文章基本信息

标题：Predicting Math Success in an Online Tutoring System Using Language Data and Click-Stream Variables: A Longitudinal Analysis
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作者：Scott Crossley ; Shamya Karumbaiah ; Jaclyn Ocumpaugh 等
期刊名称：OASIcs : OpenAccess Series in Informatics
电子版ISSN：2190-6807
出版年度：2019
卷号：70
页码：25:1-25:13
DOI：10.4230/OASIcs.LDK.2019.25
出版社：Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
摘要：Previous studies have demonstrated strong links between students' linguistic knowledge, their affective language patterns and their success in math. Other studies have shown that demographic and click-stream variables in online learning environments are important predictors of math success. This study builds on this research in two ways. First, it combines linguistics and click-stream variables along with demographic information to increase prediction rates for math success. Second, it examines how random variance, as found in repeated participant data, can explain math success beyond linguistic, demographic, and click-stream variables. The findings indicate that linguistic, demographic, and click-stream factors explained about 14% of the variance in math scores. These variables mixed with random factors explained about 44% of the variance.
关键词：Natural language processing; math education; online tutoring systems; text analytics; click-stream variables