Generative AI and experiential learning: toward a socially sustainable model of doctoral education in Ghana

Purpose This study examines how doctoral students in Ghana use generative artificial intelligence (GenAI) tools within experiential learning, focusing on their potential to support social sustainability. It explores how GenAI enhances equitable access to research resources, addresses ethical and cultural concerns, and strengthens applied research capacity in doctoral education. Design/methodology/approach A qualitative case study design was adopted. Twenty-one PhD students were purposively sampled, and data were analyzed thematically and through documentary analysis using the lens of social sustainability theory. Findings GenAI supported time savings, improved writing and communication, enhanced conceptual understanding and stimulated creativity. However, subscription fees, limited connectivity, and paywall restrictions hindered equitable access. Ethical concerns included non-disclosure of AI use, risks of overreliance and culturally insensitive AI outputs. Participants also noted GenAI's potential to improve critical thinking, collaborative problem-solving, and capacity building for addressing local educational challenges when guided by institutional policies and culturally responsive practices. Research limitations/implications Given the small, context-specific sample, findings may not generalize across all African doctoral programs. Practical implications Universities should invest in shared AI licenses, improve connectivity infrastructure and embed AI literacy and ethics in doctoral curricula. Social implications Culturally responsive validation protocols and equitable digital access are essential to ensure GenAI supports, rather than undermines, social sustainability in doctoral education. Originality/value This study offers one of the earliest theory-integrated empirical accounts of GenAI integration in doctoral experiential learning within an African context, providing insights into its benefits, risks and contributions to socially sustainable higher education.

Authors

Institutions

Publication Details

Journal
Higher Education Skills and Work-based Learning
Published
2026-05-11
DOI
https://doi.org/10.1108/heswbl-12-2025-0596
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Generative AI and experiential learning: toward a socially sustainable model of doctoral education in Ghana

Kofi Koranteng Adu, Esinam Afi Kayi, Abigail A. Aryeh-Adjei, Monica Mensah Danquah
Higher Education Skills and Work-based Learning
Artificial Intelligence in Healthcare and Education
article

Generative AI and experiential learning: toward a socially sustainable model of doctoral education in Ghana

Kofi Koranteng Adu, Esinam Afi Kayi, Abigail A. Aryeh-Adjei, Monica Mensah Danquah
article en

Abstract

Purpose This study examines how doctoral students in Ghana use generative artificial intelligence (GenAI) tools within experiential learning, focusing on their potential to support social sustainability. It explores how GenAI enhances equitable access to research resources, addresses ethical and cultural concerns, and strengthens applied research capacity in doctoral education. Design/methodology/approach A qualitative case study design was adopted. Twenty-one PhD students were purposively sampled, and data were analyzed thematically and through documentary analysis using the lens of social sustainability theory. Findings GenAI supported time savings, improved writing and communication, enhanced conceptual understanding and stimulated creativity. However, subscription fees, limited connectivity, and paywall restrictions hindered equitable access. Ethical concerns included non-disclosure of AI use, risks of overreliance and culturally insensitive AI outputs. Participants also noted GenAI's potential to improve critical thinking, collaborative problem-solving, and capacity building for addressing local educational challenges when guided by institutional policies and culturally responsive practices. Research limitations/implications Given the small, context-specific sample, findings may not generalize across all African doctoral programs. Practical implications Universities should invest in shared AI licenses, improve connectivity infrastructure and embed AI literacy and ethics in doctoral curricula. Social implications Culturally responsive validation protocols and equitable digital access are essential to ensure GenAI supports, rather than undermines, social sustainability in doctoral education. Originality/value This study offers one of the earliest theory-integrated empirical accounts of GenAI integration in doctoral experiential learning within an African context, providing insights into its benefits, risks and contributions to socially sustainable higher education.

Higher Education Skills and Work-based Learning
University of Education, Winneba (GH), University College of Management Studies (GH), Yangon University Of Distance Education (MM)
Quality Education
Openalex Percentile: Top 8%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.