Abstract Over the past decade Australian universities have experienced rapid growth and increased diversity of the student population. Increased diversity has been achieved by increased enrolments of students from groups in Australian society that have little or no experience of university study. Many of these students are working either full-time or part-time while pursuing their university studies. This combination of work and study poses many problems, both for individual students and the universities they attend. This study has three aims: (a) to conduct a large pilot study of a survey instrument designed to collect information about the work/study dilemma; (b) to investigate methods of improving response rates for surveys that are conducted across the Internet; (c) to provide policy makers with some information about the strategies students employ to resolve the work/study dilemma. The study concludes that recent attempts by Australian universities to increase the flexibility of course delivery in order to resolve the work/study dilemma is to some extent misplaced. Internet survey, diversity, attrition, flexible delivery

Abstract Introduction Perceptions of attrition Studies into student performance and attrition Methods Results Conclusions References

 

Introduction

Since 1998 the number of Australian university students has increased markedly. Furthermore, the diversity of the student population has also increased. In part, this is due to the former Colleges of Advanced Education gaining university status. Increased diversity is also in part, a result of policies specifically designed to increase the participation of students from groups in Australian society that have little or no tradition of university study. Unfortunately, students from these social groups tend to be less well prepared for university studies. Consequently, their level of performance is generally lower than that of traditional groups of students (Ramsay, Tranter, Sumner and Barrett 1996). In particular, high rates of attrition for these students are becoming a cause for concern among policy makers. The origins of these problems appear to lie in the inability of many students from non-traditional backgrounds to resolve the so-called work/study dilemma. Hence, a major cause of attrition is the inability of many students to devote sufficient time to their studies, while continuing to meet their work, family and social responsibilities. The response of the university sector in general has been to increase the flexibility of course offerings. However, this decision has been made in something of an information vacuum regarding the expectations that students have about a university education. The primary aim of this study was to pilot a survey instrument to collect information about how students address the work/study dilemma. As a result of the prohibitive associated with printing, posting and processing paper-based questionnaires it was decided to administer this survey over the Internet. However, for many people the Internet is a new medium, both for administering and responding to questionnaires. The challenges faced in the use of this new medium include the development of strategies that lead to acceptable response rates. Although there is a wealth of information about boosting response rates of postal surveys, the relative newness of on-line surveys results in a lack of equivalent knowledge for Internet based surveys. Hence, the second aim of this study is to investigate ways of increasing the response rate of surveys conducted over the Internet. The third aim of this study is to provide policy makers with some understanding about how students suggest that the work/study dilemma might be resolved.

Perceptions of attrition

Attrition can be viewed as either a negative or a positive outcome of an educational experience. Highly prestigious institutions may argue that high rates of attrition are an inevitable consequence of maintaining the competitive academic conditions upon which their reputations are based (Lenning, Beal and Sauer 1980). In this context, high attrition rates may not be perceived as a problem, but rather as a form of quality assurance and hence as a positive educational outcome for the institution. Alternatively, some people may enrol in a course with the intention of completing only a selection of subjects to reach specific personal or professional goals. In such cases, withdrawal also can be viewed as a positive educational outcome. The dominant view of attrition however, focuses on its perceived negative effects. First, such effects are identified as lowering the self-esteem and self-confidence of students. Even temporary withdrawal may adversely affect the confidence of people and have serious implications for any subsequent study or career path that they may wish to pursue (Lam 1984). Second, attrition is seen as causing a social loss as these people do not achieve their potential. Their talents are wasted, and society does not benefit by their further education. Third, attrition can be considered a waste of institutional resources, which have increasing opportunity costs in a period of declining real per student funding. Fourth, attrition can damage the reputations of courses and institutions by bringing into question the relevance of their courses, the quality of teaching and the adequacy of student support services. Finally, attrition can compound problems associated with falling enrolments leading institutions to experience difficulties with planning and budgeting (Ewell 1984: Price, Harte and Cole 1991). Regardless of whether attrition is seen from a positive or negative perspective, it is commonly investigated in terms of course and institutional loss. As such, two attrition-related matters require further discussion. These have been referred to as the 'stop out' and the 'goal fulfilment' issues (Ewell 1984). The crux of the stop out problem is that university students are displaying increasingly complex patterns of enrolment. A conventional, but outmoded, view assumes that young people complete Year 12, enrol in an undergraduate degree the following year at a university and graduate on time after three to six years of uninterrupted full-time study. However, the Australian student population is becoming increasingly diverse and hence students are becoming more flexible in their pathways through and between post-compulsory education, employment and training. Combining full-time study with periods of part-time study and paid work is increasingly common among students. Furthermore, intermission from studies in order to travel, undertake paid work or for other personal reasons are also becoming more common. The majority of students may graduate eventually, but not necessarily be from the university in which they were originally enroled. Such students may appear as institutional attrition, but they are not lost to the system and their temporary withdrawal can be viewed positively. The second issue, commonly referred to as goal fulfilment, is more complex. Some students may withdraw because they feel that their studies are not helping them to attain their goals. This can be perceived as a negative reason for withdrawing. However, other students withdraw for more positive goal-related reasons, as mentioned earlier. A student may have no intention of ever finishing a degree program having enroled in selected subjects for personal or professional interest, to assist career progression or perhaps to gain entrance to another university (Roberts 1984). Consequently, some students withdraw because they have met their goals, while others redefine their goals or identify other means of achieving them. Unfortunately, the hopes, expectations and aspirations of the Australian student population are not fully understood by university planners and administrators. The assumption that, despite the increased diversity of the Australian student body, that all university students have one goal, to complete a bachelor's degree is increasingly less likely to be valid. If indeed it ever was.

