Title: Predicting likely student performance in a first year Science, Technology, Society course

Authors: Richard White

Addresses: School of Science and Education, University of the Sunshine Coast, Maroochydore DC, Queensland 4558, Australia

Abstract: To reduce failure rate of first year students, predicting their likely performance would help targeted support. The performance of students in a STS course has been examined using a number of parameters. Student performance correlated with a student's prior educational performance in secondary school and a student's attendance at tutorials. In particular, students in the lower half of their secondary school cohort were more likely to fail. A link between lower tutorial attendance rates and failing the STS course is also noted, with lower attendance rates occurring from the first tutorial, so students who miss early tutorials should also receive early intervention. Student age and a student's family income were poor predictors of student performance. A student's mark in the course tended to increase as student age increased. The rank score given to students who enter university via an alternate pathway was a poor predictor of performance.

Keywords: early intervention; first year students; performance predictors; student performance; prediction; student retention; STS courses; science; technology; society; universities; higher education; social values; political values; cultural values; scientific research; technological innovation; politics; culture; failure rates; student failures; targeted support; prior performance; educational performance; secondary schools; student attendance; tutorials; school cohorts; attendance rates; student age; family incomes; rank scores; alternate pathways; university entrance; University of the Sunshine Coast; USC; Australia; innovation; learning; pedagogical issues; pedagogy.

DOI: 10.1504/IJIL.2012.047311

International Journal of Innovation and Learning, 2012 Vol.12 No.1, pp.72 - 84

Published online: 28 Aug 2014 *

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