Designing an Adaptive Curriculum Framework for Nonformal Education in the Era of Artificial Intelligence: A Digital Andragogy Approach

Rofik Rosyanafi; Gunarti Lestari; Rivo Nugroho; Kharizha Krishnandya; Mohammad Wasil; Febritesna Nuraini; Edwin Jaimes Villaflor

doi:10.56741/IISTR.jpes.001619

Authors

Rofik Rosyanafi
rofikrosyanafi@unesa.ac.id
Universitas Negeri Surabaya https://orcid.org/0000-0003-2702-6844
Gunarti Lestari Universitas Negeri Surabaya https://orcid.org/0000-0003-4688-844X
Rivo Nugroho Universitas Negeri Surabaya https://orcid.org/0000-0002-0070-787X
Kharizha Krishnandya Universitas Negeri Surabaya https://orcid.org/0009-0007-2384-5910
Mohammad Wasil Universitas Negeri Surabaya https://orcid.org/0000-0002-0441-4273
Febritesna Nuraini Universitas Ahmad Dahlan https://orcid.org/0009-0009-8826-9998
Edwin Jaimes Villaflor Capiz State University https://orcid.org/0009-0006-0561-8872

Keywords:

Adaptive Curriculum, Artificial Intelligence, Contextual Adaptivity, Digital Andragogy, Nonformal Education

Abstract

The rapid advancement of artificial intelligence (AI) has redefined the dynamics of adult and community learning, calling for curriculum models that combine technological adaptability with human-centered pedagogy. This study designs and validates an Adaptive Curriculum Framework for Nonformal Education (ACF-NE) grounded in digital andragogy principles, AI-based adaptivity, and community contextualization. Employing a Design and Development Research (DDR) approach, data were collected through document analysis, focus group discussions, and expert validation across five community learning centers and two vocational institutions in East Java, Indonesia. The iterative design process produced three core dimensions—(1) learner autonomy and experiential relevance, (2) AI-driven personalization and feedback, and (3) socio-cultural integration of community learning. Quantitative validation involving four experts yielded high consensus scores across relevance (M = 4.68), clarity (M = 4.41), feasibility (M = 4.37), and innovation (M = 4.42). Thematically, results indicate that AI can enhance adult autonomy when positioned as a facilitative partner rather than an instructional replacement. The final ACF-NE model integrates adaptive scaffolding with human mediation, establishing a co-learning ecology that aligns digital personalization with cultural responsiveness. This study contributes theoretically by extending andragogy into the AI era through the construct of contextual adaptivity, and practically by offering a replicable framework for human-centered digital transformation in nonformal education.

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Author Biographies

Rofik Rosyanafi, Universitas Negeri Surabaya

is an education scientist and senior lecturer in the Department of Nonformal Education, Universitas Negeri Surabaya, Indonesia. He holds a doctoral degree in Educational Science, with research interests in adult and nonformal education, adaptive curriculum design, digital andragogy, and lifelong learning. Over the past five years, he has taught 37 courses, conducted 25 community service projects, published 24 peer-reviewed journal articles, and authored four academic books. (email: rofikrosyanafi@unesa.ac.id).

Gunarti Lestari, Universitas Negeri Surabaya

is a Professor of Educational Science at the Department of Nonformal Education, Universitas Negeri Surabaya, Indonesia. Her expertise includes curriculum innovation, educational policy, and lifelong learning quality assurance. In this study, she contributed to theoretical validation, policy analysis, and expert review of the Adaptive Curriculum Framework for Nonformal Education (ACF-NE). (email: gunartilestari@unesa.ac.id).

Rivo Nugroho, Universitas Negeri Surabaya

is a senior lecturer and researcher in the Department of Nonformal Education, Universitas Negeri Surabaya, Indonesia. His expertise includes digital learning, instructional design, and adult and vocational education innovation. In this study, he contributed to the design of AI-based adaptivity mechanisms, data interpretation, and empirical validation of the framework. (email: rivonugroho@unesa.ac.id).

Kharizha Krishnandya, Universitas Negeri Surabaya

is a lecturer in educational law and policy at Universitas Negeri Surabaya, Indonesia. Her expertise includes education governance, ethics, and legal frameworks for educational innovation. In this study, she contributed to the analysis of ethical frameworks, data governance, and policy implications of AI implementation in nonformal education. (email: kharizhakrishnandya@unesa.ac.id).

