ERIC Number: EJ1150071
Record Type: Journal
Publication Date: 2017
Pages: 13
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1925-4741
EISSN: N/A
Early Detection of At-Risk Undergraduate Students through Academic Performance Predictors
Rowtho, Vikash
Higher Education Studies, v7 n3 p42-54 2017
Undergraduate student dropout is gradually becoming a global problem and the 39 Small Islands Developing States (SIDS) are no exception to this trend. The purpose of this research was to develop a method that can be used for early detection of students who are at-risk of performing poorly in their undergraduate studies. A sample of 279 students participated in the study conducted in a Mauritian private tertiary academic institution. Results of regression analyses identified the variables having a significant influence on academic performance. These variables were used in a linear discriminant analysis where 74 percent of the students could be correctly classified into three categories: at-risk, pass or fail. In conclusion, this study has proposed a new technique that can be used by institutions to determine significant academic performance predictors and then identify at-risk students upon whom interventions can be implemented prior to exams to address the problem of dropouts.
Descriptors: Foreign Countries, Undergraduate Students, Identification, At Risk Students, Low Achievement, Academic Failure, Predictor Variables, Predictive Measurement, Early Intervention, Potential Dropouts, Dropout Prevention, Personality Traits, Cognitive Style, Socioeconomic Status, Learner Engagement, Demography, Likert Scales, Correlation, Factor Analysis, Componential Analysis, Grade Point Average, Student Surveys, Multiple Regression Analysis, Monte Carlo Methods
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Mauritania
Grant or Contract Numbers: N/A