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<p>The growing prevalence of Autism Spectrum Disorder (ASD) underscores the need for adaptive educational tools that promote inclusion. While a variety of digital resources are available, their fragmentation limits data unification and comprehensive longitudinal monitoring of student progress. This study introduces a personalized Learning Management System (LMS) called SpectrumSphere that incorporates Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (AR), robotics, and Augmentative and Alternative Communication (AAC) to provide real-time, data-driven personalization, objective progress tracking, and enhanced collaboration between teachers and parents. This study has evaluated the intention of adoption of our LMS using an extended Technology Acceptance Model (TAM) with 30 special education teachers in different schools from the Valencian Community. Our findings show that perceived usefulness, perceived ease of use, and computer self-efficacy are the strongest predictors of teachers’ behavioral intention to adopt technology, while perceived external control operates indirectly by strengthening computer self-efficacy, highlighting that intuitive interfaces, robust institutional support and infrastructure, and comprehensive professional development are crucial to enable educators to harness SpectrumSphere’s adaptive recommendations.</p>

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Development and pilot evaluation of an AI-driven learning management system for personalized education for autistic students

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月9日

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  • Diana Gadzhimusieva,
  • Santiago Meliá,
  • Gonzalo Lorenzo Lledó,
  • Seyed Shahabadin Nasabeh

摘要

The growing prevalence of Autism Spectrum Disorder (ASD) underscores the need for adaptive educational tools that promote inclusion. While a variety of digital resources are available, their fragmentation limits data unification and comprehensive longitudinal monitoring of student progress. This study introduces a personalized Learning Management System (LMS) called SpectrumSphere that incorporates Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (AR), robotics, and Augmentative and Alternative Communication (AAC) to provide real-time, data-driven personalization, objective progress tracking, and enhanced collaboration between teachers and parents. This study has evaluated the intention of adoption of our LMS using an extended Technology Acceptance Model (TAM) with 30 special education teachers in different schools from the Valencian Community. Our findings show that perceived usefulness, perceived ease of use, and computer self-efficacy are the strongest predictors of teachers’ behavioral intention to adopt technology, while perceived external control operates indirectly by strengthening computer self-efficacy, highlighting that intuitive interfaces, robust institutional support and infrastructure, and comprehensive professional development are crucial to enable educators to harness SpectrumSphere’s adaptive recommendations.