Kaitlin A Oswald-McCloskey, Nicole Kubinec, Elizabeth Johnson, Alice Coffey, Kimberley P Heinrich
Teacher Perspectives of Pediatric Neuropsychology and Supporting Children With Chronic Health Conditions
Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists
context covid19 global pandemic highly intense frequent online teaching leapt one dominant learning patterns become ordinary situation university teaching practices recent years progress feature engineering machine learning made possible effective educational data mining turn enhanced performance intelligent learning models however potential impact increasing varying features online instruction new situation makes unclear whether existing related findings results practical teachers article use various stateoftheart machine learning techniques predict students performance based validation rationality built models importance features different feature selection techniques calculated separately datasets two groups compared features beginning pandemic results show current new state highly intense online learning without considering student information demographic information campus attributes administrative class teaching class learning behavior completion online learning tasks stage tests dynamic features likely discriminate students academic performances deserves attention demographics teachers guidance students learning addition suggested improvements refinements made existing features classifying features precisely expanding feature categories taking account statistics students inclass performances well subjective understanding learned findings line new situation pandemic provide implications teachers teaching guidance