 

Studies into student performance and attrition

Student success There is little reported research into student success and attrition that specifically focuses on students from non-traditional backgrounds. The limited Australian literature in the area falls into two main categories. The first attempts to develop regression or econometric models of student performance and progress through courses. These studies usually concentrate on the pre-entry characteristics of students and inform debates concerning appropriate selection criteria for university courses. The second group of studies attempt to explain pass and retention rates. The findings of both types of studies are relevant in the development of a policy framework and initiatives aimed at improving student performance and progression rates. West (1985) investigated the effects of three pre-entry characteristics on the performance of students who entered Monash University directly from secondary school in 1975, 1980 and 1982. The characteristics were, type of school attended, father's occupation and the student's country of birth. The measures of performance used were, grade point average, pass rate as measured by the percentage of subjects in which students attained a pass or better and credit rate as measured by the percentage of subjects in which students attained a credit or better. A least squares regression model and a logistic regression model were employed for these analyses. West concluded that students who undertook most of their secondary education in government schools performed better at the end of their first year of University than students with the same selection score from independent schools. Neither father's occupation nor country of birth were significant predictors of university performance over each of the three years investigated. Smyth, Knuiman, Thornett and Kiiveri (1990) investigated the performance of 3,734 first-year university students who enroled at the University of Western Australia between 1977 and 1980. This project focused on both individual subject and overall performance. Three statistical models were developed, each incorporating personal data, comprised of variables relating to the performance of students in the final year of secondary school and variables relating to performance in their first year of university study. Among their findings they argued that prediction models of first year performance needed to be more sophisticated and incorporate pre-entry student characteristics in addition to those employed in their study. Lewis (1994) analysed the results of 10,482 commencing undergraduate students who enroled at the University of Wollongong between 1990 and 1993. The study assessed the performance of students who were admitted to the University by means of its access and equity schemes, in order to determine whether the performance of these groups was comparable to that of other students. Two measures were employed. The first, the mean aggregate mark, was analysed using multivariate regression analysis. The second, whether or not students had passed 75 per cent or more of the subjects in which they were enroled, was analysed using a logistic regression model. The study concluded that female students, students who had attended government schools and older students who were not school leavers, performed significantly better than the university-wide average. Conversely, the performance of students from non-English speaking backgrounds and those of indigenous students were significantly below the university average. Killen (1994) reviewed a number of research studies into teaching and learning in higher education and concluded that a number of factors could influence student success, as measured by pass rates. The main factors identified by Killen in these studies were the motivation of students, their approach to studying, and their cultural expectations, all characteristics of students rather than institution or the higher education system. Killen then attempted to isolate the factors that were associated with student success by conducting interviews with a sample of students and lecturers at the University of Newcastle. As a result, four groups of factors were identified that significantly affected student performance. The first two factors were internal to students, self-motivation and effective study techniques. The two factors external to students were family support and enthusiastic lecturers. This study represented a shift from a focus on student deficits to a consideration of institutional factors by arguing that institutional factors could play a role in improving pass and attrition rates. Student withdrawal Since the early1980s, a relatively small number of studies have attempted to explain attrition in Australian universities. The National Institute of Labour Studies conducted an investigation into the attrition of first year students in all South Australian institutions of higher education during 1985 (Power, Robertson and Baker 1987). Two groups of students who did not proceed to the second year of their courses were identified, those who passed and withdrew and those who failed and withdrew. Students in these two sub-groups had one essential characteristic in common. They concluded that their course no longer matched their educational goals or interests. Consequently, they lacked the required level of commitment to continue. The study identified a relationship between reduced attrition rates and the implementation of appropriate strategies and programs both to generate student commitment to their course at entry and then to strengthen systematically and develop this commitment during their initial year at university. Price, Harte and Cole (1991) conducted a study of student attrition at the Northern Territory University, focusing on comparative attrition rates across faculties, stage of course, attendance status and previous educational background, as well as on the reported reasons for of attrition. The population for this study was all students who were enroled in three successive years (1988, 1989 and 1990) who did not re-enrol in the following year. Over 2,000 students were surveyed with a response rate of 23 per cent. The study identified a particular group of students who had a higher tendency to withdraw. They were part-time students who had left school more than five years prior to enroling, had matriculated at high school, were engaged in full-time employment and were enroled in the first stage of their course. Sharma and Burgess (1994) surveyed 855 undergraduate students (a response rate of 43 per cent) who withdrew from Swinburne University of Technology during 1993. This study identified 11 factors that students saw as important considerations in their decision to discontinue studies. In order of importance, lack of motivation, employment related matters, study workload, failure in examinations, financial situation, dissatisfaction with the learning environment and enrolment in the wrong course were identified by at least 30 per cent of respondents as a significant consideration for withdrawing. It was argued that there was a strong inverse relationship between student success and attrition. Therefore, action taken to improve student pass rates would reduce attrition. Sharma and Burgess concluded that a range of largely extraneous factors were important determinants of attrition, including financial status, student information, employment conditions and personal or family situation. The studies into student attrition and performance reviewed here acknowledge that these issues are becoming increasingly serious in Australian universities and require remedial action. Furthermore, these problems are especially acute for first year students. These studies suggest that these problems are cause by two sets of factors, that that are internal to students and those that are external. These studies recommend that universities implement two sets of strategies to reduce attrition and increase student performance. Strategies designed to address internal factors could include, inter alia, assisting students to; make more informed decisions about university study; become more highly motivated and committed to their course of study; develop university literacy skills; and develop the time management and other life skills required to manage the competing demands on their time. Strategies designed to address external factors could include, inter alia, assisting students to; improving the enthusiasm of lecturers; implementing programs designed to monitor and attenuate attrition; and providing a teaching and learning environment that is empathetic to the needs of diverse student population. These studies do not recommend increased flexibility of subject and course delivery through the increased use of distance education teaching methodologies and the Internet. It would therefore appear that the decision of many Australian universities to embrace flexible delivery as the panacea for the sector's woes was not based on a consideration of this body of literature.

