Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleAçık Erişim2026Scopus SJRQ1Examining the relationships between artificial intelligence literacy, AI-TPACK, job satisfaction, and well-being among teachers through structural equation modeling
Kayalı, Bünyami; Balat, Şener; Yavuz, Mehmet
This study explores the relationships between teachers' artificial intelligence literacy (AIL), AI-TPACK competencies, job satisfaction, and well-being. Survey data from 350 in-service teachers were analyzed using PLS-SEM to examine how AI-related competencies are associated with professional and psychological outcomes. The findings reveal that AIL strongly predicts AI-specific knowledge, especially AI-TCK, AI-TK, AI-TPCK, and AI-TPK, with a moderate influence on traditional pedagogical knowledge. At the job satisfaction level, AI-TCK and general pedagogical knowledge are positively associated with satisfaction, while AI-TK has a negative relationship. Mediation analyses show that AI competencies influence well-being through job satisfaction. AI-TCK and pedagogical knowledge are positively associated with well-being indirectly through job satisfaction, whereas AI-TK shows a negative indirect association along the same pathway. The study suggests that AI-related competencies are linked to teachers' work-life outcomes, and highlights job satisfaction as the key mediator between AI competence and well-being. Because the design is cross-sectional and self-reported, these relationships are interpreted as associations rather than causal effects. The study advocates for integrating AI in ways that support pedagogical development rather than just technical skills.
- MakaleAçık Erişim2026Scopus SJRQ1The 20-Year Evolution of Distance Education: A Bibliometric and LDA-Based Topic Model Analysis
Yavuz, Mehmet; Balat, Şener; Kayalı, Bünyami; Gülen, Emirhan
Although research on distance education has increased substantially in recent years, comprehensive analyses capturing the overall thematic development of the field remain limited. Modeling studies are necessary to address this gap and to uncover long-term research trends. This study aimed to reveal the trends of research conducted in the field of distance education in the last two decades by using machine learning methodology and bibliometric analysis. The unique aspect of the study was its use of the Latent Dirichlet Allocation (LDA) algorithm, a machine learning method for analysing large-scale data. Within the scope of the study, 54,444 articles in the Web of Science database were analysed. Bibliometric analysis revealed that distance education had gained significant momentum, especially in the post-pandemic period, with a wide range of applications in different disciplines such as education, management, and health. As a result of LDA analysis, 19 thematic topics were identified. Among these, digitalization, artificial intelligence, Web-based learning, and social interaction and collaboration stood out. Time series analysis showed an increasing trend for topics such as artificial intelligence and emergency distance education over the years, with less interest shown in topics such as Web-based learning and program design. The study emphasized that distance education is in a technology-driven transformation process and pointed to areas that will offer new opportunities for researchers. Furthermore, recommendations for decision-makers, such as investments in digital infrastructure, integration of artificial intelligence-based systems, and the establishment of quality standards, also emerged.
- Kitap BölümüYalnız künye2024Assessment, evaluation, and feedback in online education with artificial intelligence-supported tools
Kayali, Bünyami; Balat, Şener
The increasing role of Artificial Intelligence (AI) applications in educational activities is also evident in online education. By providing personalised and adaptive learning experiences and offering support for teachers by tracking student behaviours to make inferences about student success and performance, AI reduces teachers' workload, allowing them to focus more on educational activities. AI applications especially enable the rapid and easy completion of assessment and evaluation activities, which teachers often spend significant time and effort on. Within this scope, AI-supported tools are used in online education activities to perform automatic assessments, provide real-time feedback, and conduct data analysis and performance evaluation activities. In this context, the aim of the study is determined as the examination of measurement, evaluation, and feedback activities in online education with AI-supported tools.
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İncele - MakaleAçık Erişim2023Using Metaverse in Education: Bibliometric and Content Analysis on Applications, Tools and Impacts
Yavuz, Mehmet; Kayali, Bünyami; Balat, Şener
The study aims to investigate the impact of metaverse technologies in the field of education. To achieve this objective, bibliometrics and content analysis were employed. During the study, a total of 178 studies were subjected to bibliometric analysis, while 112 studies specifically focused on education were examined through content analysis. The analysis revealed that most publications were concentrated in 2023 (n=98) and 2022 (n=67). Furthermore, the most frequently employed keywords in these studies included metaverse, virtual reality, augmented reality, education, and artificial intelligence. In terms of country distribution, the highest number of publications originated from China (n=103), followed by South Korea (n=73), India (n=34), and the USA (n=30). On the authorship front, the most prolific contributors were Kim, J., Lee, H., Lee, L. H., and Niyato, D. In the realm of metaverse utilization in education, virtual reality, augmented reality, mixed reality, and extended reality technologies emerged as the most prominent. Additionally, the analysis identified higher education and secondary education as the primary contexts for metaverse application. The recommendations presented in the examined studies were categorized into five groups: To Ensure a Quality Learning Experience, To Improve Student Experience, For Skill Development, To Support Education Activities, and For Material Use. Finally, regarding the limitations of metaverse technology in education, a six-category structure was identified, encompassing Technical Problems, High Cost, Ethical and Safety Concerns, Learning Requirements, Limitations of the Technology Used, and Health Problems.
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İncele - MakaleAçık Erişim2023Scopus SJRQ1Investigation of student experiences with ChatGPT-supported online learning applications in higher education
Kayalı, Bünyami; Yavuz, Mehmet; Balat, Şener; Çalışan, Mücahit
The purpose of this study was to determine university students' experiences with the use of ChatGPT in online courses. The sample consisted of 84 associate degree students from a state university in Turkey. A multi-method approach was used in the study. Although quantitative data were collected using the Chatbot Usability Scale, qualitative data were collected using a semi-structured interview form that we developed. The data were analysed using descriptive and content analysis methods. According to the findings, ChatGPT exhibits advantages such as a user-friendly interface and fast, concise, relevant responses. Moreover, emphasizing its contribution to the learning process, the information provided was sufficient and topic-oriented. The understandability of the chatbot’s functions and the clarity of their communication were emphasized. However, there are disadvantages such as performance issues, frequency of errors and the risk of providing misleading information. Concerns have also been raised about the potential difficulties chatbots may face in ambiguous conversations and providing insufficient information on privacy issues. In conclusion, ChatGPT is recognised as a potentially valuable tool in education based on positive usability impressions; however, more research is needed for its safe use. Implications for practice or policy • Based on positive usability impressions, students and instructors can use ChatGPT to support educational activities. • ChatGPT can promote and enhance students' personalised learning experiences. • ChatGPT can be used in all higher education courses. • Users should be cautious about the accuracy and reliability of the answers provided by ChatGPT. • Decision-makers should take precautions against risks such as privacy, ethics, confidentiality and security that may arise from using artificial intelligence in education.
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