FROM TEACHING PROVIDERS TO KNOWLEDGE ENGINES: TRANSFORMING PRIVATE HIGHER EDUCATION IN ACEH AMID THE ARTIFICIAL INTELLIGENCE REVOLUTION
DOI:
https://doi.org/10.5281/zenodo.21128597Keywords:
Private Higher Education, Artificial Intelligence, Institutional Transformation, Knowledge Economy, Aceh, Educational SustainabilityAbstract
The rapid advancement of Artificial Intelligence (AI) is fundamentally reshaping the global landscape of higher education, challenging established business models and modes of knowledge delivery. In Indonesia, Private Higher Education Institutions (PHEIs) serve a critical role in expanding access, yet they remain structurally vulnerable due to heavy reliance on tuition fees and a prevailing focus on instruction over inquiry. This article examines the existential challenges facing PHEIs, with specific focus on the post‑conflict, resource‑rich but economically constrained context of Aceh. It argues that the traditional model of “teaching factories” is no longer viable in an era where AI democratises information access. Instead, PHEIs must undergo a paradigm shift to become Knowledge Engines: institutions that treat research, faculty development, and community engagement as strategic investments rather than operational costs. Drawing on recent global literature and local contextual analysis, the study proposes a four‑pillar framework comprising problem‑centred local research, faculty empowerment as knowledge producers, integrated curricula, and strategic partnership development. The analysis demonstrates that by leveraging AI not merely for efficiency but to unlock local data and contextual insights, PHEIs can build unique competitive advantages that large public universities cannot easily replicate. This transformation is not only essential for institutional survival but also vital for ensuring that higher education contributes meaningfully to regional development, cultural preservation, and intellectual independence in Aceh and across Indonesia.
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References
Batista, J., Mesquita, A., & Carnaz, G. (2024). Generative AI and higher education: Trends, challenges, and future directions from a systematic literature review. Information, 15(11), 676. https://doi.org/10.3390/info15110676
Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., & Nahavandi, S. (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, Article 4. https://doi.org/10.1186/s41239-023-00426-z
Braun, V., & Clarke, V. (2021). One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative Research in Psychology, 18(3), 328–352. https://doi.org/10.1080/14780887.2020.1769238
Braun, V., & Clarke, V. (2022). Thematic Analysis: A Practical Guide. Sage Publications.
Castro Benavides, L. M., Tamayo Arias, J. A., Arango Serna, M. D., Branch Bedoya, J. W., & Burgos, D. (2020). Digital transformation in higher education institutions: A systematic literature review. Sensors, 20(11), 3291. https://doi.org/10.3390/s20113291
Creswell, J. W., & Poth, C. N. (2018). Qualitative Inquiry and Research Design: Choosing Among Five Approaches (4th ed.). Sage Publications.
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20, Article 22. https://doi.org/10.1186/s41239-023-00392-6
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... & Wright, R. (2023). Opinion paper: "So what if ChatGPT wrote it?" Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Etzkowitz, H., & Zhou, C. (2017). The Triple Helix: University–Industry–Government Innovation and Entrepreneurship (2nd ed.). Routledge.
Hanelt, A., Bohnsack, R., Marz, D., & Antunes Marante, C. (2021). A systematic review of the literature on digital transformation: Insights and implications for strategy and organizational change. Journal of Management Studies, 58(5), 1159–1197. https://doi.org/10.1111/joms.12639
Harrison, H., Birks, M., Franklin, R., & Mills, J. (2017). Case study research: Foundations and methodological orientations. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 18(1), Article 19. https://doi.org/10.17169/fqs-18.1.2655
Hess, T., Matt, C., Benlian, A., & Wiesböck, F. (2016). Options for formulating a digital transformation strategy. MIS Quarterly Executive, 15(2), 123–139.
Holmes, W., & Miao, F. (2023). Guidance for generative AI in education and research. UNESCO Publishing.
Katsamakas, E., Pavlov, O. V., & Saklad, R. (2024). Artificial intelligence and the transformation of higher education institutions: A systems approach. Sustainability, 16(14), 6118. https://doi.org/10.3390/su16146118
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic Inquiry. Sage Publications.
Merriam, S. B., & Tisdell, E. J. (2016). Qualitative Research: A Guide to Design and Implementation (4th ed.). Jossey-Bass.
Mergel, I., Edelmann, N., & Haug, N. (2019). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 36(4), 101385. https://doi.org/10.1016/j.giq.2019.06.002
OECD. (2023). Digital Education Outlook 2023: Towards an Effective Digital Education Ecosystem. OECD Publishing. https://doi.org/10.1787/b14bf9f7-en
Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40–49. https://doi.org/10.1016/j.lrp.2017.06.007
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
Warner, K. S. R., & Wäger, M. (2019). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326–349. https://doi.org/10.1016/j.lrp.2018.12.001
Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage Publications.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16, 39. https://doi.org/10.1186/s41239-019-0171-0
