The importance of student success in higher education is incontestable (Morgan et al. 2001; Thornhill 2001) and improving student retention and achievement has a particularly high priority for third level institutes of higher education. Both the University and Institute of Technology sectors realise the importance, with the Inter-Universities Retention Network (Moore 2004) declaring that
The universities identified retention, completion and student withdrawal as important issues to be addressed and they have received increasing attention within the Irish university sector (p.1)
The Council of Directors of the Institutes of Technology (CODIT) are also determined, in stating (CircaGroup 2006) that there is
An urgent need to obtain more up to date and detailed information on the situation in the institutes with regard to completion rates. (p.ii)
An examination of completion rates among students in computing courses in Irish higher education institutions (HEI’s) shows a large proportion of students who enrol do not finish within the ‘normal’ duration of their programme, and a significant number do not complete their course at all (‘normal’ being defined as the expected duration of the course, typically 3 years for a degree course and 4 years for a honours degree.) There has been much research into best practices in teaching computer programming, and into new and innovative module design and curricula, and retention initiatives. However, students’ results and interests do not reflect this effort, and retention rates in the computer science and engineering disciplines are considerably lower in comparison to other disciplines. Ireland has one of the highest concentrations of Information and Communications Technology (ICT) activity and employment in the international Organization for Economic Co-operation and Development (OECD). Despite this, there are above-average rates of non-completion in computer science undergraduate courses (Morgan et al. 2001).
There has always been a stubborn issue with regard to retention on computing programmes, even in the ‘boom’ when students gaining higher Leaving Certificate points were applying for computing courses. In those years the problem was smaller and could mainly be attributed to students who picked computing courses due to the popularity, modernity and perceived economic prospects of the industry, but who were not particularly motivated by perfection of the skill and did not have good knowledge about the nature of the work. The latter problem of good knowledge and understanding of programming is still a very significant problem but is now compounded by the lack of adequate prior knowledge and preparation in terms of mental schemas from which the student can draw.
Context and Setting
Employers also express certain dissatisfaction with the coverage provided by traditional curricula and graduates’ understanding and/or willingness to pursue computer programming (Forfás 2002). Ireland was once declared the leading exporter of software in the world (IMD 2003). The country has a high concentration of ICT industrial activity and employment. There are however, above average rates of non-completion in undergraduate computer science and engineering disciplines. The fact that these higher rates are recorded in an area of key national interest for job creation and retention makes this issue a cause for concern and a major strategic priority.
Unlike our European neighbours, Ireland failed to develop its educational system in the immediate post-war years. It was only in 1967 that second-level education was provided free to all citizens. Since 1970, the educational system has been greatly expanded at second and third-level to bring it into line with the European norm (Fitzgerald and Kearney 1997). Two thirds of the generation who are retiring from the labour force today left school at 14 or less, and less than 10% of them had the benefit of third-level education. By contrast, 80% of the school leaving cohort last year completed second-level education and over 50% continued on to third-level education. Based on the 1992 intake to Irish universities, the report “A Study of Non-Completion in Undergraduate University Courses” compiled by the Educational Research Centre, (Morgan et al. 2001) revealed that 68% of students graduated on time; 15% graduated late and 17% did not complete the course on which they initially embarked.
Non-Completion Rates at University Per Discipline in 1992
The report showed that of first-time entrants to universities, 83% obtained a degree on the course on which they had initially embarked. Nonetheless there were major differences in rates of non-completion associated with students’ area of learning. Computer Studies had the highest level of non-completion with 59% entering in 1992 not completing their degree, as illustrated above (Flanagan and Morgan 2004.) At the other extreme, students studying law, medicine, dentistry or veterinary medicine had the lowest level of non-completion at 7%.
In a similar study of students attending Institutes of Technology it was found that of the students who began their course in 1995, over half graduated on time, 52%, with 5% graduating late or still in attendance in 1998-99, and just over two-fifths, 43%, not completing the courses they had enrolled in on entering college. The vast majority of students at the Institutes of Technology who did not progress to second year fell into one of two categories, both of which involved withdrawal. Over two-fifths failed their examinations, while one third withdrew before sitting their first year exams. Once more, differences in rates of non-completion associated with students’ discipline of learning were apparent, as illustrated below (Flanagan and Morgan 2004.) Again the highest rate of non-completion evident was in the Computer Science discipline.
