Strategic integration or skill compensation? Understanding GenAI use in online higher education
Jessica Sylvester, Melinda Kulick, Leonidas Maganares, Stella SmithPurpose
This study examines how non-traditional undergraduate students in online higher education environments utilize generative artificial intelligence (GenAI) as a tool to enhance academic engagement, personalize learning and improve productivity.
Design/methodology/approach
Using a quantitative, cross-sectional, correlational design, the study surveyed 491 non-traditional undergraduate students enrolled in online general education courses. Multiple regression analysis was conducted to evaluate how academic performance, skill confidence, technology proficiency and weekly time commitments relate to the frequency of GenAI use. Open-ended survey responses were also thematically analyzed to contextualize quantitative findings and explore student motivations, benefits and concerns.
Findings
Results indicate GenAI use is significantly associated with stronger academic performance and confidence in technology skills. Time constraints and lower academic confidence did not significantly predict use. High-performing and digitally proficient students were more likely to adopt GenAI to deepen understanding, generate ideas and streamline academic tasks. Qualitative responses described GenAI as a supportive thinking partner, while also highlighting ethical concerns around authorship, accuracy and academic integrity.
Research limitations/implications
This study examines GenAI use within a single large online university serving primarily adult, non-traditional learners in a flexible, asynchronous model. Findings should therefore be interpreted as contextually situated rather than broadly generalizable. The cross-sectional design captures adoption at an early stage and does not permit causal inference or analysis of long-term learning outcomes. Reliance on self-reported measures may introduce response bias. Future research should employ longitudinal, multi-institutional and mixed-method designs to examine how GenAI use evolves over time and how institutional context, discipline and learner demographics shape patterns of strategic AI integration.
Practical implications
Findings indicate GenAI adoption in online higher education is most strongly associated with digital confidence and academic motivation rather than remediation. Institutions serving adult and non-traditional learners should therefore embed structured GenAI literacy within curricula, emphasizing ethical use, critical evaluation and academic voice preservation. Faculty should design assignments that promote transparent, reflective engagement with AI tools instead of prohibition-based policies. Institutional leaders must develop coherent, context-sensitive AI frameworks and invest in digital skill development to prevent widening equity gaps as AI becomes normalized within asynchronous, autonomy-driven learning environments.
Social implications
As GenAI becomes integrated into online higher education, its social impact extends beyond productivity to issues of digital agency, equity and access. In adult-serving, asynchronous environments where learners self-manage academic decisions, disparities in digital fluency may amplify existing inequalities. Without intentional institutional support, students with lower technological confidence risk marginalization as AI-enhanced workflows become normative. Promoting inclusive, transparent and ethically guided GenAI integration can strengthen learner agency and participation, particularly among adult and non-traditional students balancing complex external responsibilities. Equitable AI adoption requires investment in digital empowerment alongside clear institutional standards.
Originality/value
This study offers contextually grounded empirical insight into how adult, non-traditional undergraduates in online higher education strategically integrate GenAI into their learning practices. By situating adoption within frameworks of technology acceptance, self-directed learning and digital agency, the findings challenge deficit-based narratives and demonstrate that GenAI use is associated with academic confidence and digital fluency rather than remediation. The study contributes student-centered evidence from an autonomy-driven, asynchronous learning environment and provides theoretically informed guidance for ethical AI integration, digital equity initiatives and future longitudinal research on AI-supported learning.