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A Contextualized, Differential Sequence Mining Method to Derive Students' Learning Behavior Patterns
Peer reviewed
Download full textKinnebrew, John S.; Loretz, Kirk M.; Biswas, Gautam – Journal of Educational Data Mining, 2013
Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially…
Descriptors: Data Analysis, Middle School Students, Information Retrieval, Student Behavior
McBroom, Charles T., Jr.; And Others – 1972
How Tennessee County Extension personnel spent their time in Fiscal Year 1970 and 1971 and how they planned their time in Fiscal Year 1971 are discussed in this master's thesis. Information on planned and expended time was retrieved through TEMIS (Tennessee Extension Management Information System). Wide variations were found to exist between time…
Descriptors: Data Processing, Extension Agents, Information Processing, Information Retrieval