Non-Completion Rates at Institutes of Technology Per Discipline in 1995
The major differences in rates of non-completion associated with students’ area of learning are noticeable, with computer science/engineering non-completion rates being high in both the Irish universities and Institutes of Technology. While there is no clear explanation for this, the motivation of students, clear/definite career paths and student perceptions of skill set necessary are possible reasons for such a difference.
There are many factors, which may influence a student’s decision in deciding to leave college/university. The literature highlights the complex nature of the retention/attrition processes, the effect of institutional characteristics, and the difficulties of generalizing or expanding the body of knowledge from that of theoretically-based research. Tinto’s revised model reinforces the dynamic nature of academic and social experiences, external communities, and effective integration of the student within the institutional culture over time (Tinto 1993). Polansky cited research indicating that students persist towards graduation in spite of poor academic achievement and conversely withdraw despite academic success (Polansky et al. 1993). Both circumstances suggest underlying factors and perhaps the need to better understand students enrolled in given institutions over time. Much of the literature with regard to student retention is institution-wide and not discipline specific. This blog post will introduce the main models/factors relating to student retention with particular emphasis on retention issues for computing students.
Many studies which have been conducted in the area of student retention have limited value. This is due to the problems in defining non-completion. There is a variety of ways in which students can fail to complete a course: some register but never actually begin the course (non-starter); others go through formal procedures before leaving (formal withdrawal); some withdraw informally (informal withdrawal); some may not attend lectures or complete required coursework but do not actually formally withdraw (non-continuer); some fail exams and subsequently leave (academic failure); and some just move to another course at the same or another institution (transfer to other programmes) (Kember 1995).
Not all students enter higher education with the intention of completing and graduating from their course. Some leave because they have achieved their learning goals; others because they want to transfer to another course or institution or because they have found employment. In such cases, a negative term such as ‘dropout’ is inappropriate as students’ choices, aspirations and circumstances change and for some individuals benefits may be gained only by leaving. Tinto has observed that
“if the leaver does not define his/her own behaviour as representing a form of failure, neither should the institution” (Tinto 1987).
Review of Retention Literature
Research on student retention has led to evidence about the reasons, and the development of models which can perhaps explain and clarify attrition, thus leading to institutional interventions to foster retention. According to Bean, only in the last two decades have the models of attrition or retention, the table below, evolved from previous theoretical or descriptive studies (Bean 1982).
|Spady (1970, 1971)||A sociological model proposed (based on Durkheim’s, 1950 suicide model)|
|‘Model of Student Departure’ a psychological processes model, explaining the factors contributing to student attrition – organizational turnover model|
|Tinto (1975, 1987, 1993)||Tinto (1975), Student Integration Model – academic and social integration; Tinto (1993) led to the development of a longitudinal, explanatory model of departure|
|Astin (1984, 1993)||Posited that the implications for practice should be overarching, rather than singular in nature.|
|Quality of student effort, student background/pre-college traits, and interactions with agents of socialization directly influence learning and cognitive development. All other variables indirectly affect the process.|
|Describes a role for institutional research in changing institutional attitudes about the priority placed on student retention efforts. Problems associated with changing perspectives are described using Kuber-Ross’s work On Death and Dying.|
|Bean and Eaton (2001, 2002)||A psychological model, Attitude-behaviour, Coping behavioural, Self-efficacy and Attribution theory|
Theorist and Theory Relating to Student Retention
At a very high level Woodley summarised the reasons for withdrawal within the following categories:
- Course factors: For example found course too difficult, insufficiently rigorous, too demanding, different from expected, uninteresting, badly designed and/or taught.
- Institutional factors: For example inadequate facilities, equipment, accommodation, etc. administrative inadequacies, student required to leave by the institution
- Study environment factors: For example unforeseen changes in personal, domestic or working life; ‘chronic factors’ such as lack of time, energy, money or support; or transport problems
- Personal blame: For example self-perception of being disorganised, not clever enough, lacking in study skills, lacking self-confidence, etc.
