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    Investigating the relationship between social presence and transactional distance in online distance learning environments through structural equation modeling analysis
    (Routledge Journals, Taylor & Francis Ltd, 2025) Yavuz, Mehmet; Kayali, Bunyami; Ustun, Aysin Gaye; Ucar, Hasan; Erdogdu, Erdem; Bozkurt, Aras
    While digitalization has increased flexibility in online distance learning, it has also brought challenges such as emotional strain, interactional issues, and social isolation. In this context, students' sense of social presence is vital for sustaining their well-being and ensuring high-quality interaction. Grounded in Transactional Distance Theory (TDT) and the Community of Inquiry (CoI) framework, this study modeled the relationships between social presence (SP) and interaction types within the using Structural Equation Modeling (SEM). The Social Presence and Transactional Distance Scales were used as data collection instruments. The sample comprised 574 online distance learners, with data collected via an online questionnaire. The results of the SEM analysis showed that SP was a significant positive predictor of all interaction types. Findings show that SP most strongly influences student - student and student - learning environment interactions, while also significantly enhancing student - instructor, student - content, and student - interface interactions. These results indicate that online learning environments should support not only content delivery but also meaningful social interaction. The study highlights the value of SP-oriented design in open, online and distance education systems and offers strategic recommendations for instructors, content developers, and digital learning administrators. Future research should compare synchronous and asynchronous learning structures.
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    Öğe
    SURVEILLANCE OR SUPPORT? A SYSTEMATIC LITERATURE REVIEW OF ARTIFICIAL INTELLIGENCE SUPPORTED PROCTORED ONLINE EXAMS
    (Anadolu Univ, 2026) Ustun, Aysin Gaye; Kayali, Bunyami; Yavuz, Mehmet; Bozkurt, Aras
    Proctored online exams have become widespread, especially after COVID-19, increasing exam security and efficiency. In recent years, artificial intelligence developments have increased these systems' importance by expanding their use. Accordingly, this study aims to provide an in-depth understanding of the conceptual structure of artificial intelligence-supported proctored online examination (AI-SPOE) research. Systematic literature review and text mining were used as methods. Thirty-two studies in Scopus and Web of Science databases were analyzed according to the PRISMA technique. While all the studies were examined in the context of content analysis, abstracts and keywords of the relevant studies were analyzed by text mining. The current study found it effective in increasing academic integrity and exam security, but problems such as privacy violations, exam anxiety, and algorithmic biases were encountered. Although methods such as biometric verification and behaviour analysis successfully detect cheating, technical difficulties, and false positives negatively affect the user experience. In the future, more inclusive designs, transparent algorithms, and alternative evaluation methods are suggested. In conclusion, the study emphasizes the potential of AI-SPOE systems and highlights the importance of ethical and technical improvements.