FACTORS ARISING FROM THE UTILIZATION OF ARTIFICIAL INTELLIGENCE AND LARGE LANGUAGE MODELS IN SPECIAL EDUCATION AND TRAINING

نویسندگان

  • Maria Drossinou Korea Assistant Professor of Special Education, Department of Philology, University of Peloponnese, Greece
  • Alexopoulos Panagiotis MEd Education Sciences – Education with the Use of New Technologies, Department of Primary Education, University of the Aegean, Greece

DOI:

https://doi.org/10.46827/ejse.v10i2.5209

کلمات کلیدی:

artificial intelligence, machine learning, language-based machine learning models, Special Education and Training [SET], large language models

چکیده

This literature review aims to create a connection between Special Education and Training (SET) with Artificial Intelligence (ΑΙ), specifically focusing on machine learning language models. These systems analyze language structures and rapidly generate text that closely resembles human expression. While AI tools have been present since the last century, global technological and research interest in AI experienced resurgence in November 2022 with the release of ChatGPT, a machine learning language model –“chatbot”. The introduction of this tool raised expectations for its potential in educating individuals with Special Educational Needs and/or Disabilities (SENDs). However, the literature also highlights concerns about potential risks and challenges associated with the widespread use of such tools in education. This paper explores the intersection of Special Education and Training goals and Large Language Models (LLM), presenting in the results the potential benefits and risks that may emerge from this interaction.

 

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بیوگرافی نویسندگان

  • Maria Drossinou Korea، Assistant Professor of Special Education, Department of Philology, University of Peloponnese, Greece

    Maria Drossinou-Korea is an assistant professor of Special Education and Training at the Department of Philology at the University of Peloponnese. She holds a PhD in clinical psychology from Panteion University in Athens. She worked for many years as the head of the Hellenic Pedagogical Institute and she is the author of three books with the following titles: a) Handbook of special education and educational narratives (2020), b) Portfolio of special education and interventions in Higher Education. Individual method of study a comprehension of texts (2023), and c) Special education and training. The "through" special education proposal for the training of children and young people with special needs (2017).

  • Alexopoulos Panagiotis، MEd Education Sciences – Education with the Use of New Technologies, Department of Primary Education, University of the Aegean, Greece
    Panagiotis Alexopoulos is a Philologist (Greek Literature Teacher), an honors graduate of the Department of Philology of the School of Humanities and Cultural Studies at the University of Peloponnese. He holds a postgraduate degree (MEd) in "Educational Sciences - Education using New Technologies" from the University of the Aegean and is a graduate of the MSc in "Modern and Contemporary History: New Perspectives and Prospects" at the University of Peloponnese. He teaches in secondary private education.

مراجع

Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of CHATGPT. Contemporary Educational Technology, 15(3). https://doi.org/10.30935/cedtech/13152

Alenezi, M. A., Mohamed, A. M., & Shaaban, T. S. (2023). Revolutionizing EFL special education: How CHATGPT is transforming the way teachers approach language learning. Innoeduca. International Journal of Technology and Educational Innovation, 9(2), 5–23. https://doi.org/10.24310/innoeduca.2023.v9i2.16774

Alshahrani, A. (2023). The impact of CHATGPT on blended learning: Current trends and future research directions. International Journal of Data and Network Science, 7(4), 2029–2040. https://doi.org/10.5267/j.ijdns.2023.6.010

AlZu’bi, S., Mughaid, A., Quiam, F., & Hendawi, S. (2023). Exploring the capabilities and limitations of CHATGPT and alternative big language models. Artificial Intelligence and Applications, 1–10. https://doi.org/10.47852/bonviewaia3202820

Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the era of Generative Artificial Intelligence (AI): Understanding the potential benefits of CHATGPT in promoting teaching and learning. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4337484

Balas, M., & Ing, E. B. (2023). Conversational AI models for ophthalmic diagnosis: Comparison of Chatgpt and the Isabel pro differential diagnosis generator. JFO Open Ophthalmology, 1, 100005. https://doi.org/10.1016/j.jfop.2023.100005

