Developing Adaptive Learning Technologies with AI for Students with Disabilities

Mohammed Zeinu Hassen

doi:doi:10.11648/j.sjedu.20251305.14

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Developing Adaptive Learning Technologies with AI for Students with Disabilities

Mohammed Zeinu Hassen^*

Published in Science Journal of Education (Volume 13, Issue 5)

Received: 4 October 2025 Accepted: 14 October 2025 Published: 31 October 2025

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Abstract

Traditional educational frameworks, characterized by standardized curricula and a uniform pace of instruction, frequently struggle to meet the varied learning requirements of students with disabilities. This systemic rigidity contributes to a persistent gap in educational outcomes and reveals the limitations of existing non-AI assistive tools, which are often static and unable to adapt to a learner's progress. The purpose of this article is to address this critical issue by examining the development of adaptive learning technologies driven by Artificial Intelligence (AI) to provide genuinely individualized educational experiences. It proposes a systematic approach for creating effective and ethical systems tailored to students with diverse needs. The methodology for this conceptual work involves a systematic review of the existing body of knowledge, which informs the introduction of a new development framework. This proposed framework outlines the essential components for robust adaptive systems, including: dynamic user profiling to create a rich, continuously updated understanding of a student’s learning patterns; generative AI models for the real-time creation and modification of educational content; immediate and constructive feedback mechanisms; and longitudinal progress monitoring to inform educators and guide long-term learning trajectories. The article concludes that while AI offers powerful tools to build more inclusive and equitable educational environments, its potential can only be realized through responsible and ethical implementation. The development process must be guided by a firm commitment to mitigating algorithmic bias, ensuring transparency and explainability in AI-driven decisions, establishing clear lines of accountability, and upholding robust data privacy standards. Ultimately, the successful integration of these advanced technologies depends on a foundation of ethical principles and human oversight to ensure fair and effective support for all students.

Published in	Science Journal of Education (Volume 13, Issue 5)
DOI	10.11648/j.sjedu.20251305.14
Page(s)	179-187
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2025. Published by Science Publishing Group

Keywords

Artificial Intelligence, Special Education, Assistive Technology, Students with Disabilities, Personalized Learning, Educational Technology, Ethical AI

References

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Hassen, M. Z. (2025). Developing Adaptive Learning Technologies with AI for Students with Disabilities. Science Journal of Education, 13(5), 179-187. https://doi.org/10.11648/j.sjedu.20251305.14

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Hassen, M. Z. Developing Adaptive Learning Technologies with AI for Students with Disabilities. Sci. J. Educ. 2025, 13(5), 179-187. doi: 10.11648/j.sjedu.20251305.14

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AMA Style

Hassen MZ. Developing Adaptive Learning Technologies with AI for Students with Disabilities. Sci J Educ. 2025;13(5):179-187. doi: 10.11648/j.sjedu.20251305.14

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@article{10.11648/j.sjedu.20251305.14,
  author = {Mohammed Zeinu Hassen},
  title = {Developing Adaptive Learning Technologies with AI for Students with Disabilities
},
  journal = {Science Journal of Education},
  volume = {13},
  number = {5},
  pages = {179-187},
  doi = {10.11648/j.sjedu.20251305.14},
  url = {https://doi.org/10.11648/j.sjedu.20251305.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjedu.20251305.14},
  abstract = {Traditional educational frameworks, characterized by standardized curricula and a uniform pace of instruction, frequently struggle to meet the varied learning requirements of students with disabilities. This systemic rigidity contributes to a persistent gap in educational outcomes and reveals the limitations of existing non-AI assistive tools, which are often static and unable to adapt to a learner's progress. The purpose of this article is to address this critical issue by examining the development of adaptive learning technologies driven by Artificial Intelligence (AI) to provide genuinely individualized educational experiences. It proposes a systematic approach for creating effective and ethical systems tailored to students with diverse needs. The methodology for this conceptual work involves a systematic review of the existing body of knowledge, which informs the introduction of a new development framework. This proposed framework outlines the essential components for robust adaptive systems, including: dynamic user profiling to create a rich, continuously updated understanding of a student’s learning patterns; generative AI models for the real-time creation and modification of educational content; immediate and constructive feedback mechanisms; and longitudinal progress monitoring to inform educators and guide long-term learning trajectories. The article concludes that while AI offers powerful tools to build more inclusive and equitable educational environments, its potential can only be realized through responsible and ethical implementation. The development process must be guided by a firm commitment to mitigating algorithmic bias, ensuring transparency and explainability in AI-driven decisions, establishing clear lines of accountability, and upholding robust data privacy standards. Ultimately, the successful integration of these advanced technologies depends on a foundation of ethical principles and human oversight to ensure fair and effective support for all students.
},
 year = {2025}
}

