Abstract
Purpose
– The purpose of this paper is to predict academic outcome in math and math-related subjects using learning approaches and demographic factors.
Design/methodology/approach
– ASSIST was used as the instrumentation to measure learning approaches. The study was conducted in the International University of Vietnam with 616 participants. An exploratory factor analysis, reliability, and correlation tests were performed before multiple regression analyses were carried out using SPSS 20.0. t-Tests to further discover relationships between learning approaches and demographic factors were also conducted.
Findings
– Females are more inclined to strategic approach, but not deep or surface by comparison with males. There is no relationship between parental education and learning approaches. Students with math preference in high school have tendency to use deep and strategic approach, but stay away from surface in higher education. Surface approach and admission mark have relationships with academic outcome; but gender, parental education, and math preference in high school do not have.
Research limitations/implications
– This model can explain only 15.5 percent of the variation of academic outcome. In addition, it may not be applicable to predict academic outcomes of subjects which are not math related.
Originality/value
– Surface approach has negative impact on academic outcome in math or math-related subjects, but the opposite is true for admission mark. Additionally, deep and strategic approach have no relationship with academic outcome.
Subject
Organizational Behavior and Human Resource Management,Education,Organizational Behavior and Human Resource Management,Education
Reference95 articles.
1. Acato, Y.
(2006), “Quality assurance vital”, New Vision, University Guide 2006/2007.
2. Adwale, P.
and
Adhuze, O.
(2014), “Entry qualifications and academic performance of architecture students in Nigerian polytechnics: are the admission requirements still relevant?”,
Frontiers of Architectural Research
, Vol. 3 No. 1, pp. 69-75, available at: http://dx.doi.org/10.1016/j.foar.2013.11.002
3. Altonji, J.
and
Blank, R.
(1999), “Race and gender in the labor market”, in
Ashenfelter, O.
and
Card, D.
(Eds),
Handbook of Labor Economics
, Elsevier Science, Amsterdam, Vol. 3c, pp. 3144-3259.
4. Anderson, G.
,
Benjamin, D.
and
Fuss, M.
(1994), “The determinants of success in university introductory economics courses”,
Journal of Economic Education
, Vol. 25 No. 2, pp. 99-119, available at: http://dx.doi.org/10.2307/1183277
5. Arcidiacono, P.
(2004), “Ability sorting and the returns to college majors”,
Journal of Econometrics
, Vol. 121 Nos 1-2, pp. 343-375, available at: http://dx.doi.org/10.1016/j.jeconom.2003.10.010
Cited by
14 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献