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Download full textLabutov, Igor; Lipson, Hod – International Educational Data Mining Society, 2016
A growing subset of the web today is aimed at "teaching" and "explaining" technical concepts with varying degrees of detail and to a broad range of target audiences. Content such as tutorials, blog articles and lecture notes is becoming more prevalent in many technical disciplines and provides up-to-date technical coverage with…
Descriptors: Educational Resources, Internet, Sequential Learning, Classification
Ng, Kelvin H. R.; Hartman, Kevin; Liu, Kai; Khong, Andy W. H. – International Educational Data Mining Society, 2016
During the semester break, 36 second-grade students accessed a set of resources and completed a series of online math activities focused on the application of the model method for arithmetic in two contexts 1) addition/subtraction and 2) multiplication/division. The learning environment first modeled and then supported the use of a scripted series…
Descriptors: Word Problems (Mathematics), Mathematics Instruction, Arithmetic, Problem Solving
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
