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Scaling Student Success with Predictive Analytics: Reflections after Four Years in the Data Trenches
Wagner, Ellen; Longanecker, David – Change: The Magazine of Higher Learning, 2016
The metrics used in the US to track students do not include adults and part-time students. This has led to the development of a massive data initiative--the Predictive Analytics Reporting (PAR) framework--that uses predictive analytics to trace the progress of all types of students in the system. This development has allowed actionable,…
Descriptors: Predictor Variables, Reflection, Academic Achievement, Models
Yin, Sylvia Chong Nguik – IAFOR Journal of Education, 2016
Universities are inundated with detailed applicant and enrolment data from a variety of sources. However, for these data to be useful there is a need to convert them into strategic knowledge and information for decision-making processes. This study uses predictive modelling to identify at-risk adult learners in their first semester at SIM…
Descriptors: Foreign Countries, Predictor Variables, Models, College Freshmen
Lee, Pei-Ling; Pang, Vincent – International Journal of Training Research, 2014
This paper reports on a study of five motivational orientations in continuing education among working adults. The influence of motivational orientations on their academic achievement was identified. The study involved 159 working adults who enrolled into part-time programs in an Open University in Sabah. Boshier's Education Participation Scale…
Descriptors: Foreign Countries, Continuing Education, Adult Students, Student Motivation