Publisher Home ↗ editor@randspublications.org
International Journal of Social Sciences, Language and Linguistics eISSN 2051-686X Submit Article
Research Articles Open access

Beyond Pedagogy: AI-Enabled Heutagogical Transformation in Fiji and Pacific Tertiary Education

Published
Pages 25-33
Views 107
Downloads 95

Authors

  • Davendra Sharma Lecturer and PhD Scholar University of Fiji, Fiji Islands Author

DOI

https://doi.org/10.55640/ijssll-06-03-03 ↗

Abstract

The rapid advancement of Artificial Intelligence (AI) is reshaping higher education globally, compelling tertiary institutions to reconsider traditional pedagogical models that prioritize content transmission over learner capability. In the context of Fiji and the broader Pacific region, where higher education systems face unique challenges related to geographic dispersion, resource constraints, digital inequities, and postcolonial educational legacies, the integration of AI presents both transformative opportunities and critical responsibilities. This paper argues that the meaningful adoption of AI in Pacific tertiary education requires a paradigmatic shift from pedagogy to heutagogy, emphasizing self-determined learning, learner autonomy, adaptability, and capability development.

Drawing on contemporary scholarship in heutagogy, digital transformation, and AI in education, the paper develops a conceptual framework positioning AI as an enabler of learner agency rather than a replacement for human educators. It examines how AI-driven tools, such as adaptive learning systems, intelligent tutoring, research assistants, learning analytics, and simulation platforms, can support personalized learning pathways, reflective practice, and double-loop learning. Within a Pacific context, this transformation is further situated within the region’s cultural emphasis on relationality, community knowledge, and collective responsibility, highlighting the importance of human-centred, ethically grounded AI integration.

The paper critically discusses opportunities, including expanded access to learning, enhanced research productivity, and innovation capacity, while also addressing challenges such as algorithmic bias, data sovereignty, digital divides, and academic integrity. It argues that sustainable AI-enabled transformation in Fiji and Pacific tertiary institutions must prioritize ethical governance, digital literacy development, culturally responsive pedagogies, and strong human oversight.

Ultimately, this study positions AI not as a technological disruption to be managed, but as a strategic catalyst for reimagining tertiary education in the Pacific, moving beyond pedagogy toward a heutagogical model that fosters lifelong learning, resilience, and capability in an era of uncertainty.

Keywords

Artificial Intelligence , Heutagogy , Tertiary Education , Fiji , Pacific Higher Education , Learner Autonomy , Digital Transformation , Capability Development , Human-Centred AI , Educational Reform

Downloads

Download data is not yet available.

References

1. Blaschke, L. M. (2012). Heutagogy and lifelong learning: A review of heutagogical practice and self-determined learning. The International Review of Research in Open and Distributed Learning, 13(1), 56–71.

2. Blaschke, L. M., & Hase, S. (2019). Heutagogy and digital media networks: Setting students on the path to lifelong learning. Pacific Journal of Technology Enhanced Learning, 1(1), 1–14.

3. Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510

4. Fiji Ministry of Education. (2020). Education sector strategic plan 2020–2030. Suva: Government of Fiji.

5. Hase, S. (2016). Self-determined learning and AI: Supporting learners’ capability. International Journal of Educational Technology, 13(2), 45–58.

6. Hase, S., & Kenyon, C. (2000). From andragogy to heutagogy. UltiBASE Articles. Retrieved from https://www.ultibase.rmit.edu.au

7. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Boston: Center for Curriculum Redesign.

8. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.

9. McCowan, T. (2020). Higher education in small states and remote regions: Challenges and prospects. Higher Education Policy, 33(2), 259–276. https://doi.org/10.1057/s41307-019-00147-x

10. OECD. (2019). OECD learning compass 2030. OECD Publishing. https://doi.org/10.1787/9789264313546-en

11. Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.

12. Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380–1400. https://doi.org/10.1177/0002764213498851

13. Tsai, Y. S., Poquet, O., Gašević, D., Dawson, S., & Pardo, A. (2021). Complexity leadership in learning analytics: Drivers, challenges, and opportunities. British Journal of Educational Technology, 52(5), 1970–1987. https://doi.org/10.1111/bjet.13103

14. UNESCO. (2021). AI and education: Guidance for policy-makers. UNESCO Publishing. https://unesdoc.unesco.org/ark:/48223/pf0000376703

15. Williamson, B., & Piattoeva, N. (2020). Education governance and datafication: Implications for ethics and equity. Learning, Media and Technology, 45(3), 245–261. https://doi.org/10.1080/17439884.2020.1772304

16. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0

Explore related research

Similar Articles

51-60 of 158
Continue exploring

Most read articles by the same author(s)

1 2 3 4 > >> 

Search the journal

Find articles by title, author or keyword.