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Webber, Karen L., Ed.; Zheng, Henry, Ed. – Johns Hopkins University Press, 2020
The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound…
Descriptors: Data Use, Decision Making, Learning Analytics, Higher Education
Levin, James; Wyckoff, John – 1990
This study developed predictive models on persistence and success in engineering at the end of the sophomore year by examining 11 intellective and 9 non-intellective variables. The project's long-term purpose was to contribute to the improvement of academic advising for students considering engineering majors and thus improve student retention.…
Descriptors: Academic Achievement, Academic Advising, Academic Persistence, College Bound Students
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
Richards, William – 1986
In fall 1985, a study was conducted by the Colorado State Board for Community Colleges and Occupational Education to analyze the efficiency and effectiveness of community college assessment programs throughout the state. Each community college in the state randomly selected 100 students whose basic skills had been assessed and who had enrolled in…
Descriptors: Academic Achievement, Academic Advising, Academic Persistence, Basic Skills

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