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Wright, Mary C.; McKay, Timothy; Hershock, Chad; Miller, Kate; Tritz, Jared – Change: The Magazine of Higher Learning, 2014
Learning Analytics (LA) has been identified as one of the top technology trends in higher education today (Johnson et al., 2013). LA is based on the idea that datasets generated through normal administrative, teaching, or learning activities--such as registrar data or interactions with learning management systems--can be analyzed to enhance…
Descriptors: STEM Education, Introductory Courses, Physics, Technology Uses in Education
Schatzel, Kim; Callahan, Thomas; Davis, Timothy – Journal of College Student Retention: Research, Theory & Practice, 2013
Results from the analyses of data from 463 former college students between the ages of 25 and 34 years old identify those most likely to reenroll in higher education in the near future. Those who intend to reenroll are more likely to be members of minority groups, younger, single, and recently laid-off, have earned more credits, and hold strong…
Descriptors: Dropouts, Stopouts, Enrollment, Withdrawal (Education)
Veenstra, Cindy P.; Dey, Eric L.; Herrin, Gary D. – Advances in Engineering Education, 2009
With the current concern over the growing need for more engineers, there is an immediate need to improve freshman engineering retention. A working model for freshman engineering retention is needed. This paper proposes such a model based on Tinto's Interactionalist Theory. Emphasis in this model is placed on pre-college characteristics as…
Descriptors: College Freshmen, Engineering Education, School Holding Power, Academic Persistence