Methods

The initial aim of this study was to pilot the work/study dilemma survey instrument. This was achieved by surveying every undergraduate student enroled in the Division of Business and Enterprise at the University of South Australia during semester 2, 1999, some 4,365 students in total. The usual mailout of questionnaires plus two reminders was considered prohibitively expensive. Furthermore, when large surveys achieve a reasonable response rate the costs of data entry also become a matter of concern. In order to minimise expense, a survey instrument that could be answered on the Internet was developed. Participant responses collected by the on-line instrument were automatically compiled to form the database and all measures were taken to ensure confidentiality. The address of the Work/Study website was emailed to all undergraduate students of the Division of Business and Enterprise at their university email account addresses. This message took the form of a covering letter seeking student involvement and supplying the information required by the University's Ethics Committee. Two follow up email messages were also sent to participants. The website contained a secure database of the names, identity numbers and dates of birth of all of students who were invited to participate in the study. This database served a number of purposes. First, the names of the students were inserted into the survey instrument so that it included a personalised greeting. Second, the student identity number and date of birth provided a degree of security for the system. Finally, this database controlled access to the website. Once participants had submitted a completed questionnaire they were refused permission to access the site a second time. Consequently, people in the sample were prohibited from completing more than one questionnaire. The data collected were analysed in order to develop some insights into the nature of the work/study dilemma. SPSSx, version 9 (Norusis 2000), was used to prepare the cross tabulations and the cluster analysis that formed the basis of the following discussion.

