HIGHER EDUCATION STUDENTS' VIEWS ON THE USE OF ARTIFICIAL INTELLIGENCE FOR TEACHING STUDENTS WITH SPECIFIC LEARNING DISABILITIES
Abstract
This research attempts to present the perspectives of higher education students regarding the use of Artificial Intelligence (AI) in language teaching interventions, with an emphasis on secondary education students with Specific Learning Difficulties (SpLDs). Although AI applications are associated in the literature with Education (AIED), the interest of the research community was revived in 2022 with the release of ChatGPT. This Large Language Model can generate text and quickly attract millions of users. This triggered expectations for potential benefits but also raised concerns about potential risks that may arise in the context of Special Education and Training (SET). Considering the above, the methodology utilized a mixed analysis of an online questionnaire administered to 120 students from "language" departments in Greece (Kalamata). In the results, expectations for skill improvement were expressed, but there were also concerns about providing ready-made answers. In addition, students expect resistance from parents and colleagues but support from the students themselves. The research highlighted the expected barriers and facilitators that students perceive they will encounter, of which the need for staff training was emphasized.
Article visualizations:
Keywords
Full Text:
PDFReferences
Ahmad, S. F., Alam, M. M., Rahmat, M. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and administrative role of Artificial Intelligence in Education. Sustainability, 14(3), 1101. https://doi.org/10.3390/su14031101
Alpaydin, E. (2016). Machine Learning: The New AI. MIT Press.
Ausat, 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), 16100-16106. https://doi.org/10.31004/joe.v5i4.2745
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
Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of Research. TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
Chaudhry, M. A., & Kazim, E. (2021). Artificial Intelligence in Education (aied): A high-level academic and industry note 2021. AI and Ethics, 2(1), 157-165. https://doi.org/10.1007/s43681-021-00074-z
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 (Vol. B). Diadrasis. [in Greek]
Cohen, L., Manion, L., & Morrison, K. (2017). Research Methods in Education. Routledge.
Drossinou Korea, M. (2020). Special education handbook and educational 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. (2024). Special education and training - The proposal "through" 's special education for the training children and young people with special needs. Opportuna. [in Greek]
Drossinou Korea, M., & Alexopoulos, P. (2023a). 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 Korea, M., & Alexopoulos, P. (2023b). Creating Structured, Differentiated Mobile Apps for a Student with ASDs. In 9th International e-Conference on Studies in Humanities and Social Sciences, 1–10. 10.32591/coas.e-conf.09.01001d
Drossinou Korea, M., & Alexopoulos, P. (2024). Factors Arising from the Utilization of Artificial Intelligence and Large Language Models in Special Education and Training. European Journal of Special Education Research, 10(2) 1–16. https://dx.doi.org/10.46827/ejse.v10i2.5209
Elbanna, S., & Armstrong, L. (2023). Exploring the integration of CHATGPT in education: Adapting for the future. Management & Sustainability: An Arab Review. https://doi.org/10.1108/msar-03-2023-0016
Fuchs, K. (2023). Exploring the opportunities and challenges of NLP models in Higher Education: Is chat GPT a blessing or a curse? Frontiers in Education, 8. https://doi.org/10.3389/feduc.2023.1166682
Hellenic Pedagogical Institute. (2009). "Readiness: Its meaning and significance (introduction)". In Ministry of Education & Pedagogical Institute, & Drossinou Korea M. (Eds.), Learning Readiness Activities. Oral Language, Psychomotor Skills, Cognitive Abilities, Emotional Organization. SET teacher's book (pp. 13-27). Pedagogical Institute, OEDB. [in Greek]
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.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An argument for AI in Education. Pearson.
Mackenzie, A. (2017). Machine Learners: Archaeology of a Data Practice. MIT Press.
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
Markakis, E., & Drossinou Korea, M. (2001). Experimental Analytical Curriculum for Specific Learning Difficulties (Dyslexia), Department of Special Education at the Pedagogical Institute. In Christakis K. (Eds.), Children with special needs in primary school: Theoretical and Practical Approach (pp. 321-350). Atrapos. [in Greek]
Mastrothanasis, K., & Kladaki, M. (2020). The Involvement of Children in the Arts during Their Leisure Time. Asian Journal of Language, Literature and Culture Studies, 3(2), 10-19.
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 (IJSE), 33(1), 191-207.
Mastrothanasis, K., Zervoudakis, K., & Kladaki, M. (2024). An application of computational intelligence in group formation for digital drama education. Iran Journal of Computer Science. https://doi.org/10.1007/s42044-024-00186-9
Muljono, M., Afini, U., Supriyanto, C., & Nugroho, R. A. (2017). The Development of Indonesian POS tagging system for computer-aided independent language learning. International Journal of Emerging Technologies in Learning (IJET), 12(11), 138–150. https://doi.org/10.3991/ijet.v12i11.7383
Ohlsson, S., & Spada, H. (1993). Learning to do and learning to understand: A lesson and a challenge for cognitive modeling. In P. Reimann (Ed.), Learning in Humans and Machines (pp. 37–62). Pergamon Press.
Papert, S. (1980). Mindstonns (Vol. 607). Basic Rooks.
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
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.
Tzimogiannis, A. (2017). E-learning: Theoretical approaches and educational designs. Critique. [in Greek]
Tzimogiannis, A. (2019). Digital technologies and 21st century learning. Critique. [in Greek]
Yu, E., & Sung, K.-S. (2002). A genetic algorithm for a university weekly courses timetabling problem. International Transactions in Operational Research, 9(6), 703–717. https://doi.org/10.1111/1475-3995.00383
DOI: http://dx.doi.org/10.46827/ejoe.v9i1.5518
Refbacks
- There are currently no refbacks.
Copyright © 2016-2023. European Journal of Open Education and E-learning Studies (ISSN 2501-9120) is a registered trademark of Open Access Publishing Group. All rights reserved.
This journal is a serial publication uniquely identified by an International Standard Serial Number (ISSN) serial number certificate issued by Romanian National Library (Biblioteca Nationala a Romaniei). All the research works are uniquely identified by a CrossRef DOI digital object identifier supplied by indexing and repository platforms.
All the research works published on this journal are meeting the Open Access Publishing requirements and can be freely accessed, shared, modified, distributed and used in educational, commercial and non-commercial purposes under a Creative Commons Attribution 4.0 International License (CC BY 4.0).