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Hyunkyung Chee; Solmoe Ahn; Jihyun Lee – British Journal of Educational Technology, 2025
This study aims to develop a comprehensive competency framework for artificial intelligence (AI) literacy, delineating essential competencies and sub-competencies. This framework and its potential variations, tailored to different learner groups (by educational level and discipline), can serve as a crucial reference for designing and implementing…
Descriptors: Competence, Digital Literacy, Artificial Intelligence, Technology Uses in Education
Hinton, Geoffrey E. – Scientific American, 1992
Discusses computational studies of learning in artificial neural networks and findings that may provide insights into the learning abilities of the human brain. Describes efforts to test theories about brain information processing, using artificial neural networks. Vignettes include information concerning how a neural network represents…
Descriptors: Algorithms, Artificial Intelligence, Cognitive Processes, Experiments
Peer reviewedSfard, Anna – Educational Studies in Mathematics, 1991
This paper presents a theoretical framework for investigating the role of algorithms in mathematical thinking using a combined ontological-psychological outlook. The intent is to demonstrate that the processes of learning and of problem solving incorporate an elaborate interplay between operational and structural conceptualizations of the same…
Descriptors: Algorithms, Cognitive Development, Cognitive Structures, Concept Formation
Peer reviewedScanlan, David; Clark, Leisa – Journal of Computers in Mathematics and Science Teaching, 1989
Studies whether students' stated preferences for flowcharts or pseudocodes match their actual behaviors. Provides a review of the literature on flowchart utility. Reports that students preferred flowcharts to pseudocodes. Lists an example of both a flowchart and pseudocode. (MVL)
Descriptors: Algorithms, Charts, College Mathematics, Computer Science Education

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