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Bellardo, Trudi – Journal of the American Society for Information Science, 1985
Investigated attributes of 61 online searchers that were believed to affect quality of search results: creativity level (measured using two self-report inventories); intelligence level (approximated from GRE verbal and quantitative scores); and personality traits in regard to masculinity, femininity, and self-esteem (measured using…
Descriptors: Creativity, Factor Analysis, Individual Characteristics, Intelligence
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Marsh, Herbert W. – Journal of Educational Psychology, 1984
Using 559 fifth graders, measures were collected to assess multiple dimensions of academic self-attribution, self-concept, and inferred self-concept, and academic achievement. The specificity and predictability of the observed patterns of relations support the construct validity of interpretations based on both the self-attribution and…
Descriptors: Academic Achievement, Attribution Theory, Factor Analysis, Foreign Countries
Morgil, Inci; Secken, Nilgun; Yucel, A. Seda; Ozyalcin Oskay, Ozge; Yavuz, Soner; Ural, Evrim – Online Submission, 2006
In times when human beings used to live in a natural environment, their needs were also provided for by natural resources. With the increase in population over time, human beings started to look for new resources willing to get "the most" and "the fastest". Just like the invention of steam, first, they increased the density of the resources and…
Descriptors: Natural Resources, Fuels, Reliability, Factor Analysis
Bauer, Scott C.; Bogotch, Ira E. – 1997
Path analysis was used to test the relationships between the resources provided to site councils in site-based management (such as administrative support for site-based management), council communication and decision making practices, and perceived outcomes in terms of effectiveness and stakeholder satisfaction. Data were collected form 12 schools…
Descriptors: Educational Administration, Elementary Secondary Education, Factor Analysis, Participative Decision Making
Margolin, Marcia E.; Forsbach, Terri A.; Griesemer, Bonnie A. – 1998
This study examined the conceptions of teacher evaluation criteria of 9th- and 12th-grade teachers and administrators. Four representative members of each group (n=12) were interviewed and asked to identify and define indicators of instructional practice based on the context of their allocated roles and experiences. It was hypothesized that…
Descriptors: Administrator Attitudes, Administrators, Criteria, Factor Analysis
Thomas, Linda A. – 1995
This paper conceptually explains higher-order factor analysis and methods for interpretation. A review of first-order factor analysis is presented that provides the foundation for the summary of second-order factor analysis. Higher order factors are derived from the correlations between the lower-level factors. An example study is provided to make…
Descriptors: Attitude Measures, College Students, Correlation, Factor Analysis
Seng, SeokHoon; Chan, Betty – 2000
This study investigated the nature of spatial ability, as measured by four instruments based on spatial orientation and visualization, and its relationship to the mathematical performance of elementary school pupils. Participating in the study were 127 elementary school students, 72 boys and 55 girls, ages 10 to 11 years. Spatial ability was…
Descriptors: Children, Computation, Elementary School Students, Factor Analysis
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Shields, Lawrence – Educational Research, 1972
Results indicate that students who have attended single-sex girls' schools and then proceed to an all women's college do not make as much progress toward maturity as other college students from co-educational schools. (Author/MB)
Descriptors: Analysis of Variance, College Students, Criterion Referenced Tests, Factor Analysis
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Meredith, Keith E.; And Others – Journal of Medical Education, 1982
Factor analysis was used to examine underlying structures for both admission and clinical performance measures. Multiple regression showed that admission interview comments best predict narrative clerkship performance, while objective scores best predict an objective measure of clinical knowledge. (Author/MLW)
Descriptors: Academic Achievement, Admission Criteria, Clinical Experience, College Admission
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Marsh, Herbert W. – Educational and Psychological Measurement, 1983
This study compares multitrait-multimethod analyses (MTMM) performed on items and factor scores derived from the items. Based upon this demonstration, researchers are encouraged to conduct a preliminary factor analysis before analyzing MTMM data whenever there is a doubt about the underlying trait structure. (Author/PN)
Descriptors: Factor Analysis, Higher Education, Item Analysis, Measurement Techniques
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Eagle, Norman – Review of Higher Education, 1982
What happens to student ratings of instruction after instructors are promoted from one professorial rank to another, and what happens when faculty exhaust all material incentives, acquiring both tenure and the highest academic rank? These questions are examined and instructor rating questionnaire is provided. (MLW)
Descriptors: College Faculty, Factor Analysis, Faculty Evaluation, Faculty Promotion
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Marsh, H. W. – British Journal of Educational Psychology, 1982
Describes research leading to the development of SEEQ (Students' Evaluations of Educational Quality), a program which collects college students' evaluations of teacher effectiveness. Three tables, a 29-item reference list, and appendices outlining the information contained in the SEEQ survey and in the SEEQ summary report are included. (JL)
Descriptors: College Faculty, College Students, Evaluation Methods, Factor Analysis
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Meredith, Gerald M. – Perceptual and Motor Skills, 1983
Two brief scales were proposed to assess effectiveness of teaching in laboratory and seminar/discussion group classes. (Author)
Descriptors: College Students, Course Evaluation, Discussion Groups, Factor Analysis
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Gruenberg, Barry – American Behavioral Scientist, 1983
Using a stepwise multiple regression analysis of data from a 1964-1965 national urban sample, the author identifies the social and demographic variables that best help to predict each of six factor-analytically derived dimensions of leisure activity. (Author/RM)
Descriptors: Behavioral Science Research, Demography, Factor Analysis, Leisure Time
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Reichel, Arie; And Others – Research in Higher Education, 1981
Using 276 students from Boston University and the University of Massachusetts at Amherst, the relationships between types of students and their work values and motivational profiles were investigated by means of factor and discriminant analyses. The vocational model is contrasted with the collegiate, nonconformist, and academic groups. (Author/MLW)
Descriptors: Academic Achievement, Discriminant Analysis, Factor Analysis, Higher Education
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