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Maarten van der Velde; Malte Krambeer; Hedderik van Rijn – International Educational Data Mining Society, 2025
Ensuring the integrity of results in online learning and assessment tools is a challenge, due to the lack of direct supervision increasing the risk of fraud. We propose and evaluate a machine learning-based method for detecting anomalous behaviour in an online retrieval practice task, using an XGBoost classifier trained on keystroke dynamics and…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Behavior, Information Retrieval
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Trezise, Kelly; Ryan, Tracii; de Barba, Paula; Kennedy, Gregor – Journal of Learning Analytics, 2019
Rural teachers and educators are increasingly called upon to build partnerships with families who use languages other than English in the home (US DOE, 2016). This is equally true for rural schools, where the number of multilingual families is small, and the language and cultural backgrounds of students differs from those of school. This article…
Descriptors: College Students, Cheating, Identification, Learning Analytics