By the end of 1997 over 64 per cent of women (Figure 2) in the 1992 cohort had completed an award. This compares to 55 per cent of men who started an undergraduate award in 1992. Although a greater proportion of men were still studying at the institution they enroled at in 1992, the estimated aggregate or crude non-completion rate for men was still higher than that for women. According to these aggregate results it would seem that women are almost ten per cent more likely to complete an award course than men.
Figure 2 Undergraduate academic outcomes by gender
The results of the logistic regression analysis suggest that a range of factors contribute to this conclusion. The crude and the adjusted probabilities are presented in Figure 3.
Figure 3 1992 commencing students
completions
by gender—crude and adjusted
The results indicate that, after controlling for all other factors, women entering university in 1992 on the basis of a TER have an adjusted probability of completing an award in the period up to 1997 of 72 per cent. Men entering on the same basis have a 66 per cent chance of completing.
For those entering university on a basis other than TER, however, the influence of gender on completion is much less. Women in this group have an adjusted probability of completion of 61 per cent and the completion rate for men is much closer at 58 per cent. In this case the higher unadjusted completion rate of 64 per cent for women is due to factors other than gender.
The probability of completing an award declines for older students (Figure 4). This is in part likely to be due to the fact that older students are more inclined to study part-time and therefore more are still studying in 1997. Nevertheless even assuming that all of the older students still studying will complete an award their completion rates would not be as high as for those in their late teens. There is also more variation in the rate at which women complete an award. The improvement in completion rates for women when they enrol in their thirties and forties coincides with the period when many women may be about to start a career. For males completion rates are relatively steady from the mid-twenties age group until the mid-forties. Completion rates increase for males over 60 years of age. This group, however, contains only 0.1 per cent (33 men) of males in the population.
Figure 4 1992
commencing undergraduate students:
Completion by age and gender
The results of the logistic multivariate analysis indicate that there is a significant decline in completion rates as age increases for both men and women who enroled on the basis of a TER. The adjusted probabilities of completion for students aged 20 to 24 years are significantly different to those aged 17, 18 and 19 years. For both men and women the decline in completion rates described by the adjusted probabilities is flatter than that for the crude probabilities (Figure 5). This implies that after controlling for other factors age has less influence on completion rates than suggested by the crude probabilities. There are too few cases of students over 24 enrolling on the basis of a TER for them to be included in the analysis.
Figure 5 1992 Commencing students (with TER) completions by age—crude and adjusted
Figure 6 1992 Commencing
students (without TER) completions
by age—crude and adjusted
Over 73 per cent of the 1992 commencing student cohort studied full-time. Almost 67 per cent of full-time students completed a course by 1997 compared to less than 47 per cent of part-time students. Around 37 per cent of external students completed an award by the end of 1997 (Figure 7). The differences in completing an award can be explained, in part, by the fact that part-time and external students were more than twice as likely than full-time students to be still studying in 1997. It is more important to note, however, that over 44 per cent of part-time students and almost 53 per cent of external students had not completed and were no longer enroled in the institution of enrolment in 1992.
Figure 7 Undergraduate academic outcomes by mode of study
The results from the regression analysis indicate that mode of study has a significant effect on completion rates and that the outcome for each mode of study is significantly different to the others. Students in the 1992 cohort who studied full-time, irrespective of their basis of entry to university, had significantly higher completion rates than those who studied part-time or externally (the control group). Similarly part-time students had significantly higher completion rates than those who studied externally.
There is little difference between the crude and adjusted completion rates for those students enroled on the basis of a TER score and studying full-time or part-time (Figure 8). There is however a substantial difference in the crude and the adjusted probability of completion for students with a TER who studied externally. The adjusted probabilities for external students suggest that women had a probability of completion of almost 27 per cent while that for men was just over 32 per cent. In both cases the crude probability of completion was just under 20 per cent. For students with a TER the adjusted probability of completion is higher than the crude probability. The adjusted results also indicate that for females with a TER, full-time students complete at nearly three times the rate of external students. Full-time male students complete at twice the rate of external students.
Figure 8 1992 commencing students (with TER) completions bymode of study—crude and adjusted
The relationship between the crude and adjusted probability of completion is different for those students who enroled on a basis other than TER. The adjusted probability of completion for women was lower for all modes of study (Figure 9).
Figure 9 1992 commencing students (without TER) completions by mode of study—crude and adjusted
For men the adjusted probabilities were very similar to the crude rate but were consistently higher. Overall the variation in completion rates by mode of study is less for female students without a TER since full-time female students complete at only one and a half times the rate of those who study externally. Male full-time students still complete at twice the rate of male external students.
3.4 Outcomes by methods of qualifying for entry to university
Students may qualify for entry to university on the basis of eleven different criteria. These have been classified into three distinct groups; those who enter on the basis of completing secondary education at either school or TAFE; those who have commenced or completed a higher education course previously or gained a professional qualification; and all other bases of entry (Figure 10).
Figure 10 Undergraduate academic outcomes by basis for entry to university
Those who enter university on the basis of completion of secondary education and previous higher education experience or professional qualifications have a higher incidence of completing before the end of 1997 than those admitted on another basis. The common factor in these two categories is previous academic experience or success.
Of these groups students accepted to university on the basis of successful completion of secondary education had the highest completion rates. Students in this category are also younger and more likely to enrol full-time. In contrast students who enter on the basis of mature age and employment experience had the lowest completion rates. Students in this group tend to be older and are more likely to study part-time.
Over 41 per cent of the undergraduates in the 1992 cohort have TER scores. Academic outcomes by aggregated TER scores are expressed in deciles and presented in Figure 11. Students are ranked according to their TER scores, and divided into 10 equal groupings, decile 1 containing students with the highest TER. The top 10 per cent of students in each State were added together to provide deciles at a national level. Figure 11 needs to be interpreted with caution since the range of TER varies from state to state. Nevertheless, it is useful to examine the general relationship between TER and academic outcomes.Figure 11 Undergraduate academic outcomes by TER scores (grouped in deciles)
There is a greater tendency for students with higher TER scores to complete their course of study. Over 78 per cent of the students who scored in the top decile completed their degree compared to about 55 per cent in the bottom decile.
The modelling indicates that TER is a significant predictor of the completion rates for every TER decile and that completion rates decline as TER declines. In general there is little difference between the completion rate calculated on the basis of aggregate data and that estimated by the logistic regression (Figure 12).
There are two points of interest. First, men have slightly higher completion rates in the top two TER deciles. Thereafter women have higher completion rates. Second, the range of completion rates for men is greater than that for women. Men in the top TER decile (the control group) have a 40 per cent increase in the probability of completion as compared to the lowest decile. For women the increase in the probability of completion is 27 per cent from the top decile (the control group) to the bottom TER decile.
It is also of interest that there is no significant difference between the completion rates for students in the top four deciles, and no significant difference between students in the bottom three deciles. It would seem, therefore, that TER is a good predictor of outcome between low and high TER scores, but is a poor predictor within high or low TER scores.
Figure 12 1992 commencing students (with TER) completions by TER score—crude and adjusted
Results of the modelling indicate that for students without a TER, even after controlling for all other variables, the method of entry to university significantly affects completion rates.
However, contrary to the results suggested by the aggregate data the methods of entry with the highest probabilities of completion are previous higher education experience and professional qualifications (Figure 13). These methods of entry are not significantly different from each other and have roughly the same impact on completion rates. Entry on the basis of TAFE experience, special entry and other basis (the control group) are also significant in determining completions for women and the adjusted probability is reasonably similar to that suggested by the aggregate data.
Figure 13 1992 commencing students (without TER) completions by basis of entry—crude and adjusted
For men in this group the results are similar in that higher education and professional experience are the most significant basis of entry in explaining completion rates. Professional qualifications provided the largest boost to the expected completion rates with the crude probability of completion of 48 per cent increasing to an adjusted rate of 62 per cent. Of the other modes of entry to university TAFE experience, finished secondary school and entry by university examination have no significant influence on completion outcomes.
