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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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Wu, Sheng-Yi; Hou, Huei-Tse; Hwang, Wu-Yuin; Liu, Eric Zhi-Feng – Journal of Educational Computing Research, 2013
Both asynchronous and synchronous discussions have advantages and limitations for online learning. This study conducts an empirical analysis of these discussion activities while applying the proposed Seamless Online Learning Integrated Discussion (SOLID) system, which can instantly integrate Facebook's asynchronous discussion function with the MSN…
Descriptors: Problem Solving, Active Learning, Student Projects, Student Behavior
Lee, Woon Jee – ProQuest LLC, 2012
The purpose of this study was to explore the nature of students' mapping and discourse behaviors while constructing causal maps to articulate their understanding of a complex, ill-structured problem. In this study, six graduate-level students were assigned to one of three pair groups, and each pair used the causal mapping software program,…
Descriptors: Student Behavior, Graduate Students, Maps, Computer Uses in Education
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection