Enhancing mathematics education for students with special educational needs through generative AI - A case study in Greece

Oct 15, 2026

Uploaded by OmBimo

Generative AI is examined as a support for mathematics learning for students with special educational needs through a nine-hour classroom intervention in Greece. The study focuses on two 8th-grade learners with special educational needs and uses ChatGPT 3.5-generated worksheets customized to the current curriculum and to each student’s needs and interests. Data from interviews, tasks, and e-questionnaires are analyzed with a new framework grounded in mathematical familiarity. Findings show active engagement, safety and confidence, achievement of learning objectives, and improved attitudes, ending with practical teaching recommendations for teachers and education policymakers.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages24

Reading Time1 h 0 min

AccessFree to download

Introduction

Generative AI and its educational impact

Distinguishing AI-generated text from human writing

AI definitions and societal relevance

Inclusive education and differentiated teaching

OPEN ACCESS Research Article Contemporary Educational Technology, 2024, 16(4), ep535 ISSN: 1309-517X (Online) Enhancing mathematics education for students with special educational needs through generative AI: A case study in Greece Ioannis Rizos 1* 0000-0002-4092-1715 Evaggelos Foykas 2 0009-0001-3872-6945 Spiros V. Georgakopoulos 1 0000-0002-3374-0422 1 Department of Mathematics, University of Thessaly, Lamia, GREECE 2 Greek Secondary Education, Lamia, GREECE * Corresponding author: [ioarizos@uth.gr](ioarizos@uth.gr) Citation: Rizos, I., Foykas, E., & Georgakopoulos, S. V. (2024) . Enhancing mathematics education for students with special educational needs through generative AI: A case study in Greece. Contemporary Educational Technology, 16(4), ep535 . [https://doi.org/10.30935/cedtech/15487](https://doi.org/10.30935/cedtech/15487) ARTICLE INFO ABSTRACT | Received: 5 Jul 2024
Accepted: 24 Sep 2024
INTRODUCTION | The rapid development of generative artificial intelligence (AI) is expected to have a profound impact on various aspects of human society, including mathematics education. Nevertheless, there is a noticeable lack of research, particularly in Greece, that focuses on the development and assessment of lesson plans and math worksheets tailored for students with special educational needs. To address this research gap, we designed and conducted a nine-hour teaching intervention in a general mathematics classroom in Greece, involving two 8th grade students with special educational needs as the subjects of the study. The intervention utilized worksheets generated by the ChatGPT 3.5 application, which were customized based on the current curriculum, as well as the special educational needs and interests of the two participating students. The data were collected through interviews, tasks, and e-questionnaires, and analyzed using a new theoretical framework based on the concept of mathematical familiarity. The results indicated that students were actively engaged in the educational process, felt safe and confident, satisfactorily met the learning objectives, and developed positive attitudes towards the mathematics course. The paper concludes with a list of good practices, teaching suggestions and restrictions that could be useful to teachers and education policymakers. The target audience for the current study is, mainly, mathematics teachers who serve at all levels of education and have students with special educational needs in their classrooms. Furthermore, the article may also prove of interest to students, parents and teachers who are interested in the interaction between mathematics education and generative AI.
Keywords: special educational needs, mathematical familiarity, math worksheets, ChatGPT, qualitative research | | --- | --- | Recent research has highlighted the importance of effectively distinguishing between artificial intelligence (AI)-generated and human-written text, a critical issue across various fields, including education. Theocharopoulos et al. (2024) investigated the detection of AI-generated scientific abstracts using large language models (LLMs), revealing both significant challenges and advancements in the text classification accuracy. Additionally, the study by Theocharopoulos et al. (2023) on identifying AI-generated book reviews underscores the need for robust methodologies to preserve the integrity of educational content, achieving an impressive accuracy rate of 96.86% in differentiated between human and AI-generated text. These findings emphasize both the potential and limitations of LLMs in educational settings, aligning with our objective of integrating AI to enhance learning experiences for students with special educational needs. AI refers to the intelligence demonstrated my machines, particularly computer systems, and is regarded by professionals as closely related to algorithms and tools for building computer programs (see Ding et al., 202

FAQs

What research gap does the study address?

The study targets the lack of research in Greece on designing and assessing lesson plans and math worksheets tailored for students with special educational needs using generative AI.

How was the intervention designed and implemented?

A nine-hour teaching intervention was carried out in a general mathematics classroom with two 8th-grade students with special educational needs, using ChatGPT 3.5 to generate worksheets customized to curriculum, needs, and interests.

How were learning outcomes and student experiences evaluated?

Data were collected through interviews, tasks, and e-questionnaires, then analyzed using a new theoretical framework based on mathematical familiarity, leading to reported engagement, safety, confidence, and achievement of learning objectives.

Oct 15, 2026

Uploaded by OmBimo