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Yang, Xi; Zhou, Guojing; Taub, Michelle; Azevedo, Roger; Chi, Min – International Educational Data Mining Society, 2020
In the learning sciences, heterogeneity among students usually leads to different learning strategies or patterns and may require different types of instructional interventions. Therefore, it is important to investigate student subtyping, which is to group students into subtypes based on their learning patterns. Subtyping from complex student…
Descriptors: Grouping (Instructional Purposes), Learning Strategies, Artificial Intelligence, Learning Analytics
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Howlin, Colm P.; Dziuban, Charles D. – International Educational Data Mining Society, 2019
Clustering of educational data allows similar students to be grouped, in either crisp or fuzzy sets, based on their similarities. Standard approaches are well suited to identifying common student behaviors; however, by design, they put much less emphasis on less common behaviors or outliers. The approach presented in this paper employs fuzzing…
Descriptors: Data Collection, Student Behavior, Learning Strategies, Feedback (Response)
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Pond, Jarrad W. T.; Chini, Jacquelyn J. – Physical Review Physics Education Research, 2017
In this study, we explore the strategic self-regulatory and motivational characteristics of students in studio-mode physics courses at three universities with varying student populations and varying levels of success in their studio-mode courses. We survey students using questions compiled from several existing questionnaires designed to measure…
Descriptors: Algebra, Physics, Profiles, Student Characteristics
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Barata, Gabriel; Gama, Sandra; Jorge, Joaquim; Gonçalves, Daniel – International Journal of Game-Based Learning, 2014
Gamification of education is a recent trend, and early experiments showed promising results. Students seem not only to perform better, but also to participate more and to feel more engaged with gamified learning. However, little is known regarding how different students are affected by gamification and how their learning experience may vary. In…
Descriptors: Educational Games, Learning Experience, College Students, Learning Strategies
Aagaard, Lola; Skidmore, Ronald L.; Conner, Timothy W., II – Online Submission, 2014
The purpose of this study was to investigate the relationship between academic self-efficacy and preferences regarding the use of text materials and in-class activities of college students at a university that serves one of the highest-poverty regions in the United States. A convenient cluster sample of 105 students taking summer classes at a…
Descriptors: College Students, Self Efficacy, Textbooks, Preferences
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Chan, Julia Y. K.; Bauer, Christopher F. – Chemistry Education Research and Practice, 2016
Students in general chemistry were partitioned into three groups by cluster analysis of six affective characteristics (emotional satisfaction, intellectual accessibility, chemistry self-concept, math self-concept, self-efficacy, and test anxiety). The at-home study strategies for exam preparation and in-class learning strategies differed among the…
Descriptors: Learning Strategies, Cognitive Style, Chemistry, Affective Behavior
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Waring, Robert – System, 1997
Examines the effects of learning words grouped in semantic sets, using Japanese words paired with artificial words. A principal finding was that there was a main effect against learning semantically related words at the same time. The article concludes that presenting students with wordlists of new words in semantic clusters, rather than in…
Descriptors: Adult Students, Cluster Grouping, College Students, Foreign Countries
Weinstein, Claire E.; And Others – 1980
Three studies were performed to investigate the effects of training versus instructions in the acquisition of cognitive learning strategies. Groups of undergraduate students were taught to use one or more strategies. The amount and type of training differed for each of the experimental groups. Strategies taught included the method of loci,…
Descriptors: Cluster Grouping, College Students, Drills (Practice), Feedback