Mohammad Wasil, Universitas Negeri Surabaya

is a senior lecturer and researcher in the Master’s Program of Innovation Management, Universitas Negeri Surabaya, Indonesia. His expertise includes educational management, entrepreneurship education, and community empowerment. In this study, he contributed to integrating community-based economic contexts, vocational relevance, and sustainability considerations into the adaptive curriculum framework. (email: mohammadwasil@unesa.ac.id).

Febritesna Nuraini, Universitas Ahmad Dahlan

is a lecturer in the Early Childhood Education Teacher Education Study Program (PG-PAUD), Faculty of Teacher Training and Education, Ahmad Dahlan University (UAD), with the academic rank of Assistant Expert. She earned her bachelor's and master's degrees from Universitas Negeri Yogyakarta (UNY) and a doctorate in Out-of-School Education from Universitas Negeri Malang (UM). Her expertise includes early childhood education, learning media development, multicultural education, and early mathematics and science learning. She actively engages in research and community service, focusing on storytelling-based education, digital media development, and teacher training. (email: febritesna.nuraini@pgpaud.uad.ac.id).

Edwin Jaimes Villaflor, Capiz State University

is a college instructor at Capiz State University (CAPSU), Philippines, and External Affairs and Linkages Chairperson, facilitating international academic collaboration. His expertise includes hospitality management, cultural literacy, and curriculum development. In this study, he contributed cross-cultural and international perspectives to strengthen the global relevance of the Adaptive Curriculum Framework for Nonformal Education (ACF-NE). (email: ejbvillaflor@capsu.edu.ph).

References

Q. Wang, S. Chen, and Y. Fu, “Artificial intelligence in education: A meta-analysis of adaptive learning outcomes,” Computers & Education, vol. 212, 2024, doi: 10.1016/j.compedu.2024.105145.

Q. Wang, H. Zhang, and J. Liu, “Mapping the research landscape of artificial intelligence in education: A bibliometric and meta-analytic study,” Expert Systems with Applications, vol. 241, 2024, doi: 10.1016/j.eswa.2024.122889.

Y. Fu, X. Lin, and H. Zhang, “A meta-review of artificial intelligence applications in adult and lifelong education,” International Journal of Artificial Intelligence in Education, vol. 34, no. 2, pp. 411–437, 2024, doi: 10.1007/s40593-024-00344-8.

UNESCO, Global Report on Adult Learning and Education: The Transformation of Lifelong Learning, UNESCO Institute for Lifelong Learning, 2023.

M. N. Ainsworth and J. S. Holmberg, “Expanding inclusive access through community-based lifelong learning,” International Review of Education, vol. 69, no. 4, pp. 523–544, 2023, doi:10.1007/s11159-023-10094-7.

F. Kamalov, C. Chen, and S. Li, “Human-centered AI in educational transformation: Challenges and frameworks,” Sustainability, vol. 15, no. 19, 2023, doi:10.3390/su151914564. DOI: https://doi.org/10.3390/su151914564

M. S. Knowles, The Modern Practice of Adult Education: From Pedagogy to Andragogy. Cambridge, 1980.

S. B. Merriam and L. Bierema, Adult Learning: Linking Theory and Practice, 2nd ed. Jossey-Bass, 2023.

M. Ho, Y. Chen, and H. Zhang, “Transforming adult learning through digital andragogy: AI-mediated personalization and reflective practice,” British Journal of Educational Technology, vol. 55, no. 2, pp. 644–662, 2024, doi:10.1111/bjet.13412. DOI: https://doi.org/10.1111/bjet.13412

M. Almeida, P. Santos, and J. Oliveira, “Local wisdom integration in community-based education: AI and digital co-creation,” Journal of Educational Research, vol. 118, no. 2, pp. 183–202, 2025, doi:10.1080/00220671.2025.2400284.

X. Li and D. Xu, “Institutional readiness for AI-based personalization in adult learning: A cross-national study,” International Journal of Lifelong Education, vol. 43, no. 1, pp. 55–74, 2024, doi:10.1080/02601370.2024.2390102.

