SensorAble_ ML_DL and Autistic Neurocognitive Processes
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SensorAble_ ML_DL and Autistic Neurocognitive Processes
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The research paper "Refining the ML/DL Argument for the SensorAble Project" by Dr David Ruttenberg and others who investigate the application of Machine Learning (ML) and Deep Learning (DL) within the SensorAble project to better understand and support autistic individuals.
The authors propose using Multimodal Learning Analytics (MMLA) to capture diverse sensory data related to distractibility and anxiety in autistic individuals. The study explores whether ML/DL is essential for processing this complex, multi-sourced data to model neurocognitive processes or if more traditional Artificial Intelligence (AI) methods would suffice.
Ultimately, the paper aims to frame research questions that align MMLA, ML/DL, and SensorAble to develop practical tools, while also considering ethical implications and the balance between heuristic and analytic decision-making processes.