Empowering Neurodivergent Learners: Developing Inclusive Learning Technologies Based on Cognitive Behavioral Theories
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Background. The effectiveness of inclusive learning technologies for neurodivergent learners is strongly influenced by how well these tools align with cognitive and behavioral needs. Cognitive Behavioral Theories (CBT) provide a structured framework for addressing learning barriers by focusing on thought patterns, emotional regulation, and adaptive behaviors.
Purpose. This study aimed to investigate the development and evaluation of inclusive learning technologies grounded in CBT frameworks. Specifically, it examined how these technologies can empower neurodivergent learners—such as those with autism spectrum disorder (ASD), ADHD, and dyslexia—by improving focus, self-regulation, and active participation in the learning process.
Method. The research employed a mixed-methods approach involving 220 neurodivergent learners across higher education and special education settings. Quantitative data were collected through pre- and post-intervention surveys measuring cognitive engagement, emotional regulation, and perceived inclusivity.
Results. The findings indicate that CBT-informed digital tools significantly enhanced self-monitoring, reduced task-related anxiety, and increased collaborative engagement across diverse learning contexts. Learners with ADHD showed marked improvements in task persistence, while those with dyslexia demonstrated better comprehension outcomes when adaptive text and cognitive scaffolding features were included.
Conclusion. This study highlights the transformative role of CBT-based inclusive technologies in empowering neurodivergent learners. By embedding cognitive-behavioral strategies into digital learning platforms, educators can design interventions that promote equity, resilience, and sustainable learning outcomes. The results carry important implications for future policy, curriculum design, and educational technology innovation aimed at inclusive education.
Aariya, N. (2025). Leveraging the Graph Convolutional Attention Hybrid Model for Real-Time Worker Safety Risk Prediction in the Gig Economy Risk Assessment and Mitigation Strategies. 6th International Conference on Mobile Computing and Sustainable Informatics Icmcsi 2025 Proceedings, Query date: 2025-08-22 02:44:20, 1827–1834. https://doi.org/10.1109/ICMCSI64620.2025.10883606
Adeyinka, K. I. (2025). Leveraging VANET and blockchain for real time solutions. Leveraging Vanets and Blockchain Technology for Urban Mobility, Query date: 2025-08-22 02:44:20, 315–358. https://doi.org/10.4018/979-8-3373-0265-2.ch016
Aggarwal, D. (2025). Leveraging the multifaceted utility of Psidium guajava derived activated carbon: A sustainable strategy for adsorptive detoxification and real-time detection of pollutants in wastewater. Journal of Water Process Engineering, 72(Query date: 2025-08-22 02:44:20). https://doi.org/10.1016/j.jwpe.2025.107490
Chen, J. (2025). Leveraging Scalable Cloud Infrastructure for Autonomous Driving Data Lakes and Real-Time Decision Making. 2025 5th International Conference on Artificial Intelligence and Industrial Technology Applications Aiita 2025, Query date: 2025-08-22 02:44:20, 1750–1753. https://doi.org/10.1109/AIITA65135.2025.11048068
Choi, W. (2024). Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator. Proceedings IEEE International Conference on Robotics and Automation, Query date: 2025-08-22 02:44:20, 14732–14739. https://doi.org/10.1109/ICRA57147.2024.10610716
Christensen, M. S. F. (2025). Leveraging the Industrial Internet of Things (IIoT) for Real-Time CO2 Monitoring, Measurement and Visualization: Technologies, Applications and Future Directions. Communications in Computer and Information Science, 2328(Query date: 2025-08-22 02:44:20), 35–59. https://doi.org/10.1007/978-3-031-78572-6_3
Dai, Y. (2025). Leveraging Social Media for Real-Time Interpretable and Amendable Suicide Risk Prediction With Human-in-The-Loop. IEEE Transactions on Affective Computing, 16(2), 1128–1145. https://doi.org/10.1109/TAFFC.2024.3494860
Debdas, S. (2024). Leveraging Real-Time Location and Weather Data for Enhanced Container Shipment Tracking. 2024 Parul International Conference on Engineering and Technology Picet 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/PICET60765.2024.10716188
Dubey, A. K. (2024). Optimizing Cybersecurity: Leveraging Support Vector Machines for Real-Time Threat Detection. 2024 1st International Conference on Innovations in Communications Electrical and Computer Engineering Icicec 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/ICICEC62498.2024.10808642
Etchegaray, D. (2023). Open-RoadAtlas: Leveraging VLMs for Road Condition Survey with Real-Time Mobile Auditing. Mm 2023 Proceedings of the 31st ACM International Conference on Multimedia, Query date: 2025-08-22 02:44:20, 9374–9375. https://doi.org/10.1145/3581783.3612668
