies-on-how-colleges-can-embed-ai-into-curriculum-and-instruction/
Credential Engine. (n.d.). Credential transparency and AI. Retrieved November 30, 2025, from https://credentialengine.org/credentialtransparency-ai/
Critical Appraisal Skills Programme. (2018). CASP qualitative checklist. CASP. https://casp-uk.net/casp-tools-checklists/
EDUCAUSE. (2023, April 11). EDUCAUSE QuickPoll Results: Adopting and Adapting to Generative AI in Higher Ed Tech. EDUCAUSE Review. https://er.educause.edu/articles/2023/4/educause-quickpoll-results-adopting-and-adapting-to-generative-ai-in-higher-ed-tech
EDUCAUSE. (2024). New survey: More than 70 % of higher-education administrators have a favorable view of AI despite low adoption to-date. https://www.educause.edu/about/corporate-participation/member-press-releases/new-survey-more-than-70-of-higher-education-administrators-have-a-favorable-view-of-ai
European Parliament & Council (EPC). (2016). General Data Protection Regulation (EU) 2016/679. Official Journal of the European Union. https://eur-lex.europa.eu/eli/reg/2016/679/oj
Fang, B. & Broussard, K. (2024, August 7). Augmented course design: Using AI to boost efficiency and expand capacity. EDUCAUSE Review. https://er.educause.edu/articles/2024/8/augmented-course-design-using-ai-to-boost-efficiency-and-expand-capacity
Gilreath, R. (2025, May 7). The use of artificial intelligence (AI) to generate case studies for the classroom. Faculty Focus. https://www.facultyfocus.com/articles/teaching-with-technology-articles/the-use-of-artificial-intelligence-ai-to-generate-case-studies-for-the-classroom/
Gough, D. (2007). Weight of evidence: A framework for the appraisal of the quality and relevance of evidence. Research Papers in Education, 22(2), 213–228. https://doi.org/10.1080/02671520701296189
Huang, A. Y. Q., Lu, O. H. T., & Yang, S. J. H. (2023). Effects of artificial intelligence–enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Computers & Education, 194, 104684. https://doi.org/10.1016/j.compedu.2022.104684
Jia, C., Hew, K. F., Du, J., & Li, L. (2023). Towards a fully online flipped classroom model to support student learning outcomes and engagement: A 2-year design-based study. The Internet and Higher Education, 56, 100878. https://doi.org/10.1016/j.iheduc.2022.100878
Jin, Y., Yan, L., Echeverria, V., Gašević, D., & Martinez-Maldonado, R. (2024, May 20). Generative AI in higher education: A global perspective of institutional adoption policies and guidelines (arXiv:2405.11800v1) [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2405.11800
Jisc. (2023). AI maturity toolkit: A pathway for effective adoption of AI in tertiary education. Jisc. https://www.jisc.ac.uk/news/all/new-toolkit-for-colleges-and-universities-sets-pathway-for-effective-adoption-of-ai
Kassorla, M., Georgieva, M., & Papini, A. (2024, October 17). AI literacy in teaching and learning: A durable framework for higher education [Introduction]. EDUCAUSE. https://www.educause.edu/content/2024/ai-literacy-in-teaching-and-learning/introduction
Liang, J., Stephens, J. M., & Brown, G. T. L. (2025). A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment. Frontiers in Education, 10, Article 1522841. https://doi.org/10.3389/feduc.2025.1522841
Merino-Campos, C. (2025). The impact of artificial intelligence on personalized learning in higher education: A systematic review. Trends in Higher Education, 4(2), 17. https://doi.org/10.3390/higheredu4020017
Mounkoro, I., Khawaji, T., Ocampo, D. M., Cadelina, F. A., Uberas, A. D., Mowafaq, F., Bhardhwaj, B. S., & D. (2024). Artificial intelligence in education: Redefining curriculum design and optimizing learning outcomes through data-driven personalization. Library Progress International, 44(4), 106–126.https://doi.org/10.48165/bapas.2024.44.2.1
Mowreader, A. (2024, September 16). College students uncertain about AI policies in classrooms. Inside Higher Ed. https://www.insidehighered.com/news/student-success/academic-life/2024/09/16/college-students-uncertain-about-ai-policies?utm_source=chatgpt.com
Muncey, N. (2025, May 19). How instructional designers can leverage AI for effective curriculum design. SchoolAI. https://schoolai.com/blog/instructional-designers-leverage-ai-effective-curriculum-design
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
UNESCO. (2025, September 2). UNESCO survey: Two-thirds of higher education institutions have or are developing guidance on AI use. https://www.unesco.org/en/articles/unesco-survey-two-thirds-higher-education-institutions-have-or-are-developing-guidance-ai-use
Sangwa, S., & Mutabazi, P. (2025a). Generative AI and Academic Integrity in Online Distance Learning: The AI-Aware Assessment Policy Index for the Global South. Preprints. https://doi.org/10.20944/preprints202509.2460.v1
Sangwa, S., & Mutabazi, P. (2025b). Mission-Driven Learning Theory: Ordering Knowledge and Competence to Life Mission. Open Journal of Transformative Education & Lifelong Learning (ISSN: 3105-305X), 1(1). https://journals.openchristian.education/index.php/oj-tell/article/view/9
Sangwa, S., Ngobi, D., Ekosse, E., & Mutabazi, P. (2025). AI governance in African higher education: Status, challenges, and a future-proof policy framework. Artificial Intelligence and Education, 1(1), 2054. https://doi.org/10.62617/aie2054
Southworth, J., Migliaccio, K., Glover, J., Glover, J., Reed, D., McCarty, C., Brendemuhl, J., & Thomas, A. (2023). Developing a model for AI across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Computers and Education: Artificial Intelligence, 4, 100127. https://doi.org/10.1016/j.caeai.2023.100127
Strubell, E., Ganesh, A., & McCallum, A. (2019). Energy and Policy Considerations for Deep Learning in NLP. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 3645-3650. https://doi.org/10.18653/v1/P19-1355
Suh, W. (2025). Generative AI integration in higher education shifts students’ attitudes from tool use to innovation. Discov Educ 4, 508. https://doi.org/10.1007/s44217-025-00914-8
Thompson, E. (2023, March 13). White paper by University of Phoenix: Aligning curriculum with labour market through skills mapping. EdTech Innovation Hub. https://www.edtechinnovationhub.com/news/white-paper-uop-aligning-curriculum-with-labour-market
UNESCO. (2025). Survey on generative AI in higher education [Report]. United Nations Educational, Scientific and Cultural Organization. Retrieved March 10, 2025, from https://unesdoc.unesco.org/%E2%80%A6
U.S. Government Publishing Office. (2022, October) Blueprint for an AI Bill of Rights: Making automated systems work for the American people. GovInfo. https://www.govinfo.gov/app/details/GOVPUB-PREX23-PURL-gpo193638
Webb, M. (2025, August 28). A strategic framework for AI in colleges and universities. National Centre for AI (Jisc). https://nationalcentreforai.jiscinvolve.org/wp/2025/08/28/a-strategic-framework-for-ai-in-colleges-and-universities/.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Sixbert SANGWA, Placide MUTABAZI, Jean Bosco Muvunyi (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