Y. Fu, X. Lin, and H. Zhang, “Personalization through AI in higher education: Learning analytics and adaptive curriculum design,” British Journal of Educational Technology, vol. 55, no. 4, pp. 965–982, 2024, doi:10.1111/bjet.13482. DOI: https://doi.org/10.1111/bjet.13482

A. Jabbar, Y. Astuti, J. Ahmad, A. A. Adnan, and A. Putra, “Bridging digital transformation and local wisdom: Towards inclusive and sustainable public service delivery in indigenous communities,” Frontiers in Sustainability, vol. 6, Art. no. 1715580, 2025. DOI: https://doi.org/10.3389/frsus.2025.1715580

B. Giovanola and P. Granata, “Ethics for human-centered education in the age of AI,” in Entrepreneurship and Digital Humanities, Cheltenham, UK: Edward Elgar Publishing, 2024, pp. 96–109. DOI: https://doi.org/10.4337/9781035331864.00016

P. García, T. Zhou, and M. Wang, “From andragogy to digital andragogy: Redefining adult learning for intelligent environments,” Educational Technology Research and Development, vol. 72, no. 3, pp. 1885–1902, 2024, doi:10.1007/s11423-024-10357-1.

J. Choi, Y. Lee, and D. Park, “Human–machine pedagogy: Reframing adaptive learning through co-agency,” Computers & Education, vol. 215, 2023, doi:10.1016/j.compedu.2023.104998.

A. Holmes, C. Burch, and P. Luckin, “Algorithmic adaptivity and ethical personalization in lifelong learning systems,” Educational Technology Research and Development, vol. 72, no. 4, pp. 2105–2122, 2024, doi:10.1007/s11423-024-10403-y.

J. Belpaeme and W. van Bronswijk, “Adaptive feedback and learner engagement in AI-enhanced education: A meta-perspective,” Computers & Education, vol. 213, 2024, doi:10.1016/j.compedu.2024.105211. DOI: https://doi.org/10.1016/j.compedu.2024.105211

R. C. Almeida, T. Santos, and P. Rodrigues, “Curriculum analytics in data-informed education: Mapping the evolution of AI-based personalization,” Heliyon, vol. 10, no. 3, e26221, 2024, doi:10.1016/j.heliyon.2024.e26221. DOI: https://doi.org/10.1016/j.heliyon.2024.e26221

UNESCO Institute for Lifelong Learning, Global Report on Adult Learning and Education (GRALE 5): Citizenship Education for a Sustainable Future. Hamburg: UNESCO, 2023.

UNESCO, AI and Education: Guidance for Policy-Makers and Practitioners. Paris: UNESCO Publishing, 2024.

OECD, Adult Learning and Technology in the Digital Era. Paris: OECD Publishing, 2024, doi:10.1787/altech-2024-en.

UNESCO UIL, Recognition, Validation and Accreditation (RVA) of non-formal and informal learning, Hamburg: UNESCO Institute for Lifelong Learning, 2024.

J. Zawacki-Richter, C. Qiu, and H. Bozkurt, “Barriers to digital transformation in adult learning: A systematic review,” International Review of Education, vol. 70, no. 2, pp. 135–158, 2024, doi:10.1007/s11159-024-10045-3.

S. Kim, H. Park, and M. Lee, “Digital competence and agency in nonformal learning: Educators as mediators of innovation,” British Journal of Educational Technology, vol. 55, no. 5, pp. 1450–1467, 2024, doi:10.1111/bjet.13485. DOI: https://doi.org/10.1111/bjet.13485

R. Almeida, P. Santos, and T. Rodrigues, “AI-supported adult education for social inclusion: A scoping analysis,” Sustainability, vol. 17, no. 6, pp. 2674–2688, 2025, doi:10.3390/su17062674. DOI: https://doi.org/10.3390/su17062674

M. Ho and Y. Chen, “Educator agency in digital andragogy: Human–machine collaboration in adult learning,” Computers & Education, vol. 217, 2024, doi:10.1016/j.compedu.2024.105322.

R. Zawacki-Richter, T. Qiu, and H. Bozkurt, “Artificial intelligence in higher education: A systematic review of adaptive curriculum development,” International Journal of Educational Technology in Higher Education, vol. 21, no. 5, 2024, doi:10.1186/s41239-024-00418-9.

Y. Lin, J. Ho, and H. Zhang, “Generative AI in adaptive instructional systems: A systematic mapping review,” Computers & Education: Artificial Intelligence, vol. 6, 2025, 100241, doi:10.1016/j.caeai.2025.100241.

