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    The effect of AI-powered chatbots in social studies education
    (Springer, 2024) Yetisensoy, Okan; Karaduman, Hidir
    The aim of this research is to investigate the educational potential of AI-powered chatbots in Social Studies learning-teaching processes. The study was conducted using embedded design, evaluated within the framework of mixed methods research. The study group consists of 78 6th-grade students studying in three different classes, along with one teacher who implemented the practices and guided the process. During the experimental phase of the study, lessons in the experimental group were taught by the practitioner teacher using an AI-powered chatbot named SosyalciBot. Meanwhile, lessons in two control groups were taught following the constructivist approach. At the end of the process, it was determined that the experimental group students' post-test and permanency test scores were significantly higher than the control group students' scores in both post-test and permanency test. In the semi-structured interviews, both students and the practitioner teacher provided positive evaluations of the pedagogical and design features of the chatbot, indicating that these features positively impacted the learning-teaching process. They also identified some shortcomings while offering suggestions for improvement. Based on the study findings, it is evident that chatbots have a high potential to contribute to Social Studies education. However, to fully harness this potential and achieve optimal effectiveness, further advancements and refinements in chatbot technology are required. At this point, it is recommended to conduct theoretical or applied studies focusing on developing chatbots with high communication capacity and explore innovative and constructive ideas regarding the integration of chatbots into educational environments.
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    Exploring the transformative power of GenAI in education: an exploratory journey from social studies classes
    (Springer, 2025) Yetisensoy, Okan
    The potential of GenAI in educational settings has attracted considerable attention, yet practical explorations of its use in K-12 classrooms are still scarce. This research aims to explore the role of GenAI models in social studies, focusing on their influence on learning-teaching processes and understanding of AI. While exploring the influence of GenAI on pedagogical aspects from the perspective of the teacher and students, this qualitative study also embraces AI as a cross-curricular theme and seeks to understand how GenAI-supported teaching activities shape students' AI understanding. The study group of this research, conducted according to the basic qualitative research design, consisted of 21 middle school students studying in one class and a social studies teacher who implemented the practices. The primary data collection tool for the research was semi-structured interview forms. In the relevant research, a teaching framework supported by GenAI, combining Teaching with AI and Teaching about AI was developed. During the four-week process, the practitioner teacher covered the curricular outcomes using lesson plans designed in alignment with this framework. In the semi-structured interviews, students stated that engaging in activities supported by GenAI not only made the learning process more effective and interesting but also enhanced their understanding regarding AI. The teacher highlighted that GenAI models encouraged constructivist learning environments, ensured the active involvement of all students, including those in inclusive education, and contributed to AI learning through their engaging structure. Additionally, the teacher highlighted technology's drawbacks, including encouraging dependence on convenience and potentially providing inaccurate information. The relevant findings of the study, serving as first observations, are expected to provide valuable insights for future research. At this point, it is recommended that further studies be conducted to explore the transformative potential of GenAI in education, especially by employing experimental designs. An additional suggestion, on the other hand, is to disseminate AI throughout the entire curriculum of all subjects within a specific educational level as a cross-curricular theme, as opposed to limiting its teaching to merely a singular, isolated subject area.
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    Investigation of the Relationship between Social Studies Teacher Candidate's Unemployment Worries and Their Attitudes toward Teaching Profession
    (Hacettepe Univ, 2020) Yetisensoy, Okan; Sahin, Ibrahim Fevzi
    This study aims to determine the levels of unemployment worries of social studies teacher candidates and 15.03.2019 their attitudes towards the teaching profession in terms of various variables and to investigate the relationship between their unemployment worries and their attitudes toward teaching profession. This study was Accepted: conducted in accordance with the relational screening model. As a result of the study, it was found that social 24.07.2019 studies teacher candidates' attitudes towards teaching profession differed significantly in favour of female teacher candidates, low-grade teacher candidates and teacher candidates with higher GPA. Also, it was found Online First: that social studies teacher candidates' unemployment worries were significantly higher in 4th grade teacher 26.07.2019 candidates but did not differ significantly by gender and GPA variables. In addition, the findings of the study showed that there were significant negative relationships between the sub-dimensions of unemployment Published: worries and attitudes towards teaching profession and there was a negative, medium level significant 31.07.2020 relationship between teacher candidates' general unemployment worries and their attitudes towards teaching profession. Moreover, it was determined that unemployment worries of the 4th grade social studies teacher candidates were significantly higher than the second-grade teacher candidates, whereas their attitudes towards teaching profession were significantly lower. In conclusion it is thought that the findings and negative relationships determined in this study provide strong clues suggesting that social studies teacher candidates' unemployment worries negatively affect their attitudes towards teaching profession.
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    The Roles of Personality Traits, AI Anxiety, and Demographic Factors in Attitudes toward Artificial Intelligence
    (Taylor & Francis Inc, 2024) Kaya, Feridun; Aydin, Fatih; Schepman, Astrid; Rodway, Paul; Yetisensoy, Okan; Kaya, Meva Demir
    The present study adapted the General Attitudes toward Artificial Intelligence Scale (GAAIS) to Turkish and investigated the impact of personality traits, artificial intelligence anxiety, and demographics on attitudes toward artificial intelligence. The sample consisted of 259 female (74%) and 91 male (26%) individuals aged between 18 and 51 (Mean = 24.23). Measures taken were demographics, the Ten-Item Personality Inventory, the Artificial Intelligence Anxiety Scale, and the General Attitudes toward Artificial Intelligence Scale. The Turkish GAAIS had good validity and reliability. Hierarchical Multiple Linear Regression Analyses showed that positive attitudes toward artificial intelligence were significantly predicted by the level of computer use (beta = 0.139, p = 0.013), level of knowledge about artificial intelligence (beta = 0.119, p = 0.029), and AI learning anxiety (beta = -0.172, p = 0.004). Negative attitudes toward artificial intelligence were significantly predicted by agreeableness (beta = 0.120, p = 0.019), AI configuration anxiety (beta = -0.379, p < 0.001), and AI learning anxiety (beta = -0.211, p < 0.001). Personality traits, AI anxiety, and demographics play important roles in attitudes toward AI. Results are discussed in light of the previous research and theoretical explanations.