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Wright, Delivee L.; Bond, Steven C. – 1985
The relationships between a diverse set of individual difference, demographic, and aptitude variables; and a set of student attitudes and behaviors pertinent to experiences in large lecture classes were examined. The sample was 4300 students enrolled in 33 lecture classes at a large university. The relationship between the set of individual…
Descriptors: Academic Achievement, Aptitude Treatment Interaction, Correlation, Higher Education
Peer reviewedToffefson, Nona; Wigington, Henry – Instructional Science, 1986
This study used multiple regression analysis to estimate the effects of variance in teacher ratings explained by teacher-produced variability (teaching practices and/or skills) and by student-produced variability (education level, motivation, and goals) on selected student variables. Previous research suggested that these student variables…
Descriptors: Higher Education, Literature Reviews, Multiple Regression Analysis, Predictor Variables
Harnisch, Delwyn L. – 1985
Data from the High School and Beyond study--restricted to over 800 regular public school students from a population of 18,684 who completed test batteries in both their sophomore and senior years--are analyzed in this report. Included in the cluster of 12 school variables are school policies, school resources, and school practices. The…
Descriptors: Academic Achievement, Competency Based Education, Educational Environment, High Schools
Download full textGorman, Kathleen L. – 1984
The purpose of this study conducted in May 1984 was to: (1) develop a demographic profile of the typical student user of Minnesota University's Walter Library; (2) confirm the validity of a similar survey conducted the previous year; and (3) determine why subjects used this particular library. The third objective was added to this survey via the…
Descriptors: Academic Libraries, College Students, Demography, Evaluation Criteria
Peer reviewedOman, Paul W. – AEDS Journal, 1986
Describes a study of 38 students at Eastern Oregon State College which identified mathematics proficiency as the key student characteristic leading to successful completion of computer science courses, and developed a model that accounts for 82 percent of the variation in students' final grades in computer courses for use by advisers. (LRW)
Descriptors: Academic Achievement, Academic Advising, Analysis of Variance, Computer Science Education
Arnold, Carolyn L.; Kaufman, Phillip D. – 1992
This report examines the effects of both student and school characteristics on mathematics and science achievement levels in the third, seventh, and eleventh grades using data from the 1985-86 National Assessment of Educational Progress (NAEP). Analyses feature hierarchical linear models (HLM), a regression-like statistical technique that…
Descriptors: Academic Achievement, Cultural Differences, Elementary Secondary Education, Grade 11