Bertacchini, F., Demarco, F., Scuro, C., Pantano, P., & Bilotta, E. (2023). A social robot connected with CHATGPT to improve cognitive functioning in ASD subjects. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1232177

Caruccio, L., Cirillo, S., Polese, G., Solimando, G., Sundaramurthy, S., & Tortora, G. (2024). Can CHATGPT provide intelligent diagnoses? A comparative study between predictive models and CHATGPT to define a new medical diagnostic bot. Expert Systems with Applications, 235, 121186. https://doi.org/10.1016/j.eswa.2023.121186

Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two Decades of Artificial Intelligence in Education: Contributors, Collaborations, Research Topics, Challenges, and Future Directions. Educational Technology & Society, 25 (1), 28-47.

Choi, E. (2023). A comprehensive inquiry into the use of CHATGPT examining general, educational, and disability-focused perspectives. International Journal of Arts, Humanities & Social Science, 04(11), 1–7. https://doi.org/10.56734/ijahss.v4n11a1

Christakis, K. (2000). Special Difficulties and Needs in Primary School. Atrapos. [in Greek]

Christakis, K. (2011). The education of children with difficulties, Introduction to special education. Diadrasis. [in Greek]

Christakis, K. (2023). Child and Youth Behaviour Problems. Diadrasis. [in Greek]

Drossinou Korea, M. (2017). Special education and training - The "through" of special education proposal for the education of children and young people with special needs. Opportuna. [in Greek]

Drossinou Korea, M. (2020). Special education handbook and education narratives. Opportuna. [in Greek]

Drossinou Korea, M. (2023). Special education portfolio and interventions in higher education. Individual study method and text comprehension. Opportuna. [in Greek]

Drossinou Korea, M., & Alexopoulos, P. (2022). Teaching social skills interventions with digital cognitive and language machines to a student with autism. International Journal of Social Science And Human Research, 05(11), 5234-5241. https://doi.org/10.47191/ijsshr/v5-i11-55

Drossinou Korea, M., & Alexopoulos, P. (2023). Informal Pedagogical Assessment in inclusive secondary education for a student with autism. International Journal of Social Science and Human Research, 06(05). https://doi.org/10.47191/ijsshr/v6-i5-01

Drossinou, M. (1997). The new technologies in special education. On the occasion of a visit to Sweden through the European Aryan educational exchange program. New Education, (05), 131-142. [in Greek]

Drossinou, M. (1999). Computer applications in teaching programs of special education. Special Education Issues, (4), 51-72. [in Greek]

Dutt, S., Ahuja, N. J., & Kumar, M. (2021). An intelligent tutoring system architecture based on Fuzzy Neural Network (FNN) for special education of learning disabled learners. Education and Information Technologies, 27(2), 2613–2633. https://doi.org/10.1007/s10639-021-10713-x

Hirosawa, T., Kawamura, R., Harada, Y., Mizuta, K., Tokumasu, K., Kaji, Y., Suzuki, T., & Shimizu, T. (2023). CHATGPT-generated differential diagnosis lists for complex case–derived clinical vignettes: Diagnostic Accuracy Evaluation. JMIR Medical Informatics, 11. https://doi.org/10.2196/48808

Horiuchi, D., Tatekawa, H., Shimono, T., Walston, S. L., Takita, H., Matsushita, S., Oura, T., Mitsuyama, Y., Miki, Y., & Ueda, D. (2023). Accuracy of chatgpt generated diagnosis from patient’s medical history and imaging findings in neuroradiology cases. Neuroradiology. https://doi.org/10.1007/s00234-023-03252-4

Ivanov, S., & Soliman, M. (2023). Game of algorithms: Chatgpt implications for the future of tourism education and research. Journal of Tourism Futures, 9(2), 214–221. https://doi.org/10.1108/jtf-02-2023-0038

Jauhiainen, J. S., & Guerra, A. G. (2023). Generative AI and Chatgpt in school children’s education: Evidence from a school lesson. Sustainability, 15(18), 14025. https://doi.org/10.3390/su151814025

Jimoyiannis, Α. (2017). E-learning: Theoretical approaches and educators Theoretical and theoretical approaches and theoretical designs. Kritiki. [in Greek]

Jimoyiannis, Α. (2019). Digital technologies and 21st century learning. Kritiki. [in Greek]

Karakose, T., & Tülübaş, T. (2023). How Can ChatGPT Facilitate Teaching and Learning: Implications for Contemporary Education. Educational Process, International Journal, 12(4), 7-16.

