This thesis analyzes Specific Learning Disorders (SLD) within an integrated theoretical framework that considers the interaction between biological and environmental factors in determining individual functioning profiles. Moving beyond a purely deficit-based perspective, SLD is interpreted as the expression of dynamic processes, influenced by contextual variables and flexible, modifiable developmental mechanisms.
Particular attention is paid to the contribution of epigenetics, which highlights how environmental factors—such as stress, socio-educational context, and the quality of early experiences—can modulate gene expression and impact learning processes. From this perspective, individual functioning is seen as the result of a balance between vulnerabilities and resources, continually influenced by the environment.
Within this framework, the thesis explores the role of digital technologies and, in particular, artificial intelligence, interpreted not only as a compensatory tool but as an active component of the learning environment. AI-based systems, through adaptive and personalized mechanisms, can impact the conditions for accessing knowledge, supporting cognitive processes and reducing performance barriers.
The results of the theoretical reflection highlight how the integration of biological and environmental factors—including emerging technologies—allows for more inclusive, equitable, and effective educational practices, promoting equal opportunities and enhancing the potential of students with learning disabilities.
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