Session Information
99 ERC SES 07 A, Ignite Talks
Ignite Talks Session
Contribution
In the rapidly evolving landscape of education, the integration of AI, particularly Chatbots, presents a fundamental area of exploration. My research is centered around the critical question: "How does the integration of AI, particularly Chatbots, affect the professional activities of teachers, and how do educators envision their roles with these AI tools?" This inquiry delves into the transformative impact of artificial intelligence on educational practices. The theoretical framework of this research is multi-faceted, intertwining educational philosophy paradigms with contemporary socio-technological theories.
At its core, the research utilizes a constructivist paradigm, inspired by the works of Papert (1971), Kay (2011), Ilic et al. (2021) viewing AI as a dynamic tool enhancing the learning process. It actively transforms education and motivates teachers to prepare students for the future. These tools simplify complex concepts by relating them to familiar ones within the environment and have the potential to create their models of the world. Complementing this, the postmodern perspective, particularly Foucault's and other Foucauldian scholars contributing to this discourse's insights on power dynamics and knowledge creation, offers a lens to examine the interaction between technology and educators. It probes into how these interactions influence societal structures and control within the educational realm.
Furthermore, the application of Actor-Network Theory (ANT), as conceptualized by Latour (2005), provides a nuanced understanding of AI in education. ANT posits that both technology and humans, in this case, educators, are co-actors in the social world, shaping and being shaped by each other. This theory is particularly relevant in exploring how educators interact with AI tools like Chatbots, forming a symbiotic relationship that redefines the educational landscape.
The research also draws attention to the broader European and international dimensions, reflecting on the insights from UNESCO which underscore the importance of technology in future educational models. The response of European countries, as noted by the OECD and the European Parliament, especially during the Covid-19 pandemic, highlights the strength and adaptability of implementing AI in various sectors, including education.
This research aims not only to provide a theoretical understanding of these dynamics but also to offer practical insights for educators and policymakers. The increasing necessity for teacher professional development in line with technological advancements is a crucial aspect of this study. It addresses the potential risks of a future where educators might be unprepared for the integration of modern AI tools in their teaching practices.
In conclusion, this research analyzing the motivations, implications, and future prospects of AI integration in teacher professional activities, it aims to contribute significantly to the discourse on technology and education, ensuring that educators are well-equipped to harness the benefits of AI in their professional lives.
Method
In my PhD research, I am planning to use Actor-Network Theory (ANT) as both a theoretical and methodological approach to explore the intricate relationship between educators and artificial intelligence tools, particularly Chatbots. ANT, a framework developed in the field of Science and Technology Studies, offers a unique lens through which the complex networks of interactions between human and non-human actors can be examined. In the context of my research, this involves understanding how educators, as human actors, interact with and are influenced by AI technologies, which are non-human actors in the educational landscape. However, I am currently conducting a survey with teachers to gather data on their readiness and motivation to use digital tools, particularly AI technologies like Chatbots. The survey seeks to understand the educators' level of engagement with these technologies, their perceptions of its benefits and challenges, and their willingness to integrate such tools into their teaching practices. Therefore, in this conference, I will also present this dynamic to provide a more holistic understanding of the impact of AI on teaching and teachers' motivations to use these tools. This mixed-methods approach allows for a more comprehensive exploration of the topic. The qualitative aspect focuses on the nuanced, detailed experiences and perceptions of educators, while the quantitative aspect offers a broader, statistically significant perspective.
Expected Outcomes
One of the primary expected outcomes is a detailed insight into educators readiness and motivation to incorporate AI tools in their teaching practices. The survey conducted with teachers is likely to reveal varied levels of engagement with these technologies, influenced by factors such as technological proficiency, perceived benefits and challenges, and the existing educational infrastructure. These findings will contribute to a deeper understanding of the factors that drive or hinder the adoption of AI in education. In general this research is expected to provide comprehensive findings on the integration of AI in education, with a focus on the perspective of teachers. It aims to inform future practices in educational technology, ensuring that the incorporation of AI tools like Chatbots is effectively aligned with the needs and capabilities of educators. This alignment is crucial for maximizing the potential of AI in enhancing educational outcomes and preparing students and teachers for a future increasingly influenced by technological advancements.
References
Ausat, A. M. A. (2022). Positive Impact of The Covid-19 Pandemic on The World of Education. Jurnal Pendidikan, 23(2), 107-117. Ausat, A. M. A., Massang, B., Efendi, M., Nofirman, N., Riady, Y. (2023). Can Chat GPT Replace the Role of the Teacher in the Classroom: A Fundamental Analysis. Journal on Education, 5(4), 100-106 Ball, S. J. (2013). Foucault and education: Disciplines and knowledge. Routledge. Fenwick, T., Edwards, R. (2010). Introduction: Reclaiming and renewing actor network theory for educational research. Educational Philosophy and Theory, 43(sup1), 1-14. Gough, N. (2004). RhizomANTically Becoming-Cyborg: Performing posthuman pedagogies. Educational Philosophy and Theory, 36(3), 253-265. https://doi.org/10.1111/j.1469-5812.2004.00066.x Foucault, M. (1975). Discipline and punish: The birth of the prison. Vintage. Heimans, S., Biesta, G., Takayama, K., & Kettle, M. (2023). ChatGPT, subjectification, and the purposes and politics of teacher education and its scholarship. Asia-Pacific Journal of Teacher Education, 51(2), 105-112. https://doi.org/10.1080/1359866X.2023.2189368 Ilic, M. P., Paun, D., Popovic Ševic, N., Hadžic, A., Jianu, A. (2021). Needs and performance analysis for changes in higher education and implementation of artificial intelligence, machine learning, and extended reality. Education Sciences, 11(10), 568. Kay, A. C. (1991). Computers, networks and education. Scientific American, 265(3), 138-149. Latour, B. (2005) Reassembling the Social: An introduction to actor-network theory, (Oxford, Oxford University Press). OECD (2021). OECD Digital Education Outlook. Retrieved from: https://read.oecd-ilibrary.org/education/oecd-digital-education-outlook-2021_589b283f-en#page5 Papert, S. (1993). The children's machine: Rethinking school in the age of the computer. Basic Books, a Division of HarperCollins Publishers. Rabinow P., Rose N. (2006) Biopower today. BioSocieties 1.2: 195-217. Simanowski, R. (2016). Digital humanities and digital media conversations on politics, culture, aesthetics, and literacy. London. UNESCO. (2021). Pathways to 2050 and beyond: Findings from a public consultation on the futures of higher education. Retrieved from: https://unesdoc.unesco.org/ark:/48223/pf0000379985 Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30.
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