A-Learning Ecosystem for Transformative Adult Education: A Holistic Model

Thesis Abstract

This study addresses the fragmentation of adult learning initiatives within traditional and digital learning milieus by proposing an A-Learning Ecosystem for Transformative Adult Education that integrates cognitive, social, and experiential dimensions to foster holistic professional and personal development. The problemiset centers on limited theoretical coherence and fragmented practice in adult education, which impede transformative outcomes such as critical reflection, agency, and sustained behavioral change across diverse learner contexts. The aim is to develop and validate a holistic A-Learning Ecosystem model that coherently integrates formal, informal, and experiential learning pathways within accessible digital environments to enhance transformative outcomes. Specific objectives are (1) to identify core components and interrelationships of an A-Learning Ecosystem that supports transformative adult education; (2) to examine how indicators of learner agency, self-regulated learning, and critical reflection mediate learning gains; (3) to test the predictive validity of the holistic model across different domains of adult learning (vocational, civic, and community-based education); (4) to assess practitioner readiness and organizational readiness for ecosystem implementation; (5) to develop a validated measurement instrument for ecosystem coherence and transformative learning outcomes. The study adopts a mixed-methods sequential explanatory design anchored in social-constructivist and connectivist theories, drawing explicitly on Mezirow’s Transformative Learning Theory and Siemens’ Connectivism as guiding lenses. The research comprises two phases. Phase I involves the development of the A-Learning Ecosystem Framework through expert elicitation (n=15 senior educators and instructional designers) and a Delphi process to reach consensus on core components, relationships, and metrics. Phase II empirically tests the framework via a multi-site study with a total population of 1,200 adult learners enrolled in continuing education programs across three metropolitan regions, stratified by domain (vocational, civic, and community-based learning). A stratified random sample of 600 learners is invited, with 540 completed responses (response rate 90%). Data collection employs (a) a 42-item Likert-scale Instrument for Ecosystem Coherence (IEC) capturing structural, functional, and relational dimensions; (b) the Transformative Learning Outcomes Scale (TLOS) adapted for adults; (c) measures of learner agency, self-regulated learning, and critical reflection; and (d) semi-structured interviews with 40 learners and 12 instructors to enrich quantitative findings. Quantitative analysis uses confirmatory factor analysis to validate the IEC structure, structural equation modeling (SEM) to test hypothesized pathways from ecosystem coherence to transformative outcomes via learner agency and self-regulated learning (with bootstrapped indirect effects), and multi-group invariance testing to explore domain differences. Regression analyses identify key predictors of transformative outcomes, while ANOVA explores domain-level differences. Qualitative data are analyzed thematically using Braun and Clarke’s framework to illuminate mechanisms of transformation, with triangulation achieved through member checking and cross-method convergence. Validity and reliability procedures include content validity by expert panels, pilot testing (n=60), composite reliability (Cronbach’s alpha > 0.80), and discriminant validity checks. Key expected findings include (i) a robust, empirically validated A-Learning Ecosystem model with high coherence scores (>0.85) and significant paths (p < 0.01) from ecosystem dimensions to transformative outcomes; (ii) learner agency and self-regulated learning mediating the relationship between ecosystem coherence and transformative learning gains, with effect sizes indicating practical significance; (iii) domain-specific variations in effect sizes, with vocational learners showing stronger instrumental transformation and civic/community learners showing greater critical reflection gains; (iv) positive associations between practitioner readiness (instructional design capabilities, digital infrastructure) and learner outcomes, highlighting implementation leverage points. The study contributes to knowledge by operationalizing a holistic, technology-enabled ecosystem theory for adult education and by providing a validated measurement instrument and actionable guidance for policymakers, program designers, and educators. The findings are expected to advance Transformative Learning Theory in digital ecosystems by foregrounding ecosystemic interdependencies and the centrality of learner agency within connectivist-informed practice. Practical recommendations include staged adoption of the ecosystem framework, professional development for instructors in digital pedagogy and reflective facilitation, and investment in interoperable learning platforms that support integrative, cross-domain learning experiences. The conclusion emphasizes that transformative outcomes emerge from coherent, well-supported A-Learning Ecosystems that align instructional design, digital infrastructure, and learner supports with adult learners’ diverse goals and contexts, accompanied by continuous evaluation and adaptation.