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- 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 Erişim2025Scopus SJRQ1The Effects of Artificial Intelligence Supported Flipped Classroom Applications on Learning Experience, Perception, and Artificial Intelligence Literacy in Higher Education
Yavuz, Mehmet; Balat, Sener; Kayali, Bunyami
Rapid changes in the field of technology have greatly affected learning and teaching styles as in every field. Artificial intelligence (AI), which is increasingly used in the field of education for different purposes such as improving learning outcomes or solving teaching problems, is one of the important technologies that contribute to this change. It is thought that there is a need for applications based on AI technology that can meet these needs in terms of sustainability of learning, especially in ODE environments where individual learning and instant feedback are important. Accordingly, the study aims to determine the impact of AI-supported flipped classroom applications on students' AI literacy and to evaluate their experiences and perceptions towards these applications. Explanatory sequential mixed design was used as the method in the study. In this context, in the quantitative phase of the study, a one-group pretest-posttest design from the weak experimental design was used to determine students' perceptions of flipped learning and AI literacy levels. In the qualitative phase of the study, a case study was used to determine students' views on learning experiences. The sample comprised 33 university students enrolled in a Web Design and Coding associate degree program. Data were collected through a flipped learning perception scale, an AI literacy scale, and semi-structured interviews. Quantitative findings revealed a statistically significant improvement in students' AI literacy levels from pre-test to post-test. Qualitative analyses indicated that AI-supported flipped classroom practices positively influenced students' motivation, interest in the course, and personalized learning experiences. Furthermore, the model fostered collaboration by promoting interactive learning environments and enhanced critical thinking and problem-solving skills. However, students also reported challenges related to managing their time effectively within this instructional model. The study concludes that AI-supported flipped classroom applications hold promise for improving AI literacy and fostering active, student-centered learning in higher education. Nevertheless, challenges such as time management warrant further attention. It is recommended that future research explore the implementation of this model across diverse courses and educational contexts, investigate strategies to mitigate time management issues, and conduct comparative studies between AI-supported and traditional flipped classroom models to further elucidate the sources of observed positive perceptions.
AtıfWoS12OpenAlex15
İncele - MakaleAçık Erişim2023Scopus SJRQ2Artificial intelligence literacy teaching in social studies education
Yetişensoy, Okan; Rapoport, Anatoli
The increasing role of artificial intelligence (AI) in daily life has led to the emergence of numerous skill sets associated with AI. AI literacy, which is becoming an important citizenship competence, has become a skill that has gained importance in recent years. It is thought that the aim of social studies to prepare students as active citizens of today and the future has made AI literacy a direct subject of social studies education. However, the literature on the relationship between social studies and AI literacy is still scarce. This study aims to explore the relationship between social studies and AI literacy and to discuss the potential role of social studies in teaching AI literacy. In this direction, the concept of AI is defined, and the teaching of AI literacy in education is examined; the teaching of this literacy within the scope of social studies is discussed, and an example of a hands-on activity-supported lesson plan, which can be used in social studies classes, is presented. This study is important in terms of pointing out the potential role of social studies in AI literacy teaching.
AtıfScopus41OpenAlex57
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