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Barata, Gabriel; Gama, Sandra; Jorge, Joaquim; Gonçalves, Daniel – IEEE Transactions on Learning Technologies, 2016
State of the art research shows that gamified learning can be used to engage students and help them perform better. However, most studies use a one-size-fits-all approach to gamification, where individual differences and needs are ignored. In a previous study, we identified four types of students attending a gamified college course, characterized…
Descriptors: Prediction, Performance, Profiles, Games
Soh, Kay Cheng – Higher Education Review, 2012
Three university ranking systems in vogue have been shown in the previous issue of "Higher Education Review" to be capable of modifications to make them more parsimonious by using only about half of the number of predictors currently in use. This makes some of the predictors "redundant" as they contributed little to the overall ranking. It is…
Descriptors: Higher Education, Predictor Variables, Profiles, Test Items
Eynon, Rebecca; Malmberg, Lars-Erik – Computers & Education, 2011
Using data from a nationally representative survey of over a 1000 young people in the UK this paper proposes a typology of the ways young people are using the Internet outside formal educational settings; and examines the individual and contextual factors that help to explain why young people are using the Internet in this way. Specifically, this…
Descriptors: Individual Characteristics, Young Adults, Classification, Profiles
Keat, Donald B., II; Hackman, Roy B. – Measurement and Evaluation in Guidance, 1972
Individuals were grouped into person clusters on the basis of the similarity of their inventory profiles. In any particular profile cluster, homogeneous groups (by curriculum areas) of individuals tend to group into attraction patterns (presence in profile cluster) and avoidance patterns (absence from profile cluster). (Author)
Descriptors: Classification, Cluster Analysis, Cluster Grouping, College Students

Pickett, Lawrence K., Jr. – Criminal Justice and Behavior, 1981
The MMPI results obtained from 245 adolescent males referred to the evaluation unit of a Juvenile Court were submitted to a multivariate classification system. By correlating individual subject profiles with the modal profiles, six membership groups were formed. No relationship was found between group membership and age or race. (Author)
Descriptors: Adolescents, Age, Classification, Cluster Grouping