A Framework for Enhancing Digital Literacy in Adult Education Contexts

Thesis Abstract

The rapid proliferation of digital technologies has underscored the critical importance of digital literacy for adult learners, particularly within informal and formal education settings, yet many adult education programs in urban and rural contexts continue to face significant challenges in equipping learners with essential digital competencies. This study aims to develop a comprehensive framework to enhance digital literacy among adult learners by identifying key determinants, barriers, and facilitators influencing digital skill acquisition. Specific objectives include examining the current levels of digital literacy among adult learners, exploring contextual factors impacting digital skill development, and constructing a contextually relevant model to guide adult education practitioners in designing effective digital literacy interventions. Employing a sequential mixed-methods research design, the study commenced with a quantitative survey to assess digital literacy levels among a stratified random sample of 450 adult learners enrolled in continuing education centers across metropolitan and peri-urban regions. Data collection instruments included standardized digital literacy assessment tools complemented by a structured questionnaire capturing demographic, psychological, and infrastructural variables. Quantitative data were analyzed using descriptive statistics, correlation analysis, and multiple regression to identify predictors of digital literacy proficiency. The qualitative phase involved semi-structured interviews with 20 adult educators and focus group discussions with 40 adult learners, analyzed through thematic analysis to identify contextual barriers and best practices in digital literacy instruction. The expected findings point to significant disparities in digital literacy levels linked to age, educational background, income, and access to technology, with infrastructural limitations and limited digital pedagogical training acting as prominent barriers. The regression analysis is anticipated to reveal that motivation, self-efficacy, and institutional support are strong predictors of digital skill development. The qualitative analysis is expected to uncover contextual themes such as cultural attitudes towards technology, perceived relevance of digital skills, and institutional constraints that influence adult learners' engagement and progress. Synthesizing these insights, the study aims to propose a theoretically grounded framework, integrating principles from the Technological Pedagogical Content Knowledge (TPACK) model and the Adult Learning Theory (Andragogy), to guide curriculum development, instructional strategies, and policy formulation. This research contributes valuable empirical data and theoretical insights to the field of adult education, addressing the existing gaps concerning context-specific digital literacy development frameworks. It offers a practical and adaptable model that can be implemented by adult educators, policymakers, and stakeholders to systematically enhance digital competencies among diverse adult populations. The anticipated outcomes include a set of actionable recommendations for integrating digital literacy modules into adult education curricula, strategies for capacity building of educators, and infrastructural improvements necessary to support digital inclusion. The study concludes that a coherent, contextually tailored framework rooted in adult learning principles and technology integration models is essential for sustainable enhancement of digital literacy among adults. Recommendations emphasize the importance of collaborative efforts among educational institutions, government agencies, and the private sector to address infrastructural deficiencies, foster digital motivation, and promote equitable access. Further research is suggested to evaluate the implementation and impact of the proposed framework across different adult education settings and demographic groups, ensuring its dynamic refinement and broader applicability.