Abstract Learning environments such as classrooms and online systems for students with developmental or intellectual disabilities are typically dynamic, multisensory, and make use of top-down attention and working memory mechanisms to promote sense making by the student. However, the last five years have ushered a revolution in computational power, brain mapping, wearable sensors use, large scale data collection, generative artificial intelligence, and physiological signal processing techniques e.g., the 4th industrial revolution. Owing to the advent of inexpensive and highly accurate sensor technologies, generative artificial intelligence, and neurotechnologies, educators now have a new way to assess every student’s learning status, cognitive states, and promote adaption in a multi-modal and multi-dimensional way in real-time. Process data from sensors and neurotechnologies can be available for use by educators within milliseconds as opposed to minutes, hours, or days, as is the case for traditional educational data. Data from artificially intelligent systems can tracks students’ learning progressions using sensor-based data so that content adjustments and differentiation of instruction can meet a student’s needs in real-time. Keywords: Artificial Intelligence, Online Learning, Wearable Sensors, Special Education, Adaptive Learning.