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TY  - JOUR
T1  - Developing Adaptive Learning Technologies with AI for Students with Disabilities

AU  - Mohammed Zeinu Hassen
Y1  - 2025/10/31
PY  - 2025
N1  - https://doi.org/10.11648/j.sjedu.20251305.14
DO  - 10.11648/j.sjedu.20251305.14
T2  - Science Journal of Education
JF  - Science Journal of Education
JO  - Science Journal of Education
SP  - 179
EP  - 187
PB  - Science Publishing Group
SN  - 2329-0897
UR  - https://doi.org/10.11648/j.sjedu.20251305.14
AB  - Traditional educational frameworks, characterized by standardized curricula and a uniform pace of instruction, frequently struggle to meet the varied learning requirements of students with disabilities. This systemic rigidity contributes to a persistent gap in educational outcomes and reveals the limitations of existing non-AI assistive tools, which are often static and unable to adapt to a learner's progress. The purpose of this article is to address this critical issue by examining the development of adaptive learning technologies driven by Artificial Intelligence (AI) to provide genuinely individualized educational experiences. It proposes a systematic approach for creating effective and ethical systems tailored to students with diverse needs. The methodology for this conceptual work involves a systematic review of the existing body of knowledge, which informs the introduction of a new development framework. This proposed framework outlines the essential components for robust adaptive systems, including: dynamic user profiling to create a rich, continuously updated understanding of a student’s learning patterns; generative AI models for the real-time creation and modification of educational content; immediate and constructive feedback mechanisms; and longitudinal progress monitoring to inform educators and guide long-term learning trajectories. The article concludes that while AI offers powerful tools to build more inclusive and equitable educational environments, its potential can only be realized through responsible and ethical implementation. The development process must be guided by a firm commitment to mitigating algorithmic bias, ensuring transparency and explainability in AI-driven decisions, establishing clear lines of accountability, and upholding robust data privacy standards. Ultimately, the successful integration of these advanced technologies depends on a foundation of ethical principles and human oversight to ensure fair and effective support for all students.

VL  - 13
IS  - 5
ER  -

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Author Information

Mohammed Zeinu Hassen

Department of Social Sciences, Addis Ababa Science and Technology University, Addis Ababa, Ethiopia

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http://orcid.org/0009-0007-7329-2146

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APA Style

Hassen, M. Z. (2025). Developing Adaptive Learning Technologies with AI for Students with Disabilities. Science Journal of Education, 13(5), 179-187. https://doi.org/10.11648/j.sjedu.20251305.14

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ACS Style

Hassen, M. Z. Developing Adaptive Learning Technologies with AI for Students with Disabilities. Sci. J. Educ. 2025, 13(5), 179-187. doi: 10.11648/j.sjedu.20251305.14

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AMA Style

Hassen MZ. Developing Adaptive Learning Technologies with AI for Students with Disabilities. Sci J Educ. 2025;13(5):179-187. doi: 10.11648/j.sjedu.20251305.14

