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Transformative Inclusive Education: A Case Study of an AI Game-Based Deep Learning Model for Literacy among
Minsih1, Coiriyah Widyasari2, Ratnasari Diah Utami2
1Elementary Education, Universitas Muhammadiyah Surakarta, Surakarta, Central Java, Indonesia.
Background:
Inclusive students with Specific Learning Disorder (SLD) often experience persistent challenges in acquiring foundational literacy skills due to the lack of adaptive and personalized instructional approaches. Artificial Intelligence (AI) game-based deep learning models offer a promising alternative by enabling individualized learning pathways and continuous feedback. However, the integration of such models within inclusive primary school settings remains underexplored, particularly in Indonesia.
Methods:
This study employed a descriptive qualitative approach using a case study design to investigate the relevance and potential of AI game-based deep learning for literacy development among students with SLD. Data were collected through document analysis, review of scientific publications, and examination of related empirical studies. The collected data were analyzed using qualitative content analysis to identify key themes, conceptual patterns, and implications for inclusive literacy instruction.
Results:
The findings reveal three central insights. First, the adoption of AI game-based deep learning models is urgently needed to address the persistent literacy gaps among inclusive students with SLD. Second, such models demonstrate strong potential in supporting individualized literacy learning, particularly through features such as adaptive difficulty levels, automated feedback, and multimodal engagement. Third, the approach aligns well with the context of Indonesian primary schools, offering a feasible and pedagogically relevant tool for inclusive classrooms. The study also highlights the novelty of conceptualizing AI game-based deep learning not merely as a technological innovation but as a context-sensitive pedagogical model tailored to learners' needs.
Conclusions:
AI game-based deep learning models hold significant promise for enhancing literacy outcomes among primary school students with SLD. Their adaptive and personalized nature provides meaningful support for inclusive education, helping to reduce learning barriers and promote equitable literacy development. Further research and pilot implementation are recommended to strengthen evidence-based adoption in schools.
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