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Luz, Yael; Yerushalmy, Michal – Journal for Research in Mathematics Education, 2023
We report on an innovative design of algorithmic analysis that supports automatic online assessment of students' exploration of geometry propositions in a dynamic geometry environment. We hypothesized that difficulties with and misuse of terms or logic in conjectures are rooted in the early exploration stages of inquiry. We developed a generic…
Descriptors: Algorithms, Computer Assisted Testing, Geometry, Mathematics Instruction
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Levin, Nathan A. – Journal of Educational Data Mining, 2021
The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…
Descriptors: Learning Analytics, Data Collection, Competition, Prediction
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Matayoshi, Jeffrey; Uzun, Hasan; Cosyn, Eric – International Educational Data Mining Society, 2022
Knowledge space theory (KST) is a mathematical framework for modeling and assessing student knowledge. While KST has successfully served as the foundation of several learning systems, recent advancements in machine learning provide an opportunity to improve on purely KST-based approaches to assessing student knowledge. As such, in this work we…
Descriptors: Knowledge Level, Mathematical Models, Learning Experience, Comparative Analysis
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Chen, Jianlin – International Journal of Bilingual Education and Bilingualism, 2020
The parasitic model proposes that novel words in L3 learning will build parasitic connections to already learned words that share orthographic or phonological similarities. This accounts for little in terms of the connections between words that share very few similarities. The present study explored the parasitic connections of L3 word concepts to…
Descriptors: Multilingualism, Native Language, Second Language Learning, English (Second Language)
Northwest Evaluation Association, 2016
Northwest Evaluation Association™ (NWEA™) is committed to providing partners with useful tools to help make inferences from the Measures of Academic Progress® (MAP®) interim assessment scores. One important tool is the concordance table between MAP and state summative assessments. Concordance tables have been used for decades to relate scores on…
Descriptors: Scores, Inferences, Academic Achievement, Achievement Tests
Northwest Evaluation Association, 2016
Northwest Evaluation Association™ (NWEA™) is committed to providing partners with useful tools to help make inferences from the Measures of Academic Progress® (MAP®) interim assessment scores. One important tool is the concordance table between MAP and state summative assessments. Concordance tables have been used for decades to relate scores on…
Descriptors: Scores, Inferences, Academic Achievement, Achievement Tests
Northwest Evaluation Association, 2016
Northwest Evaluation Association™ (NWEA™) is committed to providing partners with useful tools to help make inferences from the Measures of Academic Progress® (MAP®) interim assessment scores. Recently, NWEA completed a concordance study to connect the scales of the Virginia Standards of Learning (SOL) reading and math tests with those of the MAP…
Descriptors: Scores, Inferences, Academic Achievement, Achievement Tests
Northwest Evaluation Association, 2016
Northwest Evaluation Association™ (NWEA™) is committed to providing partners with useful tools to help make inferences from the Measures of Academic Progress® (MAP®) interim assessment scores. Recently, NWEA completed a concordance study to connect the scales of the North Carolina End-of-Grade (EOG) English language arts (ELA) and math with those…
Descriptors: Scores, Inferences, Academic Achievement, Achievement Tests
Northwest Evaluation Association, 2016
Northwest Evaluation Association™ (NWEA™) is committed to providing partners with useful tools to help make inferences from the Measures of Academic Progress® (MAP®) interim assessment scores. One important tool is the concordance table between MAP and state summative assessments. Concordance tables have been used for decades to relate scores on…
Descriptors: Scores, Inferences, Academic Achievement, Achievement Tests
Northwest Evaluation Association, 2016
Northwest Evaluation Association™ (NWEA™) is committed to providing partners with useful tools to help make inferences from the Measures of Academic Progress® (MAP®) interim assessment scores. One important tool is the concordance table between MAP and state summative assessments. Concordance tables have been used for decades to relate scores on…
Descriptors: Scores, Inferences, Academic Achievement, Achievement Tests
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries
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