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Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement
Staker, Heather; Horn, Michael B. – Innosight Institute, 2012
The growth of online learning in the K-12 sector is occurring both remotely through virtual schools and on campuses through blended learning. In emerging fields, definitions are important because they create a shared language that enables people to talk about the new phenomena. The blended-learning taxonomy and definitions presented in this paper…
Descriptors: Blended Learning, Definitions, Taxonomy, Elementary Secondary Education
Gates, Jillian C. – ProQuest LLC, 2011
This study involved the investigation of the effects of the Total Cluster Grouping Model on the achievement and identification of urban, elementary students and to learn about the classroom practices of and perceptions classroom teachers had of their students' ability levels over the course of the study. Proportionality of representation in…
Descriptors: Ethnicity, Socioeconomic Status, Investigations, Economic Status
Brulles, Dina; Saunders, Rachel; Cohn, Sanford J. – Journal for the Education of the Gifted, 2010
Although experts in gifted education widely promote cluster grouping gifted students, little empirical evidence is available to attest to its effectiveness. This study is an example of comparative action research in the form of a quantitative case study that focused on the mandated cluster grouping practices for gifted students in an urban…
Descriptors: Academically Gifted, Action Research, Mathematics Achievement, Cluster Grouping