EVALUATION OF OPEN AND DISTANCE LEARNER PROFILE IN THE CONTEXT OF LEARNING STRATEGIES: AN ANALYSIS OF THE LATENT PROFILE IN TERMS OF DEEP AND SURFACE LEARNERS
Turkish Online Journal of Distance Education, cilt.27, sa.4, ss.354-370, 2026 (ESCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 27 Sayı: 4
- Basım Tarihi: 2026
- Doi Numarası: 10.17718/tojde.1957084
- Dergi Adı: Turkish Online Journal of Distance Education
- Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, EBSCO Education Source, Education Abstracts, ERIC (Education Resources Information Center), Index Islamicus, Education Source Ultimate (EBSCO)
- Sayfa Sayıları: ss.354-370
- Anahtar Kelimeler: deep learning, diffusion of innovations theory, latent profile analysis, learner profiles, Open and distance learning, surface learning, technology acceptance
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Eskişehir Osmangazi Üniversitesi Adresli: Evet
Özet
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.