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Download full textCrossley, Scott A.; Karumbaiah, Shamya; Ocumpaugh, Jaclyn; Labrum, Matthew J.; Baker, Ryan S. – Journal of Learning Analytics, 2020
This study builds on prior research by leveraging natural language processing (NLP), click-stream analyses, and survey data to predict students' mathematics success and math identity (namely, self-concept, interest, and value of mathematics). Specifically, we combine NLP tools designed to measure lexical sophistication, text cohesion, and…
Descriptors: Elementary School Mathematics, Blended Learning, Self Concept, Audience Response Systems
Crossley, Scott; Ocumpaugh, Jaclyn; Labrum, Matthew; Bradfield, Franklin; Dascalu, Mihai; Baker, Ryan S. – International Educational Data Mining Society, 2018
A number of studies have demonstrated strong links between students' language features (as found in spoken and written production) and their math performance. However, no studies have examined links between the students' language features and measures of their Math Identity. This project extends prior studies that use natural language processing…
Descriptors: Correlation, Speech Communication, Written Language, Mathematics Achievement
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
