This article was downloaded by: [RMIT University] On: 19 February 2014, At: 13:40 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
Journal of Higher Education Policy and Management Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/cjhe20
Towards a typology of at-risk students: a case study in Singapore a
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Angela R. Dobele , Foula Kopanidis , Michael Gangemi , Stuart a
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Thomas , Rabea Janssen & Rose E. Blasche
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RMIT University , Melbourne , Australia Published online: 25 Jan 2012.
To cite this article: Angela R. Dobele , Foula Kopanidis , Michael Gangemi , Stuart Thomas , Rabea Janssen & Rose E. Blasche (2012) Towards a typology of at-risk students: a case study in Singapore, Journal of Higher Education Policy and Management, 34:1, 3-13, DOI: 10.1080/1360080X.2011.621194 To link to this article: http://dx.doi.org/10.1080/1360080X.2011.621194
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Journal of Higher Education Policy and Management Vol. 34, No. 1, February 2012, 3–13
Towards a typology of at-risk students: a case study in Singapore Angela R. Dobele*, Foula Kopanidis, Michael Gangemi, Stuart Thomas, Rabea Janssen and Rose E. Blasche
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RMIT University, Melbourne, Australia The purpose of this study is to examine at-risk students and the reasons they give to explain their poor academic performance, with a view to developing a typology of at-risk students. A case study methodology was used to investigate the total population of at-risk students for Semester 2, 2008 studying at the Singapore campus of an Australian-based university. Poor academic performance means that students are placed ‘at-risk’ of exclusion from the University if their grades do not significantly improve in subsequent semesters. The majority of students cite employment pressures (primarily work commitments interfering with study) and personal relationship difficulties (including divorce and family commitments) as the main causes of their at-risk status. Our findings may help universities implementing at-risk programmes reduce student attrition and better aid students in completing their degrees. Keywords: at-risk; typology; student; case study
Introduction Tertiary education has undergone a shift in recent years, moving from teacher-centred or content-oriented learning towards student-centred or learning-oriented outcomes (for example, Bates, 1995; Ramsden, 1992; Parpala & Lindblom-Ylänne, 2007). In its efforts to ensure positive student outcomes one Australian-based university has increased its focus on how its students perform, as measured by academic grades achieved across subjects studied. Through its at-risk programme the University identifies students whose academic progress is poor in order to introduce pastoral care programmes and identify different learning tools that can be implemented before a student faces university expulsion. At the university studied, the term ‘at-risk’ refers students in danger of being expelled from their university programme due to unsatisfactory academic performance. Once at-risk the student remains so until the end of their degree programme; there are no grace periods or resets. The following research questions are investigated; 1. Is there a typology of at-risk students? 2. What reasons do these students give to account for their poor academic performance?
*Corresponding author. Email:
[email protected] ISSN 1360-080X print/ISSN 1469-9508 online © 2012 Association for Tertiary Education Management and the L H Martin Institute for Higher Education Leadership and Management http://dx.doi.org/10.1080/1360080X.2011.621194 http://www.tandfonline.com
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These questions are explored in a single semester focussing on all at-risk students studying at the Singapore campus of the Australian university. At-risk students from undergraduate degrees in either economics/finance or marketing are considered.
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Learning and learning styles Self-efficacy describes how people judge their own capabilities as a means of organisation and execution of tasks to achieve desired goals (Bandura, 1986, 1997), with self-efficacy affecting an individual’s choice of activities, level of effort, and persistence in achieving desired outcomes (Bandura, 1997). Those with higher levels of self-efficacy are generally better able to achieve desired goals (Bandura, 1997; Schunk, 2003; Chang & Ho, 2009). Self-efficacy is important for students as it affects their levels of motivation, persistence in the face of difficulties, academic adjustment and achievement (Gore Jr, 2006; Feldt et al., 2010), and people with a strong belief in their own abilities will tend to work harder and persist longer in the face of difficulties than those who feel hopeless or doubt their own abilities (Drewes & Michael, 2006). However, past research in this area is fragmented, confined to specific domains, and fails to provide a cohesive progression of understanding (Kopanidis, 2008). For example, learners will acquire more information more effectively when they control their own learning journey (Ferber, 1977; Morse, 1991; Spiggle, 1994), yet learning is less effective when learners are in charge of their own learning pathways (Mohring, 1990). Overall, research on learning styles is enjoying renewed importance in higher education (Quester, et al., 2007; Schiffman, et al., 2008). At-risk is an important topic for three reasons. First, the focus on the reasons given by students for poor academic results seeks to determine whether these students are taking responsibility for their own academic performance. This is important as previous research indicates that those taking responsibility for their academic performance are best at determining their learning needs and acting positively on this knowledge (Mager, 1964; Merrill, 1975, 1980). Secondly, existing literature concentrates on attrition; students who have already failed or dropped out. There is little research that considers students who are at-risk but have not yet dropped out or been excluded, though a connection between unsatisfactory academic performance and likelihood of a student abandoning the course has been established (Araque, Roldán, & Salguero, 2009). Finally, given the link between performance-based funding and student performance (Dobson, Sharma, & Haydon, 1998), at-risk students should be of concern for educators and institutions. Methodology This paper reports on the efforts of one capital-city based Australian university to manage an intervention programme for at-risk students. The identity of the University and the School in which this research was conducted is withheld to ensure anonymity and hereafter referred to as the University. The University is a member of the Australian Technology Network (ATN) and offers a Bachelor of Business (Economics and Finance), either full- or part-time, and a full-time Bachelor of Business (Marketing) in Singapore offered through a partner institution. The case-study method chosen for this research is considered advantageous as it employs multiple sources of evidence (Yin, 2009). For example, student demographic details were sourced from online enrolment data and academic performance information
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were sourced from the academic records of students. At the end of each semester the University’s Academic Progress Committee evaluates the performance of all students in order to identify those students who are to be classified as at-risk. This study considers Semester 2, 2008. Each at-risk student is advised via email of their situation, and is invited to participate in a non-compulsory face-to-face interview with an academic advisor. During the at-risk interview, students are asked to account for their poor academic performance and an Academic Performance Improvement Plan (APIP) is prepared. Students unable or unwilling to attend can complete an APIP via email. Research question 1 is analysed using the chi-square statistic and research question 2 is analysed using thematic analysis of the substance of the reasons given by students to explain their own poor academic performance, consistent with Spiggle (1994).
Results: research question 1 – typology of at-risk student Of the 659 marketing students studying in Singapore in Semester 2, 2008, 85 (13 per cent) were at-risk, and 135 of the 806 economics and finance students (17 per cent) were atrisk, giving a total of 220 students at-risk from a population of 1,465 enrolled students (15 per cent of the students were at-risk). The sample group was evenly divided by gender, (48 per cent male, 52 per cent female) and a chi-square test confirmed that the proportions were not significantly different (Table 1). These percentages are comparable to those for the total student population in Singapore during 2008 (44.6 per cent male and 55.4 per cent female students). When considered by programme gender is statistically significant, χ 2 (218) = −4.442, p = 0.000 (