Fowdur, T. P. (2024). Leveraging the Power of Blockchain in Industry 4.0 and Intelligent Real-Time Systems for Achieving the SDGs. Artificial Intelligence Engineering Systems and Sustainable Development Driving the Un Sdgs, Query date: 2025-08-22 02:44:20, 109–121. https://doi.org/10.1108/978-1-83753-540-820241009
Gentili, A. (2023). Leveraging Wi-Fi 6 and MPTCP for Efficient and Reliable Real-Time Video Streaming in Safe Port Monitoring. 2023 Joint European Conference on Networks and Communications and 6g Summit Eucnc 6g Summit 2023, Query date: 2025-08-22 02:44:20, 591–596. https://doi.org/10.1109/EuCNC/6GSummit58263.2023.10188277
Goslen, A. (2022). Leveraging Student Goal Setting for Real-Time Plan Recognition in Game-Based Learning. Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 13355(Query date: 2025-08-22 02:44:20), 78–89. https://doi.org/10.1007/978-3-031-11644-5_7
Harika, N. (2025). Leveraging YOLO Deep Learning for Real-Time Weed Detection with a Mini Rover. Proceedings of 3rd International Conference on Augmented Intelligence and Sustainable Systems Icaiss 2025, Query date: 2025-08-22 02:44:20, 1752–1757. https://doi.org/10.1109/ICAISS61471.2025.11041734
Hawlader, F. (2024). Leveraging the edge and cloud for V2X-based real-time object detection in autonomous driving. Computer Communications, 213(Query date: 2025-08-22 02:44:20), 372–381. https://doi.org/10.1016/j.comcom.2023.11.025
Ileana, M. (2025). Optimizing Customer Experience by Exploiting Real-Time Data Generated by IoT and Leveraging Distributed Web Systems in CRM Systems. Iot, 6(2). https://doi.org/10.3390/iot6020024
Isabel, X. (2023). Live Demonstration: A fully embedded adaptive real-time hand gesture classifier leveraging HD-sEMG and deep learning. Biocas 2023 2023 IEEE Biomedical Circuits and Systems Conference Conference Proceedings, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/BioCAS58349.2023.10388931
Kreitmann, L. (2023). Next-generation molecular diagnostics: Leveraging digital technologies to enhance multiplexing in real-time PCR. Trac Trends in Analytical Chemistry, 160(Query date: 2025-08-22 02:44:20). https://doi.org/10.1016/j.trac.2023.116963
Liu, J. (2025). Leveraging Time-Causal State Variable Aggregation for Real-Time Schedule of Massive Air Conditioners. IEEE Transactions on Smart Grid, 16(3), 2389–2403. https://doi.org/10.1109/TSG.2025.3547985
Mehnaz, F. (2024). MindWatch leveraging wearable technology for real-time monitoring and support of student mental health. Wearable Devices and Smart Technology for Educational Teaching Assistance, Query date: 2025-08-22 02:44:20, 233–255. https://doi.org/10.4018/979-8-3693-7817-5.ch009
O’Horo, J. C. (2024). Leveraging real-time patient data during the COVID-19 pandemic. Infection Control and Hospital Epidemiology, 45(10), 1257–1258. https://doi.org/10.1017/ice.2024.118
Padwal, S. (2024). Modernizing Agriculture with Real-Time Crop Insurance: Leveraging Blockchain, IoT, and Machine Learning. 2024 IEEE International Conference on Blockchain and Distributed Systems Security Icbds 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/ICBDS61829.2024.10837140
Pallawabonang, M. (2024). Leveraging YOLOv8 for Real-Time Parking Space Detection. 2024 Beyond Technology Summit on Informatics International Conference Bts I2c 2024, Query date: 2025-08-22 02:44:20, 439–444. https://doi.org/10.1109/BTS-I2C63534.2024.10942123
Parisio, F. (2024). LiveEO’s Rapid Response Insights: Leveraging high-resolution Capella Space SAR imagery to automate near-real-time storm damage detection. Proceedings of the European Conference on Synthetic Aperture Radar Eusar, Query date: 2025-08-22 02:44:20, 475–479.
Peixoto, Í. (2025). Leveraging Real-Time EEG Neurofeedback in Virtual Reality towards Personalized Interventions in Exposure Therapy. Proceedings 2025 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops Vrw 2025, Query date: 2025-08-22 02:44:20, 1512–1513. https://doi.org/10.1109/VRW66409.2025.00402
Phuong, N. A. (2024). Novel Semi-Nested Real-Time PCR Assay Leveraging Extendable Blocking Probes for Improved SHOX2 Methylation Analysis in Lung Cancer. Biomolecules, 14(6). https://doi.org/10.3390/biom14060729
Sánchez-Brizuela, G. (2023). Lightweight real-time hand segmentation leveraging MediaPipe landmark detection. Virtual Reality, 27(4), 3125–3132. https://doi.org/10.1007/s10055-023-00858-0
Sangolgi, V. (2025). Novel Framework for Real-Time Object Detection with Audio Output Leveraging YOLO and CNN. Smart Innovation Systems and Technologies, 440(Query date: 2025-08-22 02:44:20), 183–198. https://doi.org/10.1007/978-981-96-3420-0_16
Sonawane, A. (2025). Leveraging YOLO for Real-Time Human Detection and Pose Estimation in Live Stream Environments. 2025 International Conference on Computing and Communication Technologies Iccct 2025, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/ICCCT63501.2025.11020018
Sonone, N. (2024). LEVERAGING XGBOOST FOR ACCURATE PREDICTION OF CHRONIC KIDNEY DISEASE WITH REAL-TIME DATA. 2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies Inspect 2024, Query date: 2025-08-22 02:44:20. https://doi.org/10.1109/INSPECT63485.2024.10896080
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