Results

A total of 383 valid questionnaires were submitted to the database. Since the survey was emailed to 4,365 students this represented a response rate of 8.8 per cent. The address of the survey website was sent to the email accounts that the University provided to its students. However, the University's information technology services unit indicated that only 30 per cent of students accessed their university email accounts. Consequently, students who did not have access to the Internet at home or at work found it very difficult to access their email accounts. Consequently, it could be argued that only 1,310, or 30 per cent of 4,365, students read the emails that were sent to them regarding the survey. Hence, this lower figure should be regarded as the sample size. In which case, the response rate would be 29.3 per cent. The 383 respondents were fairly representative of the student population of the Division, with the notable exception of the gender balance. There were 230 female and 153 male respondents to the survey. Males and females were fairly equally represented in the student body of the Division. The over representation of females would seem to indicate that the work/study dilemma was of more serious concern for women than it was for men. However, it might also reflect increased access by women to the Internet or that women made better use of email. Furthermore, access to and confidence with information technology may play a significant role in academic success and progress. Consequently, these sources of bias needed to be investigated. Table 1 shows the age distribution of the respondents. The youngest respondent was only 17 years of age and the oldest 51 years old, with an average age of 23.6 years. The age distribution of the respondents appeared to be representative of the student population of the Division. Table 2 shows the pathways that the respondents used to gain entry to the University. This table confirmed the view that the respondents to the survey reflected the general population of the Division. Table 1: Respondents by Gender and Age. Age group Females Males Total Per cent Under 21 108 65 173 45 21 to 25 65 48  113 30 25 to 30 34 14 48 13 31 to 35 8 9 17 4 36 to 40 7 11 18 4 41 to 45 6 5 11 3 Over 45 2 1 3 1 Total 230 153 383 100 Table 2: Respondents by Entry Pathway. Entry pathway Females Males Total Per cent School leaver 130 89 219 58 Mature age test 39 29 68 18 Tertiary transfer 13 3 17 5 Previous TAFE studies 27 13 40 11 Recognition of prior learning 9 6 15 3 Special access award 3 0 3 1 Special entry applicant 1 4 5 1 Other 7 6 13 3 Total 229 151 380 100 Table 3 shows the courses that the respondents were enroled in when the survey was conducted. The table also indicates that this group of students reflected the general population of the Division. Courses listed as "Other" in Table 3 refers to courses offered by Schools outside of the Division of Business and Enterprise. An over representation of commerce students responded to the survey instrument. In the main, these students were studying accounting and were required to undertake a high proportion of their classes in the computer pools. Hence, they had much better access to the University's computing facilities and consequently made much better use of their university email accounts.  Table 3: Respondents by Course of Enrolment. Course Females Males Total Per cent Commerce 69 33 102 29 Management 44 29 73 21 Marketing 22 16 38 11 International business 26 11 37 11 Information systems 15 18 33 9 Administrative management 24 6 30 9 Banking and finance 7 6 13 4 Property 7 4 11 3 Other 16 29 45 13 Total 230 152 352 100 Table 4: Source of Income by Sex Source of income Females Males Total Per cent Full-time employment 53 28 81 21 Casual employment 43 19 62 16 Youth Allowance 31 29 60 16 Part-time employment 34 14 48 13 Family Support 25 22 47 12 Austudy 27 18 45 12 Casual employment 4 11 15 4 Private income 3 2 5 1 Other 9 7 16 4 Total 229 150 379 100 Table 4 indicates that the vast majority of students were employed. Just over a quarter of students were in receipt of a government benefit, either Austudy or Youth Allowance. Nevertheless, the majority of these students worked on either a casual or part-time basis in order to supplement their benefits. Only those 47 respondents who stated that their sole source of income was family support fitted the typical student model. In all likelihood, these students were probably international students and the survey instrument needs modification to identify this group of students for separate analysis in future studies. Of more importance is the amount of time and energy that students devoted to paid employment. The relationship between the sex of the respondents and the number of hours they worked is shown in Table 5. On average, the respondents to the survey undertook 23.6 hours of paid work per week outside of the home. This figure was slightly lower for females, 23.5 hours per week, than it was for men, 23.9 hours per week. More interesting, was the high proportion of students who could be considered to be full-time employees. Thirty hours of paid employment outside of the home per week is commonly considered to be full-time employment. In which case, Table 5 shows that 21 per cent of respondents who worked were employed on a full-time basis. The concept of time budgets and time management skills is an increasingly important issue for many students. Especially given the relationship between time on task and student performance (Kokkinn Head Feast and Barrett 1998). However, information about the time students spent meeting their family, sporting or social commitments, which was likely to be considerable, was not collected during this study. Nor were any questions about how much time respondents devoted to their studies was asked. These important questions should be followed up in a later survey.  