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Xiaoman Wang; Rui Huang; Max Sommer; Bo Pei; Poorya Shidfar; Muhammad Shahroze Rehman; Albert D. Ritzhaupt; Florence Martin – Journal of Educational Computing Research, 2024
The purpose of this research study was to examine the overall effect of adaptive learning systems deployed using artificial intelligence technology across a range of relevant variables (e.g., duration, student level, etc.). Following a systematic procedure, this meta-analysis examined literature from 18 academic databases and identified N = 45…
Descriptors: Meta Analysis, Outcomes of Education, Artificial Intelligence, Learning Management Systems
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Rennie, Joseph P.; Zhang, Mengya; Hawkins, Erin; Bathelt, Joe; Astle, Duncan E. – Developmental Science, 2020
We used two simple unsupervised machine learning techniques to identify differential trajectories of change in children who undergo intensive working memory (WM) training. We used self-organizing maps (SOMs)--a type of simple artificial neural network--to represent multivariate cognitive training data, and then tested whether the way tasks are…
Descriptors: Short Term Memory, Teaching Methods, Artificial Intelligence, Cognitive Development
Vandendorpe, Mary M. – 1985
This paper discusses a model of information storage and retrieval, the k-d tree (Bentley, 1975), a binary, hierarchical tree with multiple associate terms, which has been explored in computer research, and it is suggested that this model could be useful for describing human cognition. Included are two models of human long-term memory--networks and…
Descriptors: Artificial Intelligence, Cognitive Development, Cognitive Processes, Comparative Analysis