Copy | Download

@article{10.11648/j.sjedu.20251305.14,
  author = {Mohammed Zeinu Hassen},
  title = {Developing Adaptive Learning Technologies with AI for Students with Disabilities
},
  journal = {Science Journal of Education},
  volume = {13},
  number = {5},
  pages = {179-187},
  doi = {10.11648/j.sjedu.20251305.14},
  url = {https://doi.org/10.11648/j.sjedu.20251305.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjedu.20251305.14},
  abstract = {Traditional educational frameworks, characterized by standardized curricula and a uniform pace of instruction, frequently struggle to meet the varied learning requirements of students with disabilities. This systemic rigidity contributes to a persistent gap in educational outcomes and reveals the limitations of existing non-AI assistive tools, which are often static and unable to adapt to a learner's progress. The purpose of this article is to address this critical issue by examining the development of adaptive learning technologies driven by Artificial Intelligence (AI) to provide genuinely individualized educational experiences. It proposes a systematic approach for creating effective and ethical systems tailored to students with diverse needs. The methodology for this conceptual work involves a systematic review of the existing body of knowledge, which informs the introduction of a new development framework. This proposed framework outlines the essential components for robust adaptive systems, including: dynamic user profiling to create a rich, continuously updated understanding of a student’s learning patterns; generative AI models for the real-time creation and modification of educational content; immediate and constructive feedback mechanisms; and longitudinal progress monitoring to inform educators and guide long-term learning trajectories. The article concludes that while AI offers powerful tools to build more inclusive and equitable educational environments, its potential can only be realized through responsible and ethical implementation. The development process must be guided by a firm commitment to mitigating algorithmic bias, ensuring transparency and explainability in AI-driven decisions, establishing clear lines of accountability, and upholding robust data privacy standards. Ultimately, the successful integration of these advanced technologies depends on a foundation of ethical principles and human oversight to ensure fair and effective support for all students.
},
 year = {2025}
}

Copy | Download

TY  - JOUR
T1  - Developing Adaptive Learning Technologies with AI for Students with Disabilities

AU  - Mohammed Zeinu Hassen
Y1  - 2025/10/31
PY  - 2025
N1  - https://doi.org/10.11648/j.sjedu.20251305.14
DO  - 10.11648/j.sjedu.20251305.14
T2  - Science Journal of Education
JF  - Science Journal of Education
JO  - Science Journal of Education
SP  - 179
EP  - 187
PB  - Science Publishing Group
SN  - 2329-0897
UR  - https://doi.org/10.11648/j.sjedu.20251305.14
AB  - Traditional educational frameworks, characterized by standardized curricula and a uniform pace of instruction, frequently struggle to meet the varied learning requirements of students with disabilities. This systemic rigidity contributes to a persistent gap in educational outcomes and reveals the limitations of existing non-AI assistive tools, which are often static and unable to adapt to a learner's progress. The purpose of this article is to address this critical issue by examining the development of adaptive learning technologies driven by Artificial Intelligence (AI) to provide genuinely individualized educational experiences. It proposes a systematic approach for creating effective and ethical systems tailored to students with diverse needs. The methodology for this conceptual work involves a systematic review of the existing body of knowledge, which informs the introduction of a new development framework. This proposed framework outlines the essential components for robust adaptive systems, including: dynamic user profiling to create a rich, continuously updated understanding of a student’s learning patterns; generative AI models for the real-time creation and modification of educational content; immediate and constructive feedback mechanisms; and longitudinal progress monitoring to inform educators and guide long-term learning trajectories. The article concludes that while AI offers powerful tools to build more inclusive and equitable educational environments, its potential can only be realized through responsible and ethical implementation. The development process must be guided by a firm commitment to mitigating algorithmic bias, ensuring transparency and explainability in AI-driven decisions, establishing clear lines of accountability, and upholding robust data privacy standards. Ultimately, the successful integration of these advanced technologies depends on a foundation of ethical principles and human oversight to ensure fair and effective support for all students.

VL  - 13
IS  - 5
ER  -

Copy | Download