NotesFAQContact Us
Search Tips
Peer reviewed Peer reviewed
PDF on ERIC Download full text
ERIC Number: EJ1142069
Record Type: Journal
Publication Date: 2016
Pages: 17
Abstractor: As Provided
ISSN: EISSN-2187-0594
Identification of Early Predictors of Adult Learners' Academic Performance in Higher Education
Yin, Sylvia Chong Nguik
IAFOR Journal of Education, v4 n2 p16-32 Sum 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 University, a Singapore University that caters mainly to adult learners. Fourteen variables from the enrolment database were considered as possible factors for the predictive model. To classify the at-risk students, various algorithms were used such as a neural network and classification tree. The performances of the different models were compared for sensitivity, specificity and accuracy indices. The model chosen is a classification tree model that may be used to inform policy. The implications of these results for identification of individuals in need of early intervention are discussed.
International Academic Forum. Sakae 1-16-26 - 201 Naka Ward, Nagoya Aichi, Japan 460-0008. Tel: +81-50-5806-3184; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education; Adult Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Singapore
Grant or Contract Numbers: N/A