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Download full textLiu, Ran; Stamper, John; Davenport, Jodi – Journal of Learning Analytics, 2018
Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…
Descriptors: Intelligent Tutoring Systems, Learning, Data Analysis, Student Development
Direct linkLiu, Ran; Stamper, John; Davenport, Jodi – Grantee Submission, 2018
Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…
Descriptors: Intelligent Tutoring Systems, Learning, Data Analysis, Student Development
Gee, Kevin A. – American Journal of Evaluation, 2014
The growth in the availability of longitudinal data--data collected over time on the same individuals--as part of program evaluations has opened up exciting possibilities for evaluators to ask more nuanced questions about how individuals' outcomes change over time. However, in order to leverage longitudinal data to glean these important insights,…
Descriptors: Longitudinal Studies, Data Analysis, Statistical Studies, Program Evaluation
