Mesut Aydemir

The rapid evolution of digital technologies has significantly transformed educational methodologies, particularly in open and distance learning environments. Employing a quantitative, cross-sectional design, the study applies Latent Profile Analysis (LPA) to data collected from 1,045 students enrolled in the open education faculty at Anadolu University, Turkiye. This study investigates the latent profiles of open and distance learners in terms of their learning strategies, focusing on deep and surface learning approaches, and their perceptions of technology acceptance and barriers. Utilizing Latent Profile Analysis (LPA), the research identifies three distinct learner profiles: preservers, prudents, and pioneers. These profiles are characterized by varying levels of intrinsic technology barriers and technology acceptance. The findings reveal significant differences in deep and surface learning strategies among these profiles, with pioneers exhibiting higher technology adoption and deep learning engagement, while preservers show greater resistance to technology and a tendency toward surface learning. The study underscores the importance of understanding these profiles to design adaptive digital learning environments that cater to diverse learner needs. It also highlights the role of psychological, motivational, and contextual factors in shaping technology adoption and learning behaviors. Practical implications include the development of targeted interventions, such as user-friendly platforms for preservers and advanced tools for pioneers, to enhance technology acceptance and promote deep learning strategies. The study enriches digital learning ecosystem discourse by applying Diffusion of Innovations Theory and highlighting the need for personalized, inclusive experiences in open and distance learning.

Background: Generative artificial intelligence (AI) systems can now produce written texts, solve complex problems, and create academic artifacts previously treated as reliable indicators of student learning. This capability undermines the construct validity of output-focused assessment, a challenge especially acute in online and distance learning (ODL) environments where AI agents can complete assessments on students' behalf. Purpose: This paper identifies the distinctly human capacities that educational assessment should prioritize and proposes conceptual principles for an assessment paradigm adequate to cultivating and evaluating those capacities across educational levels and delivery modes. Method: A systematic conceptual review was conducted across ERIC, PsycINFO, Scopus, and Web of Science (November 2022 to March 2026). From 874 initial records, 90 sources (64 journal articles, 17 monographs, 9 policy reports) were selected through a PRISMA-adapted screening process and synthesized using an integrative conceptual approach. Findings: The review identifies four distinctly human capacities resistant to AI replication (contextual judgment, lived-experience originality, dialogic meaning-making, and reflective action under uncertainty) and derives a four-principle assessment framework: processuality, dialogicity, situatedness, and reflexivity. These principles are organized along temporal/contextual and individual/relational axes. Implications: The framework offers assessment designers, particularly in online and technology-enhanced learning contexts, principled foundations for creating tasks that evidence genuine human learning rather than automatable output production. Implications for educational policy, teacher education, equity, and future empirical research are discussed.

We examined the relationships between self-directed learning skills, university belonging, and student engagement in open online and distance learning environments within the framework of Self-Determination Theory. The research was conducted using a correlational survey model. Data were collected from 696 university students enrolled at a large-scale open, online and distance learning institution in Türkiye. We used three instruments measuring self-directed learning skills, university belonging, and student engagement. The data were analyzed using partial least squares structural equation modeling. The findings indicate that university belonging significantly and positively predicts all dimensions of student engagement. While self-control skills, learning skills, and sustaining the desire to learn significantly explain university belonging, metacognitive awareness and ability to identify sources were found to have no significant effect. Furthermore, it was found that university belonging acts as a significant mechanism in the relationships between self-control skills, learning skills, and sustaining the desire to learn, and student engagement. In this open and distance learning context, student engagement was not explained by individual learning skills alone. University belonging may therefore be one mechanism that partly accounts for the association between self-directed learning and academic participation. The study contributes by testing self-directed learning at the level of its dimensions, by identifying university belonging as a mechanism that partly accounts for its association with engagement, and by situating this model in a large-scale open and distance learning setting.