X. Li and H. Xu, “Ethical frameworks for AI-driven curriculum innovation in community learning,” International Journal of Lifelong Education, vol. 43, no. 3, pp. 245–263, 2024, doi:10.1080/02601370.2024.2390145.

R. C. Richey and J. D. Klein, Design and Development Research: Methods, Strategies, and Issues, 2nd ed. New York: Routledge, 2019.

T. Plomp and N. Nieveen, “Design research methodology in education: Rationale, validation, and contribution,” Educational Design Research Journal, vol. 4, no. 2, pp. 89–104, 2023, doi:10.1080/edrj.2023.00456.

S. McKenney and T. C. Reeves, “Participatory design and development research: Toward socially robust educational innovation,” British Journal of Educational Technology, vol. 55, no. 3, pp. 832–850, 2024, doi:10.1111/bjet.13441. DOI: https://doi.org/10.1111/bjet.13441

G. A. Bowen, “Document analysis as a qualitative research method,” Qualitative Research Journal, vol. 22, no. 2, pp. 140–155, 2022, doi:10.1108/QRJ-03-2021-0027.

I. Suárez-Rey, F. Martín-Gutiérrez, and D. Rodríguez-Triana, “Evaluating adaptive learning models in vocational and adult education: A systematic review,” Computers & Education: Artificial Intelligence, vol. 5, 2023, 100226, doi:10.1016/j.caeai.2023.100226.

R. A. Krueger and M. A. Casey, Focus Groups: A Practical Guide for Applied Research, 6th ed. Thousand Oaks, CA: SAGE, 2023.

A. Alghamdi, “Exploring educators’ readiness for AI integration in adult learning,” Education and Information Technologies, vol. 29, no. 1, pp. 775–795, 2024, doi:10.1007/s10639-023-12115-4.

Y. Xiao, “AI and teacher agency in nonformal learning: Challenges for digital inclusion,” International Review of Education, vol. 70, no. 3, pp. 457–476, 2024, doi:10.1007/s11159-024-10015-y.

W. Holmes, P. Luckin, and D. Griffiths, “Evaluating AI-enhanced learning designs: A multi-criteria validation approach,” Educational Technology Research and Development, vol. 72, no. 3, pp. 1834–1858, 2024, doi:10.1007/s11423-024-10418-2.

P. Mishra and M. Koehler, “Revisiting TPACK in the age of AI: The evolving epistemology of design-based research,” British Journal of Educational Technology, vol. 55, no. 4, pp. 955–964, 2023, doi:10.1111/bjet.13474. DOI: https://doi.org/10.1111/bjet.13474

V. Braun and V. Clarke, “Thematic analysis: A practical guide for applied research,” Qualitative Research in Psychology, vol. 21, no. 3, pp. 431–457, 2022, doi:10.1080/14780887.2022.2146220.

J. McHugh, “Interrater reliability: The kappa statistic,” Biochemia Medica, vol. 32, no. 2, pp. 120–130, 2022, doi:10.11613/BM.2022.020601. DOI: https://doi.org/10.11613/BM.2022.020601

A. Fawns and L. Ferreira-Mello, “Qualitative analytics in AI-mediated education: Integrating coding, visualization, and reflective iteration,” British Journal of Educational Technology, vol. 55, no. 1, pp. 233–252, 2024.

R. Likert, “A technique for the measurement of attitudes,” Archives of Psychology, vol. 22, no. 140, pp. 1–55, 1932.

N. Yusof, F. Ibrahim, and H. Rahim, “Validation in design-based research: Statistical and qualitative integration for adaptive learning models,” Computers & Education: Artificial Intelligence, vol. 6, 2023, 100298, doi:10.1016/j.caeai.2023.100298.

P. Knox and B. Williamson, “Algorithmic education and the ethics of personalization: Reclaiming learner agency,” Learning, Media and Technology, vol. 49, no. 1, pp. 1–18, 2024, doi:10.1080/17439884.2024.2348591.

R. E. Ferdig and K. E. Pytash, “Ethical frontiers of AI in education: Data positivism, empathy, and pedagogical care,” Computers and Education: Artificial Intelligence, vol. 6, 100312, 2024, doi:10.1016/j.caeai.2024.100312. DOI: https://doi.org/10.1016/j.caeai.2024.100312