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Ye, Cheng; Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam – International Educational Data Mining Society, 2015
This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features…
Descriptors: Learning Activities, Learning Processes, Data Collection, Student Behavior
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Bellocchi, Alberto; King, Donna T.; Ritchie, Stephen M. – International Journal of Science Education, 2016
There is on-going international interest in the relationships between assessment instruments, students' understanding of science concepts and context-based curriculum approaches. This study extends earlier research showing that students can develop connections between contexts and concepts--called "fluid transitions"--when studying…
Descriptors: Comparative Analysis, Student Reaction, Chemistry, Science Education
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers