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Mengjiao Yin; Hengshan Cao; Zuhong Yu; Xianyu Pan – International Journal of Web-Based Learning and Teaching Technologies, 2024
This study presents the Academic Investment Model (AIM) as a novel approach to predicting student academic performance by incorporating learning styles as a predictive feature. Utilizing data from 138 Marketing students across China, the research employs a combination of machine learning clustering methods and manual feature engineering through a…
Descriptors: Predictor Variables, Artificial Intelligence, Performance, Cluster Grouping
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Morais, Jorge E.; Forte, Pedro; Silva, Antonio J.; Barbosa, Tiago M.; Marinho, Daniel A. – Research Quarterly for Exercise and Sport, 2021
Purpose: The aims of this study were to classify, identify and follow-up young swimmers' performance and its biomechanical determinants during two competitive seasons (in seven different moments of assessment--M), and analyze the individual variations of each swimmer. Method: Thirty young swimmers (14 boys: 12.70 ± 0.63 years-old; 16 girls:…
Descriptors: Aquatic Sports, Performance, Biomechanics, Reliability
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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
DUNN, JAMES A.; SCHELKUN, RUTH F. – 1967
THE RELATIONSHIPS BETWEEN SCHOOL GENERATED ANXIETY AND VARIOUS INDICES OF SCHOOL ACHIEVEMENT, CREATIVITY, AGE, AND IQ, ARE INVESTIGATED. A 160 ITEM, MULTIPLE-CHOICE, MULTI-SCALE, SCHOOL ANXIETY QUESTIONNAIRE WAS ADMINISTERED TO 56 FOURTH, FIFTH, AND SIXTH GRADE CHILDREN WITH A MEAN STANFORD BINET IQ OF 126 FROM AN UPPER MIDDLE CLASS COMMUNITY.…
Descriptors: Anxiety, Cluster Grouping, Creativity, Elementary School Students
Rarick, G. Lawrence; Dobbins, D. Alan – 1974
A motor performance typology of boys and girls (ages 6-10 years) was developed, based on four factors extracted by factor analysis from data on 47 physical growth and motor performance variables. Nineteen variables which best described the four factor-defined components were used in formulating the person-clusters (typologies) following Tryon's…
Descriptors: Child Development, Children, Classification, Cluster Grouping
Munce, John W. – 1982
A skills model and clustering system are presented, based on the assumptions that the tasks of all work, including scholarship, require many similar skills that can be identified and clustered. Six levels of competency are addressed: possession, combination, application, quantity, quality, and mastery. These skills can be clustered into adaptive…
Descriptors: Check Lists, Cluster Grouping, College Students, Competence