Intorduction Inclusive education requires accurate and systematic identification of students with disabilities to ensure appropriate educational support and equitable learning opportunities. However, conventional assessment instruments used in inclusive schools are often limited in flexibility, accessibility, and responsiveness to diverse disability profiles. Recent advances in educational technology have introduced new possibilities for supporting assessment and identification processes through technology-based instruments. Methods This study aims to regularly review the use of technology-supported assessment instruments for identifying students with disabilities in inclusive education settings. A systematic literature review was conducted following the PRISMA 2020 guidelines. Relevant articles were retrieved from Scopus, Web of Science, ERIC, and PubMed databases, covering publications from 2021 to 2025. After a rigorous screening and eligibility process based on predefined inclusion and exclusion criteria, eight peer-reviewed international studies were included in the qualitative synthesis. Result and Discussion The findings reveal several dominant themes, including the use of assistive technologies and mobile applications to enhance accessibility, data-driven assessment systems such as learning analytics for continuous monitoring, and interactive or immersive technologies (e.g., AR/VR) to support adaptive and personalized assessment. Overall, technology-supported instruments were found to improve the accuracy, efficiency, and inclusiveness of assessment processes, although challenges related to teacher competence, infrastructure, and system integration remain prevalent. Conclusion In conclusion, technology-supported assessment instruments play a strategic role in strengthening the identification and assessment of students with disabilities in inclusive education. The review highlights the need for integrated, user-friendly, and data-informed assessment systems, as well as professional development for educators, to maximize the potential of technology in inclusive assessment practices.
Abnar et al. (Fri,) studied this question.