Session Information
Paper Session
Contribution
Generative Artificial Intelligence (GenAI) enables human-machine interaction that significantly differs from previous information technologies. It is capable of creating new knowledge, maintaining coherent discussions, and evaluating ideas (Jovanovic & Campbell, 2022). Generative AI offers varied opportunities for the educational system to transform teaching and learning processes, potentially enhancing essential skills, including knowledge construction, critical analysis, and learner autonomy (Luckin, 2024). However, it also presents substantial challenges, particularly around ethical considerations, data privacy, and systemic bias in algorithms (Grassini, 2023).
Recent studies on GenAI in education have predominantly focused on its integration into teaching practices, often assuming such integration is desirable (e.g. Cheng & Wang, 2023; Pörn et al., 2024). This perspective aligns with the technology's potential to facilitate education's adaptation to 21st-century needs. However, as empirically evident, teachers in the field might hold different perspectives regarding how schools should adapt to contemporary challenges and student needs (Ben-David Kolikant, 2019).
This research adopts a socio-cultural perspective, viewing actions as mediated by physical and psychological tools. When encountering a new tool, our perception of its possibilities and limitations gradually develops, transforming our goals and actions within that context. Our history with the tool and the contextual setting influences how we perform actions and perceive the context. Previous experiences and social structures shape how people define and prioritize their goals (Wertsch, 1998). From this theoretical viewpoint, GenAI is not merely another tool for lesson planning or assessment, nor a means for students to potentially circumvent learning. Instead, like any new tool, it transforms users' contextual understanding, actions, and values, even without direct usage.
Correspondingly, our research extends beyond integration questions to examine teachers' comprehensive considerations regarding their teaching in light of GenAI's significant presence in educational discourse. Specifically, we investigate how teachers perceive changes in their teaching due to the availability of technology as well as the evolving context of their work within schools and the broader education system. To this end, semi-structured interviews were conducted with interviewed 24 teachers and were analyzed thematically.
All the teachers distinguished between using GenAI for lesson preparation tasks and using it with students. Teachers generally show a willingness to use it themselves, yet they tend to think that students should use it only limitedly, if at all.
The willingness to use GenAI in teaching (themselves or with students) corresponds with teachers' perceptions about the nature of the technology and their pedagogical worldview. Specifically, teachers who focus on content delivery and perceive GenAI as an (unreliable) information source choose not to use it themselves or present it to students. In contrast, teachers whose pedagogical approach focuses on flexible teaching based on responding to developing classroom discussion and who simultaneously perceive GenAI as enabling flexibility use it both in lesson preparation and with students. Teachers who emphasize the importance of student thinking in their teaching and perceive GenAI as making thinking redundant indicated that while they use it themselves, they oppose student use.
Assessment was a prominent theme. It was part of teachers’ concerns about students' unethical use of technology. Some explained that GenAI use may empty important tasks from the original mental efforts they require. Teachers’ efforts concentrate on blocking student use, preferring classroom work over homework and tests over projects and term papers.
All teachers reported that they are in the process of determining the implications of the new tool for their work. Most interviewees reported feeling they are going through this process alone, navigating without clear guidelines. This feeling was shared even by those who participated in professional development and those whose school appointed a team to dealing with GenAI.
Method
This study is part of a larger research project that revolves around how the prevalence of GenAI in our life influences teachers’ professionally. We conducted semi-structured interviews with 24 middle school teachers across Israel (20 women and 4 men). The sample is a convenience sample of teachers teaching various subjects (average experience: 13.04 years, SD: 8.8). The interviews were conducted during the summer break 2024. The interviews focused on several key areas: teachers' perceptions regarding the nature of GenAI (how the technology works and their opinions about it), whether and how they take this technology into account in their work, how they perceive the education system's readiness for the technology (Ministry of Education, school, and colleagues); whether their students use it; and how they should adapt their teaching to the new reality. The interviews were analyzed thematically using the Constant Comparison Method (Strauss & Corbin, 1998). Two judges coded the interviews, and disagreements were resolved through discussion.
Expected Outcomes
This study supports previous empirical work that found that teachers' pedagogical perceptions influence how they use technology in their teaching (Kopcha et al., 2020; Tondeur et al., 2017). Our findings add that the choice of how to use the technology, if at all, also corresponds with the various ways teachers perceive GenAI and its affordances. Contrary to the perception of GenAI adoption as desirable and non-adoption as a "problem" (e.g., Cheng & Wang, 2023), our findings reveal that, at least in some cases, teachers who do not use GenAI in teaching have significant arguments on this issue, such as the importance of students expressing themselves directly. Finally, the historical and institutional context of needing to preserve learning and assessment activities that the new tool might make meaningless was prominent, leading to prioritizing activities where teachers have more control over student work, such as tests, instead of assignments. Therefore, in order to exploit the educational potential of GenAI, the discourse on its integration into schooling practices cannot focus merely on introducing teachers to tools and ways to use them, with the hope to raise their ‘willingness’, but must also address the richness and complexity of the context within which they work, such as the complexity of the school arena (and its actors), the variety of pedagogical actions and their goals, the diversity of teachers' perceptions, and the connections between them. While this study is based on a small sample, the findings provide significant insights into how teachers perceive GenAI, decide on its use, and cope with the changes it brings. This study constitutes the first stage of a broader national research project, which in its next phases will quantitatively examine, among other things, the issues that emerged.
References
Ben-David Kolikant, Y. (2019). Adapting school to the twenty-first century: Educators’ perspectives. Technology, Pedagogy and Education, 28(3), 287–299. https://doi.org/10.1080/1475939X.2019.1584580 Cheng, E. C. K., & Wang, T. (2023). Leading digital transformation and eliminating barriers for teachers to incorporate artificial intelligence in basic education in Hong Kong. Computers and Education: Artificial Intelligence, 5, 100171. https://doi.org/10.1016/j.caeai.2023.100171 Grassini, S. (2023). Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences, 13(7), 692. https://doi.org/10.3390/educsci13070692 Jovanovic, M., & Campbell, M. (2022). Generative Artificial Intelligence: Trends and Prospects. Computer, 55(10), 107–112. https://doi.org/10.1109/MC.2022.3192720 Kopcha, T. J., Neumann, K. L., Ottenbreit-Leftwich, A., & Pitman, E. (2020). Process over product: The next evolution of our quest for technology integration. Educational Technology Research and Development, 68(2), 729–749. https://doi.org/10.1007/s11423-020-09735-y Luckin, R. (2024). Nurturing human intelligence in the age of AI: Rethinking education for the future. Development and Learning in Organizations: An International Journal. https://doi.org/10.1108/DLO-04-2024-0108 Pörn, R., Braskén, M., Wingren, M., & Andersson, S. (2024). Attitudes towards and expectations on the role of artificial intelligence in the classroom among digitally skilled Finnish K-12 mathematics teachers. LUMAT: International Journal on Math, Science and Technology Education, 12(3). https://doi.org/10.31129/LUMAT.12.3.2102 Strauss, A. L., & Corbin, J. M. (1998). Basics of qualitative research: Techniques and procedures for developing grounded theory (2nd ed). Sage Publications. Tondeur, J., Van Braak, J., Ertmer, P. A., & Ottenbreit-Leftwich, A. (2017). Understanding the relationship between teachers’ pedagogical beliefs and technology use in education: A systematic review of qualitative evidence. Educational Technology Research and Development, 65(3), 555–575. https://doi.org/10.1007/s11423-016-9481-2 Wertsch, J. V. (1998). Mind as action. Oxford University Press.
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