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). Chatgpt for good? on opportunities and challenges of large language models for Education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Khan, R. U., Cheng, J. L. A., & Bee, O. Y. (2018). Machine Learning and Dyslexia: Diagnostic and Classification System (DCS) for Kids with Learning Disabilities. International Journal of Engineering & Technology, 7(3.18), 97-100.

Koga, S., Martin, N. B., & Dickson, D. W. (2023). Evaluating the performance of large language models: ChatGPT and Google Bard in generating differential diagnoses in clinicopathological conferences of neurodegenerative disorders. Brain Pathology. https://doi.org/10.1111/bpa.13207

Kuroiwa, T., Sarcon, A., Ibara, T., Yamada, E., Yamamoto, A., Tsukamoto, K., & Fujita, K. (2023). The potential of CHATGPT as a self-diagnostic tool in common orthopedic diseases: Exploratory study. Journal of Medical Internet Research, 25. https://doi.org/10.2196/47621

Liao, M., Duan, H., & Wang, G. (2022). Application of machine learning techniques to detect children with autism spectrum disorder. Journal of Healthcare Engineering, 2022, 1–10. https://doi.org/10.1155/2022/9340027

Maenner, M. J., Yeargin-Allsopp, M., Van Naarden Braun, K., Christensen, D. L., & Schieve, L. A. (2016). Development of a machine learning algorithm for the surveillance of autism spectrum disorder. PLOS ONE, 11(12). https://doi.org/10.1371/journal.pone.0168224

Marino, M. T., Vasquez, E., Dieker, L., Basham, J., & Blackorby, J. (2023). The Future of Artificial Intelligence in Special Education Technology. Journal of Special Education Technology, 38(3), 404–416. https://doi.org/10.1177/01626434231165977

Mastrothanasis, K., Kalianou, M., Katsifi, S., & Zouganali, A. (2018). The Use of Metacognitive Knowledge and Regulation Strategies of Students with and without Special Learning Difficulties. International Journal of Special Education, 33(1), 184–200.

Mbakwe, A. B., Lourentzou, I., Celi, L. A., Mechanic, O. J., & Dagan, A. (2023). CHATGPT passing USMLE shines a spotlight on the flaws of Medical Education. PLOS Digital Health, 2(2). https://doi.org/10.1371/journal.pdig.0000205

Rakap, S. (2023). Chatting with GPT: Enhancing individualized education program goal development for novice special education teachers. Journal of Special Education Technology. https://doi.org/10.1177/01626434231211295

Rane, N. (2023). Chatbot-enhanced teaching and learning: Implementation strategies, challenges, and the rrole of chatgpt in Education. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4603204

Rizwan, A., & Sadiq, T. (2023). The use of AI in diagnosing diseases and providing management plans: A consultation on cardiovascular disorders with CHATGPT. Cureus. https://doi.org/10.7759/cureus.43106

Stokel-Walker, C. (2023). CHATGPT listed as author on research papers: Many scientists disapprove. Nature, 613(7945), 620-621. https://doi.org/10.1038/d41586-023-00107-z

Trust, T., Whalen, J., & Mouza, C. (2023). Editorial: ChatGPT: Challenges, opportunities, and implications for teacher education. Contemporary Issues in Technology and Teacher Education, 23(1), 1-23.

Yu, H. (2023). Reflection on whether chat GPT should be banned by academia from the perspective of education and teaching. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1181712

Zhai, X. (2023). Chatgpt for Next Generation Science Learning. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4331313

Zhang, C., & Lu, Y. (2021). Study on Artificial Intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224. https://doi.org/10.1016/j.jii.2021.100224

دانلودها

چاپ شده

2024-02-12

شماره

دوره 10 شماره 2 (2024)

نوع مقاله

Articles

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