Educational YouTube constitutes a globally accessible, practitioner-produced corpus of structured learning content. Despite learners developing genuine and verifiable competencies through sustained engagement, informal video-based learning remains excluded from formal qualification frameworks, creating a systemic gap between acquired capability and recognized achievement. This paper proposes the AI- Augmented Epistemic Design and Microcredential Derivation (AEDMD) framework, which reconceptualizes educational YouTube content as intentional epistemic design and illustrates how AI-assisted learning outcome extraction can translate that design into formally issued microcredentials. A conceptual synthesis methodology was employed, integrating literature across educational technology, artificial intelligence in education, epistemic design theory, and microcredential policy. A structured database search across ERIC, Scopus, and Web of Science (January 2015–December 2024) returned 634 candidate sources; after duplicate removal and title/abstract screening against explicit inclusion and exclusion criteria, 124 sources were reviewed in full, and 42 were selected for substantive engagement. The AEDMD framework comprises five epistemically grounded stages: (1) multi-modal AI content analysis; (2) learning outcome extraction and epistemic profiling; (3) epistemic level classification using a Bloom-SOLO synthesis; (4) workload calibration and ECTS credit assignment; and (5) open badge microcredential issuance with portfolio integration. A hypothetical illustrative application to a data science YouTube channel conceptually illustrates the framework’s potential applicability. AEDMD advances epistemic design theory as an analytical lens for informal digital learning, provides a theoretically grounded AI pipeline for extracting learning outcomes, and proposes a potentially scalable microcredential issuance pathway for open and distance learning institutions and higher education providers. Implications for platform providers, content creators, and credential policymakers are discussed.

Introduction: While Open and Distance Learning (ODL) expands access, the extent to which assessment modality is associated with psychological barriers for learners with disabilities remains underexplored. Aligned with the United Nations Sustainable Development Goal 4 (SDG 4)—ensuring inclusive and equitable quality education for all—this study contributes evidence on whether assessment design in open and distance systems supports or hinders equitable participation by learners with disabilities. Situated in debates on inclusive and equitable higher education, this study tests a self-regulation account in which test anxiety (TA) predicts academic procrastination (AP), which in turn predicts Grade Point Average (GPA), and examines whether exam environment (EE) moderates these psychological pathways differently for students with and without formally recognized disabilities. Methods: Data were collected via an online questionnaire from 667 undergraduates (118 learners with formally recognized disabilities) in a large-scale distance education system; GPA was obtained from institutional records. Structural equation modelling (SEM) and conditional process (moderated mediation) analyses were employed to test the hypothesized model. Results: AP mediates the negative association between TA and GPA for both disabled and non-disabled learners. For learners with disabilities, EE moderated the procrastination–GPA association: the negative association was stronger in face-to-face settings and weaker in online settings. Discussion: Given the cross-sectional design and self-selection into exam mode, these findings should be interpreted as associations rather than causal effects. Nonetheless, they suggest that carefully designed online assessment may function as an EE that helps reduce environmental frictions that can exacerbate the anxiety–procrastination cycle for some disabled learners, with implications for assessment practice (as a contextual factor) and accessibility and fairness (as contextual concerns) in open and distance higher education.

The chapter investigates the global shortage of qualified teachers, emphasizing the critical role of Sustainable Development Goal (SDG) 4 in ensuring equitable access to quality education. It highlights disparities in teacher qualifications across income levels and regions, with low-income countries facing the greatest challenges due to inadequate training infrastructure, economic constraints, and sociopolitical barriers. The chapter proposes strategies such as enhancing teacher training programs, integrating technology, offering financial incentives, and fostering international cooperation to address these challenges. By aligning policies with SDG 4's targets, the chapter advocates for a sustainable and inclusive approach to improving teacher supply and education quality worldwide.

MOOCs and micro-credentials make high-quality education accessible to people from all backgrounds, leveling the playing field and promoting equitable access to skills and knowledge. These concepts are closely tied to global competitiveness by enabling individuals and economies to rapidly adapt to evolving skill demands, access cutting-edge knowledge, and foster innovation. This chapter aims to incorporate both concepts considering the sections and intersections from a global perspective to shape the future of education and bridge the skills gap. When the term makes it more important than ever to be competitive in a global sense, the chapter emphasizes to be aware of the competencies that the institutions have. Designing the skill-oriented online course contents would be a motivation source within the concept of internationalization. The recommendations for the stakeholders given in the frameworks that triggered the quality assurance, internationalization, and global competitiveness.