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Toprak, Emre; Gelbal, Selahattin – International Journal of Assessment Tools in Education, 2020
This study aims to compare the performances of the artificial neural network, decision trees and discriminant analysis methods to classify student achievement. The study uses multilayer perceptron model to form the artificial neural network model, chi-square automatic interaction detection (CHAID) algorithm to apply the decision trees method and…
Descriptors: Comparative Analysis, Classification, Artificial Intelligence, Networks
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Bofah, Emmanuel Adu-tutu; Hannula, Markku S. – Large-scale Assessments in Education, 2017
In large scale international assessment studies, questionnaires are typical used to query students' home possessions. Composite scores are computed from responses to the home resource questionnaires and are used as a measure of family socioeconomic background in achievement comparison or for statistical control. This paper deals with profiling the…
Descriptors: Foreign Countries, Socioeconomic Status, International Assessment, Scores
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Wighting, Mervyn J.; Liu, Jing; Rovai, Alfred P. – Quarterly Review of Distance Education, 2008
Discriminant analysis was used to determine whether classifications could be made between students enrolled in e-learning and in face-to-face university courses (N = 353) based on their scores from separate instruments measuring sense of community and motivation. Study results provide evidence that the predictors were able to distinguish between…
Descriptors: Electronic Learning, Online Courses, Discriminant Analysis, Academic Achievement
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Rice, Kenneth G.; Ashby, Jeffrey S. – Journal of Counseling Psychology, 2007
Multiple samples of university students (N = 1,537) completed the Almost Perfect Scale-Revised (APS-R; R. B. Slaney, M. Mobley, J. Trippi, J. Ashby, & D. G. Johnson, 1996). Cluster analyses, cross-validated discriminant function analyses, and receiver operating characteristic curves for sensitivity and specificity of APS-R scores were used to…
Descriptors: Validity, Life Satisfaction, Group Membership, Grade Point Average
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Wilson, Rick L.; Hardgrave, Bill C. – Educational and Psychological Measurement, 1995
A study of the ability of different models--including the classification techniques of discriminant analysis, logistic regression, and neural networks--to predict the academic success of master's degree students in business administration suggests that prediction is difficult, but that classification and nonparametric techniques may be…
Descriptors: Academic Achievement, Business Administration, Classification, Discriminant Analysis
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Kopiez, Reinhard; Weihs, Claus; Ligges, Uwe; Lee, Ji In – Psychology of Music, 2006
The unrehearsed performance of music, called "sight-reading" (SR), is a basic skill for all musicians. It is of particular interest for musical occupations such as the piano accompanist, the conductor, or the correpetiteur. However, up until now, there is no theory of SR which considers all relevant factors such as practice-related…
Descriptors: Expertise, Reaction Time, Music, Low Achievement
Hanson, Bradley A.; Bay, Luz; Loomis, Susan Cooper – 1998
Research studies using booklet classification were implemented by the American College Testing Program to investigate the linkage between the National Assessment of Educational Progress (NAEP) Achievement Levels Descriptions and the cutpoints set to represent student performance with respect to the achievement levels. This paper describes the…
Descriptors: Academic Achievement, Classification, Cutting Scores, Discriminant Analysis
Everson, Howard T.; And Others – 1994
This paper explores the feasibility of neural computing methods such as artificial neural networks (ANNs) and abductory induction mechanisms (AIM) for use in educational measurement. ANNs and AIMS methods are contrasted with more traditional statistical techniques, such as multiple regression and discriminant function analyses, for making…
Descriptors: Academic Achievement, Algebra, Classification, College Freshmen