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Zhang, Dake; Stecker, Pamela; Huckabee, Sloan; Miller, Rhonda – Journal of Learning Disabilities, 2016
Research has suggested that different strategies used when solving fraction problems are highly correlated with students' problem-solving accuracy. This study (a) utilized latent profile modeling to classify students into three different strategic developmental levels in solving fraction comparison problems and (b) accordingly provided…
Descriptors: Middle School Students, Fractions, Mathematics Achievement, Low Achievement
van Viersen, Sietske; de Bree, Elise H.; Kalee, Lilian; Kroesbergen, Evelyn H.; de Jong, Peter F. – Reading and Writing: An Interdisciplinary Journal, 2017
A few studies suggest that gifted children with dyslexia have better literacy skills than averagely intelligent children with dyslexia. This finding aligns with the hypothesis that giftedness-related factors provide compensation for poor reading. The present study investigated whether, as in the native language (NL), the level of foreign language…
Descriptors: Foreign Countries, Second Language Learning, Reading Instruction, Spelling Instruction
Sao Pedro, Michael; Jiang, Yang; Paquette, Luc; Baker, Ryan S.; Gobert, Janice – Grantee Submission, 2014
Students conducted inquiry using simulations within a rich learning environment for 4 science topics. By applying educational data mining to students' log data, assessment metrics were generated for two key inquiry skills, testing stated hypotheses and designing controlled experiments. Three models were then developed to analyze the transfer of…
Descriptors: Simulation, Transfer of Training, Bayesian Statistics, Inquiry
Sabourin, Jennifer L.; Rowe, Jonathan P.; Mott, Bradford W.; Lester, James C. – Journal of Educational Data Mining, 2013
Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as off-task behavior, has shown considerable promise for understanding students' motivational characteristics during learning. In this paper, we…
Descriptors: Student Behavior, Classification, Learner Engagement, Data Analysis
Rai, Dovan; Gong, Yue; Beck, Joseph E. – International Working Group on Educational Data Mining, 2009
Student modeling is a widely used approach to make inference about a student's attributes like knowledge, learning, etc. If we wish to use these models to analyze and better understand student learning there are two problems. First, a model's ability to predict student performance is at best weakly related to the accuracy of any one of its…
Descriptors: Data Analysis, Statistical Analysis, Probability, Models
Johnson, Matthew S.; Jenkins, Frank – ETS Research Report Series, 2005
Large-scale educational assessments such as the National Assessment of Educational Progress (NAEP) sample examinees to whom an exam will be administered. In most situations the sampling design is not a simple random sample and must be accounted for in the estimating model. After reviewing the current operational estimation procedure for NAEP, this…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, National Competency Tests, Sampling