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Chiu, Ming Ming – Journal of Learning Analytics, 2018
Learning analysts often consider whether learning processes across time are related (1) to one another or (2) to learning outcomes at higher levels. For example, are a group's temporal sequences of talk (e.g., correct evaluation [right arrow] correct, new idea) during its problem solving related to its group solution? I show how to address these…
Descriptors: Statistical Analysis, Models, Data Analysis, Regression (Statistics)
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Allen, Jeff – Applied Measurement in Education, 2017
Using a sample of schools testing annually in grades 9-11 with a vertically linked series of assessments, a latent growth curve model is used to model test scores with student intercepts and slopes nested within school. Missed assessments can occur because of student mobility, student dropout, absenteeism, and other reasons. Missing data…
Descriptors: Achievement Gains, Academic Achievement, Growth Models, Scores
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Möller, Jens; Zimmermann, Friederike; Köller, Olaf – British Journal of Educational Psychology, 2014
Background: The reciprocal I/E model (RI/EM) combines the internal/external frame of reference model (I/EM) with the reciprocal effects model (REM). The RI/EM extends the I/EM longitudinally and the REM across domains. The model predicts that, within domains, mathematics and verbal achievement (VACH) and academic self-concept have positive effects…
Descriptors: Self Concept, Mathematics Achievement, Verbal Ability, Validity
Giorgio, Dorian – ProQuest LLC, 2012
Educational experts have criticized status models of school accountability, as required by the No Child Left Behind Act (NCLB), describing them as ineffectual in measuring achievement because their one-time assessment of student knowledge ignores student growth. Research on student achievement has instead identified growth models as superior…
Descriptors: Hierarchical Linear Modeling, Academic Achievement, Achievement Gains, Models