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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
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Fernandes Malaquias, Rodrigo; de Oliveira Malaquias, Fernanda Francielle – Turkish Online Journal of Distance Education, 2014
The objective of this study was to validate a scale for assessment of academic projects. As a complement, we examined its predictive ability by comparing the scores of advised/corrected projects based on the model and the final scores awarded to the work by an examining panel (approximately 10 months after the project design). Results of…
Descriptors: Predictive Measurement, Predictive Validity, Predictor Variables, Test Construction
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Koys, Daniel – Journal of Education for Business, 2010
The author found that the GPA at the end of the MBA program is most accurately predicted by the Graduate Management Admission Test (GMAT) and the Test of English as a Foreign Language (TOEFL). MBA GPA is also predicted, though less accurately, by the Scholastic Level Exam, a mathematics test, undergraduate GPA, and previous career progression. If…
Descriptors: Grade Point Average, Predictive Validity, Prediction, Foreign Countries
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Goodman, Anna; Ford, Tamsin – Research in Education, 2008
Emotional and behavioural difficulties (EBD) are common in children, and forecasting their prevalence in schools is of interest to both academic researchers and local authorities. Percentage of pupils eligible for free school meals is one measure often used for this purpose. The article presents the first independent validation of a simple…
Descriptors: Mental Disorders, Well Being, Mental Health, Disadvantaged