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Direct linkBarbieri, Christina Areizaga; Young, Laura K.; Newton, Kristie J.; Booth, Julie L. – Child Development, 2021
Fraction knowledge and algebraic skill are closely linked. Algebra is a gatekeeper for advanced courses (Booth & Newton, 2012; Brown & Quinn, 2007). This study uses the person-centered approach of latent profile analysis to examine individual differences in middle schoolers' (N = 350) algebra performance at the end of the year (EOY). The…
Descriptors: Prediction, Middle School Students, Algebra, Mathematics Instruction
Siegelman, Noam; Rueckl, Jay G.; Lo, Jason Chor Ming; Kearns, Devin M.; Morris, Robin D.; Compton, Donald L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
Statistical views of reading highlight the link between proficient literacy and the assimilation of various regularities embedded in writing systems, including those in the mapping between print and meaning. Still, orthographic-semantic (O-S) regularities remain relatively understudied, with open questions regarding 3 issues: (a) how O-S…
Descriptors: Orthographic Symbols, Semantics, Reading Skills, Prediction
Download full textMaria Bempeni; Stavroula Poulopoulou; Xenia Vamvakoussi – Online Submission, 2021
In the present study, we tested the hypotheses that: a) there are individual differences in secondary students' conceptual and procedural fraction knowledge, and b) these differences are predicted by students' approach (deep vs. surface) to mathematics learning. We used two instruments developed and evaluated for the purposes of the study which…
Descriptors: Mathematics Instruction, Teaching Methods, Prediction, Learning Processes
Dale, Philip S.; Paul, Alexander; Rosholm, Michael; Bleses, Dorthe – International Journal of Behavioral Development, 2023
Prediction from early development to later achievement has the potential to improve clinical and educational service delivery as well as to inform developmental theory. In this longitudinal study, we asked how well can educational achievement measured in the final year (Grade 9, age 15) of compulsory education--both overall and for outcomes in the…
Descriptors: Prediction, Child Development, Vocabulary Development, Academic Achievement
Khajah, Mohammad; Lindsey, Robert V.; Mozer, Michael C. – International Educational Data Mining Society, 2016
In theoretical cognitive science, there is a tension between highly structured models whose parameters have a direct psychological interpretation and highly complex, general-purpose models whose parameters and representations are difficult to interpret. The former typically provide more insight into cognition but the latter often perform better.…
Descriptors: Bayesian Statistics, Data Analysis, Prediction, Intelligent Tutoring Systems
Yli-Piipari, Sami; Leskinen, Esko; Jaakkola, Timo; Liukkonen, Jarmo – Research Quarterly for Exercise and Sport, 2012
In this study we examined adolescents' physical activity (PA) stability as well as individual differences in PA across grades 7-9. In addition, we tested the predictive role of adolescents' self-determination and goal orientations in physical education at grade 6 in relation to their PA development. Adolescents' (N = 812) self-reported PA was…
Descriptors: Motivation, Physical Activity Level, Adolescents, Junior High School Students
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
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
