Implementation of Deep Learning Technology in Adaptive Learning Models Using Smart Learning for Students with Special Needs at SMK -PPI Bandung
DOI:
https://doi.org/10.70825/jptb.v7i2.2353Keywords:
deep learning, adaptive learning, students with special needs (SBK), inclusive education, smart learningAbstract
This community service program focuses on ensuring equal access to education for SBK through the use of advanced technology. The methodology begins with identifying the specific needs of SBK through observation and interviews to understand the challenges they face, followed by collaboration with the school and technology developers to design suitable solutions. Intensive training on Deep Learning (DL) technology and inclusive teaching strategies is provided to SMK-PPI teachers, introducing concepts such as Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), and image processing to support the learning process. The DL-based learning model is then implemented in classrooms involving SBK, with a focus on personalized learning content and more inclusive teaching methods. Continuous evaluation through data collection from observations, interviews, and surveys demonstrates improvements in student engagement, material accessibility, and learning outcomes for SBK. Based on feedback from both teachers and students, reflections and adjustments are made to ensure the sustainability of this model at SMK-PPI and its potential replication in other schools. This program is expected to make a significant contribution to strengthening inclusive education at SMK-PPI Bandung, ensuring that all students have an equal opportunity to reach their full potential.
References
Jansen, B., Smith, R., & Taylor, A., 2020. Artificial Intelligence in Inclusive Education: Trends and Challenges. Educational Technology Research and Development, 68(5), pp. 2561-2578.
Poon, W., Lee, M., & Sutherland, D., 2021. Deep Learning in Education: Applications and Approaches for Students with Special Needs. Journal of Educational Technology & Society, 24(1), pp. 52-63.
Thomas, M., & Lauder, H., 2018. Educational Technology and its Impact on Students with Special Needs. Computers & Education, 116, pp. 134-145.
Anderson, C., & McGreal, R., 2019. Personalized Learning: A Review of the Technology and Its Impact on Special Education. International Journal of Educational Technology, 26(2), pp. 82-97.
Kaur, A., & Singh, G., 2020. The Role of Deep Learning in Personalized Learning Environments. Journal of Educational Computing Research, 58(3), pp. 586-602.
Salminen, J., & Kukul, L., 2021. Leveraging Natural Language Processing (NLP) for Inclusive Education: Case Studies and Applications. Journal of Artificial Intelligence in Education, 31(4), pp. 111-123.
Zhang, X., & Liu, Y., 2017. Machine Learning and Special Education: A New Era of Adaptive Learning Systems. Educational Media International, 54(3), pp. 186-199.
Jenkins, C., & Moore, C., 2019. The Impact of AI and Deep Learning on Inclusive Education. Computers in Human Behavior, 96, pp. 98-112.
Ford, D., & Meyer, L., 2018. Training Teachers for Technology Integration in Inclusive Classrooms. International Journal of Inclusive Education, 22(10), pp. 1021-1035.
Wang, F., & Liu, M., 2020. Deep Learning Technologies for Special Education in Schools: Challenges and Solutions. International Journal of Educational Technology, 14(2), pp. 48-61.
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