Aug 2026· Uludağ Üniversitesi Eğitim Fakültesi Dergisi· 0 citations· 23 references
TL;DR
The findings reveal that pre-service teachers perceive generative artificial intelligence as a supportive learning partner in areas such as time management, idea development, linguistic accuracy, and self-regulation, but also highlighted risks such as over-reliance, diminished creativity, ethical concerns, and the generation of inaccurate information.
Abstract
This study investigates how pre-service teachers experience generative artificial intelligence tools in their learning processes and how they plan to integrate these technologies into their future teaching practices. The study employed a qualitative phenomenological design and was conducted with 28 pre-service teachers enrolled in the English language teaching program of a public university in Türkiye. Semi-structured online interviews were carried out, and the data were analyzed through content analysis. Coding was conducted independently by two coders, achieving a high level of inter-rater agreement. The findings reveal that pre-service teachers perceive generative artificial intelligence as a supportive learning partner in areas such as time management, idea development, linguistic accuracy, and self-regulation. However, they also highlighted risks such as over-reliance, diminished creativity, ethical concerns, and the generation of inaccurate information. The participants emphasized that while generative artificial intelligence may serve as a complementary tool in learning processes, classroom integration requires transparency, critical verification, and active teacher guidance as essential conditions. The originality of the study lies in its holistic exploration of pre-service teachers’ experiences with generative artificial intelligence across pedagogical, ethical, and professional identity dimensions. These findings provide qualitative evidence for the relatively underexplored perspectives of pre-service teachers, thereby offering a new lens for ongoing debates on the role of generative artificial intelligence in teacher education.
The findings reveal that GenAI is increasingly being used to support core teaching tasks such as lesson planning, materials development, and assessment design, enhancing efficiency and expanding instructional possibilities while reshaping traditional notions of pedagogical work.
O. Madden· Digital Applied Linguistics· 0 citations
This study explores how pre-service English teachers experience and perceive the use of Gen AI in language education contexts, and underscores the potential of Gen AI as a supportive tool in teacher education while reinforcing the necessity of human oversight and reflective practice.
Ramazan Yetkin, Zekiye Özer-Altınkaya· Kuramsal Eğitimbilim· 0 citations
This study explores how pre-service mathematics teachers experience AI-supported teaching during their practicum and how they make sense of the perceived influence of these experiences on pedagogical decision-making, classroom management, reflective awareness, and professional identity development. Conducted within a qualitative research framework, the study draws on data collected from 21 pre-service teachers through weekly reflective journals, AI-integrated lesson plans, and semi-structured interviews over an 8-week practicum period. Thematic analysis revealed four core themes: (1) Establishing effective classroom interaction, (2) Designing pedagogy for diverse student needs, (3) Developing reflective and metacognitive decision-making skills, and (4) Professional identity formation, sense of belonging, and self-worth. Findings indicate that GenAI tools supported teacher candidates in recognizing students’ academic and emotional needs, justifying their instructional strategies, and transforming their relational practices in the classroom. The study suggests that AI-supported practicum experiences can contribute not only to instructional planning but also to the development of reflective, responsive, and professionally aware mathematics teacher candidates.
Şahin Danişman· E-Learning and Digital Media· 0 citations
By isolating the crucial components of fairness, accountability, and agency which underpin the factors most predictive of teacher readiness, this study lays a framework for leaders and policy makers searching to translate teacher doubt into enthusiastic and responsible carrying out of AI tools.
Laurence Ajaka, Mireille Saba Redford, Randa Saliba Chidiac et al.· Journal of Intelligent Decis...· 0 citations
The development of generative artificial intelligence in education has brought about significant transformations in learning practices, particularly through its emergence as a shadow teacher capable of providing explanations, feedback, and learning materials instantly. This situation has given rise to new problems related to the shift in teachers' pedagogical authority, both in epistemic, relational, and normative aspects in formal classrooms. This study aims to analyze the impact of the use of generative AI on teachers' pedagogical authority and identify the opportunities and challenges it poses in the contemporary educational context. This study uses a qualitative approach with a literature review method, which includes data collection through searching reputable journal articles, academic books, research reports, and education policy documents relevant to the topic of AI and pedagogy. Data analysis techniques used thematic and comparative analysis to identify patterns, trends, and differences in expert views. Data validity was maintained through evaluation of source credibility, reference recency, and argument consistency, while triangulation was carried out by comparing findings from various types of sources and disciplinary perspectives. The results of the study indicate that generative AI has the potential to shift teachers' pedagogical authority from the center of knowledge transmission to the role of facilitator, learning curator, and value builder, but not completely replace the role of the teacher. Pedagogical authority is actually undergoing a redefinition, demanding stronger pedagogical, ethical, and digital literacy competencies. This research implies the importance of developing teacher education and training policies that are adaptive to the integration of AI in a critical, humanistic manner, and oriented toward strengthening teachers' strategic role in the digital learning ecosystem.
Izza Agitsna, Arief Ardyansyah, Ega Krisna Pradita et al.· TA DIBUNA Jurnal Pendidikan...· 0 citations
The objective of this study was to explore how teachers interpret learning engagement in AI-mediated classrooms and develop a qualitative model based on their lived professional experiences. This qualitative study used a phenomenological–interpretive design to explore teachers’ conceptualizations of engagement in the context of artificial intelligence. Data were collected through semi-structured, in-depth interviews with 24 teachers from Tehran selected via purposive sampling to ensure variation in teaching level, experience, and familiarity with AI-supported tools. Interviews lasted 45–75 minutes, were audio-recorded, transcribed verbatim, and analyzed using thematic analysis supported by NVivo software. Coding proceeded through open, axial, and selective stages, and theoretical saturation was achieved after 24 interviews. Trustworthiness was ensured through peer debriefing, constant comparison, and analytic memoing. Analysis yielded four overarching themes: (1) redefinition of learning engagement, (2) AI as a catalyst for instructional transformation, (3) challenges and tensions in AI-supported engagement, and (4) shifts in teacher professional identity. Teachers reported that AI reshapes cognitive, emotional, and behavioral facets of engagement through adaptive feedback, analytics, and interactive tools. AI-personalized pathways strengthened perceived cognitive engagement, while real-time data influenced how teachers inferred students’ attention and persistence. However, concerns emerged regarding algorithmic accuracy, over-reliance on automation, and pedagogical misalignment. Teachers also described evolving roles as facilitators of human–AI interaction, interpreting engagement through both professional judgment and AI signals. These inferential results indicate that teacher interpretations are hybrid, negotiated, and context-dependent. Teachers in AI-enhanced classrooms reconceptualize learning engagement as a multidimensional and technology-mediated construct shaped by analytics, emotional responses, behavioral cues, and evolving professional identities. The resulting qualitative model underscores the need for AI literacy, critical interpretation of automated insights, and balanced integration of human expertise and intelligent systems.
Ardeshir Danesh, Samira Memari· Assessment and Practice in E...· 0 citations
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