Table 5: Hours Worked by Sex Number of hours worked Females Males Total Per cent 10 or less 37 18 55 22 More than 10 and less than 20 46 31 77 31 More than 20 and less than 30 17 12 29 12 More than 30 and less than 40 35 17 52 21 More than 40 and less than 50 16 8 24 10 More than 50 and less than 60 4 3 7 3 More than 60 and less than 70 0 1 1 0 Total 155 90 245 100 Table 6: Income by Sex Weekly income Females Males Total Per cent Less than $50 10 9 18 6 More than $50 and less than $100 36 19 55 18 More than $100 and less than $150 31 20 51 16 More than $150 and less than $200 30 25 55 18 More than $200 and less than $300 23 16 39 13 More than $300 and less than $400 15 6 21 7 More than $400 and less than $500 9 11 20 6 More than $500 and less than $1000 29 13 42 14 More than $1000 and less than $2000 3 5 8 3 Total 186 124 310 100 The relationship between sex and income is presented in Table 6, which shows that not only did students devote significant amounts of time to undertaking paid employment, but also these respondents were also quite well paid. The average weekly income of employed respondents was $295.38. The figure was a little lower for females ($288.63) than it was for males ($305.52). Interestingly, the maximum income was reported to be $1800 per week. Clearly, the preceding tables present a picture of a diversified student population, which reflects the macro level changes that have occurred in the Australian higher education system since 1988.  Table 7: Preferred Class Times by Sex Preferred class times Females Males Total Per cent Weekdays 9 am to 5 pm 57 41 98 88 Weekdays 5 pm to 9 pm 4 4 8 7 Weekends 4 2 6 5 Total 65 47 112 100 Table 8: Preferred Teaching Mode by Sex Preferred Teaching Mode Females Males Total Per cent Offered internally on campus 50 35 85 83 Offered externally 5 5 10 10 Offered via the Internet 5 3 8 8 Total 60 43 103 100 The third aim of this study was to develop some understanding of the work/study dilemma. The University of South Australia has identified the problems that students encounter combining their studies with work and other commitments as a major cause of student attrition and poor performance (Ramsay, Sumner, Tranter and Barrett 1996). The response of the University has been to increase the flexibility of program delivery. This usually means increased use of distance education modes of delivery and increased use of the Internet. As this has been a major thrust of curriculum development over the past few years it was decided to gauge the opinions of students about the University's increased reliance of these non-traditional forms of subject delivery. The responses to these two questions are reported in Tables 7 and 8. These tables demonstrate that despite the diversity of the respondents they share two common characteristics. Firstly, 88 per cent of the respondents wanted to attend classes during normal business hours (Table 7), between 9 am and 5 pm on Monday to Friday. Secondly, 83 per cent of the respondents revealed a strong preference to study on-campus in the internal mode (Table 8). However, these results need to be interpreted with some caution due to the much lower response rates on these two questions, compared to the response rates for the questions reported in Tables 1 to 6, which were among the first questions on the survey instrument.  Results of the Cluster Analysis In order to understand better the attitudes of students, a series of cluster analyses were undertaken to identify whether there were any distinct groups of respondents (Table 9). The cluster analysis identified the presence of two distinct groups of students. Surprisingly, given the literature reviewed above, the sex of students did not emerge as a characteristic of these groups. Group 1 accounted for the majority of students, 84 per cent, in the sample. This group of 190 people was characterised by young students, who live at home with their parents and earn a small income as a result of casual employment. Group 2, which accounted for 37 people in the sample, is almost the exact opposite to Group 1. It is characterised by older people, in well-paid full-time employment, who lived at home with their partners and children. Cluster analysis is essentially an iterative process. Once the analysis identified the two groups discussed above the cluster analysis was extended to investigate whether a third or even a fourth cluster of respondents existed. Further analysis identified a third group of six people as a distinct cluster, which was comprised of a small number of the highest income earners in Group 2. In effect, it was a sub-group of the second group. Given the size of this sub-group and the characteristics of its members it was concluded that only two distinct clusters were present.  Table 9: Results of the Cluster Analysis Respondent characteristics Cluster 1 Cluster 2 Age 22.1 32.3 Employment Casual employment Full-time employment Weekly income $237.42 $908.75 Hours of work per week 20 42 Length of enrolment 2 years 3 years Entry pathway School leaver Previous TAFE studies Enrolment status Full-time Part-time Mode of study Internal student Internal student Parental responsibilities No Yes Domestic arrangements Live at home with parents Live at home with partner Number of respondents 190 (84 %) 37 (16 %) Despite the marked differences between the members of Group 1 and Group 2, the two groups of students had one thing in common. They wanted to study on campus during normal business hours, as shown in Tables 7 and 8. Not surprisingly, they also displayed a strong preference for traditional forms of subject delivery. However, given the obvious differences in the characteristics of the members of these two groups, the reasons underlying these preferences were probably quite different. For example, young school leaver students might value highly the social interactions that took place with other young people on campus. Young students might also come to university with strong expectations that university is an extension of secondary school and they would attend classes and be taught by teachers. Conversely, older students might feel the need to interact with other students in order to gain support, reduce social isolation and develop business networks. They may also have seen study as an integral part of their employment. Hence, they held the view that classes should be taken during business hours. Clearly, the survey instrument needs further modification to include a number of items that unpack the information shown in Tables 7 and 8 and explore the expectations and aspirations of students. It might also be necessary to conduct a number of focus groups with participants to further refine the questionnaire items.