- Motivational factors; e.g. original goal achieved or changed; realisation that goal will not be achieved or could be achieved better elsewhere; other goals given priority (Woodley et al. 1987; McGivney 1996)
These clusters of reasons figure predominately in most studies of non-completion, with reports making a clear distinction between institution and course factors, and factors which are external to the higher educational institute.
In the field of academic student retention literature Tinto’s model is held in high regard and is the most highly respected model (Kember 1995), providing a heuristic and theoretical framework for understanding student behaviour (Tinto 1975; Tinto 1982; Tinto 1987; Tinto 1993). According to Tinto’s theory the decision to ‘drop out’ arises from a combination of student characteristics and the extent of their academic, environmental and social integration in an institution.Further work by Tinto led to the development of a longitudinal explanatory model of departure (Tinto 1993). This expanded work added “…adjustment, difficulty, incongruence, isolation, finances, learning, and external obligations or commitments” to his original model. He proposed that
“…the stronger the individual’s level of social and academic integration, the greater his or her subsequent commitment to the institution and to the goal of college graduation” (Pascarella et al. 1986).
In summary, the model argues that individual departure from institutions can be viewed as arising out of a longitudinal process of interactions between an individual with given attributes, skills, financial resources, prior educational experiences, dispositions (intentions and commitments) and integration with other members of the academic and social systems of the institution (Tinto 1993). Students’ entry commitment affects the extent of their social and academic interaction within a learning institution, and the extent of their integration, which in turn has an impact on their goals and institutional commitment.
A Conceptual Schema for Dropout From College, (Tinto 1993)
**I’ll do a separate more detailed post on the elements of Tinto’s Model shortly
Effects of Non-Completion
In institutes of higher education in the US more students leave college or university prior to degree completion than stay (Tinto 1993). The consequences of this migration from higher education are not trivial, either to the individuals who leave, or for their institutions.
For institutions, the consequences of high rates of student departure, though measured in different terms to that of the student, are of no less concern. It is a major concern presently where the decline in the numbers of students sitting their Leaving Certificate has finally arrived (i.e. the decline of the ‘traditional student’), and the interest in computing courses has also declined. Institutes of higher education have invested in large recruitment campaigns in order to increase the number of applicants, but these campaigns no longer produce notable gains. They no longer offer the hope of ensuring departmental/course survival in the coming years. From a course viewpoint poor programming ability has many potential knock-on effects i.e. contributing to wastage, failure rates or poor progress. The quality of the institutions’ qualifications may be devalued accordingly if graduates have a reputation for having poor programming competence. The decline in student numbers during the course has a negative effect on the morale of the class cohort and impacts negatively on the spirit of the year group.
However, it is most important to emphasise that improving student retention not only fulfils the institutionally self-serving function of promoting fiscal solvency, but that it also serves the student-centred purpose of promoting learning and development. Should a student leave their initial choice of educational institution, they not only leave the course they study but they also leave without the broad education that attending a third-level institute may give them. Research has shown that students who leave higher education without completing a degree find it much more difficult than graduates to obtain a ‘graduate-job’ or to enter a channel that could be expected to lead to such a position. In a foreword to a report on non-completion in Ireland (Morgan et al. 2001), Don Thornhill, the former chairman of the Irish Higher Education Authority (HEA), reminds both teachers and policy-makers not to forget that “..for some students who do not complete their courses, the results can be very damaging not just in financial terms but also in terms of reduced self-esteem and self-confidence” (Thornhill 2001).
High non-completion rates among computing students seems to be a global phenomenon compared to other disciplines. This suggests that along with the more generic reasons associated with underperformance and dropout, there may be factors associated with computer programming that differentiates these students in some important ways, from the general population or learners in higher education. In order to develop programs to alleviate the problems of computing students avoiding, fearing and failing with computer programming modules, institutions which seek to prepare students in the field of software development must become concerned with identifying those students who are computer anxious and evaluating the impact of these experience on their self-concept, their cognitive development, their adjustment and their success!
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Astin, W.A. (1993) ‘College Retention Rates are Often Misleading.’ The Chronicle of Higher Education.
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