Conclusions

If this pilot study is to be expanded then the response rate will need to be markedly increased. Moreover, sources of bias need to be identified and understood. Hence, several strategies should be employed. Firstly, the number of items in the survey instrument must be reduced and refined to improve its focus. Secondly, students must be encouraged to visit the survey website by a variety of means other than sending messages to their university email accounts, which 70 per cent do not read. Hence, the cooperation of people such as course coordinators, subject conveners, school office staff and other administrators, is vital. Thirdly, the Internet is increasingly being used for both teaching and administration. Courses, subjects, staff and even students increasingly have their own website. Furthermore, student administration, such as checking enrolment details, amending information held on student information databases, receiving provisional as well as final results and tutorial allocation are increasingly being undertaken across the Internet. Consequently, hypertext links to the survey website could be added to the administration and teaching websites students should visit. Fourth, approximately 30 per cent of students subscribe to an Internet service provider. Many lecturers at the University of South Australia have responded to this trend by setting up webserve lists for their subjects as a medium to distribute teaching materials and to communicate directly with their students. Hence, the address of the survey website could be posted to these webserve lists. Finally, students are rational and do respond to inducements. Hence, the personal information database could be used to pick prizewinners. The survey indicates that students use a wide variety of pathways into and through their university studies. They combine study with periods of part-time and full-time work and step out of their studies for travel or other personal reasons. These observations may also indicate changed patterns of workforce entry. The conventional view is that students complete secondary school, complete their university studies and then enter the workforce after graduation. However, for business students this does not appear to be the case. University studies and workforce entry increasingly seem to be occurring in tandem. However, this may differ for students in other courses and in other universities. Hence, the survey instrument needs to include questions that provide greater insights about the pathways that students follow through their studies and unpack the process by which entry to the workforce is undertaken. Despite the increased diversity of the Australian student population and the complexity of the pathways through their studies, the respondents expressed a strong desire to study on campus with their classes conducted during normal business hours. This preference for traditional methods of subject delivery is clearly at odds with recent trends at the University of South Australia towards increased flexibility of course offerings. The survey found that a high proportion of students were employed on a casual or part-time basis, especially in the growing service sector. Students appear to be using the increased flexibility that has emerged in the labour market, as a result of economic restructuring and recent changes to workplace relations to provide the flexibility required to overcome the work/study dilemma. If this is the case then the University's flexible delivery agenda appears to be misplaced. Hence, the University needs to understand these issues if it is to improve the performance of students from non-traditional backgrounds.  The findings of the survey indicated the existence of two distinct clusters of students, which have very different demographic characteristics. Consequently, different reasons probably underlie the preferences for teaching traditional methods. The expectations of these two groups of students need to be fully understood if appropriate policies to improve student performance are to be implemented. The next step in this project should be to conduct focus group discussions with respondents to unpack the issues and refine the survey instrument.

    

References

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