3.5 Outcomes by field of studyThe description field of study is based on the student’s vocational field of specialisation. However, not all university courses lead to a specific vocation and business, economics, arts and humanities and science degrees are generalist rather than vocation specific degrees. It is interesting, therefore, that the aggregate or crude data suggest that vocation specific courses are those with the highest completion rates (Figure 14). More specifically, veterinary science, nursing, health and education have completion rates that range from 70 per cent to over 90 per cent.
Another issue is the number of students in different fields of study. The fields of business, science and arts are the largest groups and collectively account for over 59 per cent of university majors. Business, science and arts have comparatively high non-completions of 36, 38 and 39 per cent respectively. Only agriculture and animal husbandry have higher non-completions (41 per cent).
Figure 14 Undergraduate academic outcomes by field of study
The regression analysis was designed to estimate the significance of fields of study for completion rates against completions in business, administration and economics (the control group). The results indicate that there is consistency across groups in that arts, science and engineering, where significant, have a negative effect on completion rates. Similarly across all groups, health, education, law, architecture and veterinary science have a positive impact on completion rates as measured against business studies.
For those enroled on the basis of a TER the difference in completion rates between nursing students, who have the highest adjusted completion rate, and engineering, the lowest completion rate, is 14 per cent (Figure 15). The range between the highest and lowest adjusted probability of completion by significant field of study is greater for those students enroled on a basis other than TER (Figure 16). For this group the completion rate for veterinary science is 33 per cent above that for law.
The effect of some fields of study differs according to a
students’ gender and basis of entry. For those who entered university on the basis of
TER the field of education has a significant effect on completions for women but not for
men. This may be due to the small number of men undertaking education. For those who
entered university on a basis other than TER, science is significant for men but not for
women. Again this may be due to the relatively small number of women in the science field
of study. Only the two fields of study, health and health nursing have a significant
effect on completion rates for all students, regardless of both mode of enrolment and
gender.
Figure 16 1992 commencing students
(without TER) completions
by field of study—crude and adjusted
Just over one per cent of the 1992 student cohort is of Aboriginal and Torres Strait Islander (ATSI) descent. Completion rates for Indigenous students are substantially lower than for non-Indigenous students (Figure 17).
Figure 17 Undergraduate academic outcomes by Indigenous status
Over 62 per cent did not complete by 1997. The proportion of students still studying in 1997 was the same for both groups at about six per cent.
The results of the logistic modelling confirm that the completion rates for Indigenous and non-Indigenous students are significantly different. The adjusted completion rates indicate that Indigenous women complete at a higher rate in both the groups with and without a TER. For those students with a TER, however, non-Indigenous women are one and a half times more likely to complete than Indigenous women (Figure 18). Male non-Indigenous students are almost twice as likely to complete than male Indigenous students.
The difference between Indigenous and non-Indigenous completion rates is slightly greater among those students without a TER (Figure 19). Non-Indigenous women without a TER have completion rates 1.7 times that of their Indigenous counterparts while non-Indigenous men are 2.3 times more likely to complete.
Almost 13 per cent of the 1992 undergraduate commencing student cohort were from a non-English speaking background. Students from the non-English speaking background group complete at a higher rate than those with an English speaking background (Figure 20). More of the non-English speaking background group were also still studying in 1997.
Figure 20 Undergraduate academic outcomes by language background
The logistic regression analysis confirms that the completion rate of the non-English speaking background group was significantly higher than that for the English speaking background. Among students with a TER, both women and men from non-English speaking backgrounds had a significantly higher probability of completion than students with an English speaking background. The adjusted probabilities were, however, reasonably similar to the crude or aggregate probabilities (Figure 21).
For the group without a TER, the completion rate for women with non-English speaking backgrounds was significantly different from that of women with English speaking backgrounds. The adjusted probability of completion for a woman with a non-English speaking background was 2.6 per cent higher than for a woman with an English speaking background (Figure 22).
Figure 21 1992 commencing students (with TER) completions by language background—crude and adjusted
Students in the cohort have been categorised into quartiles according to their socioeconomic advantage or disadvantage. The relationship between socioeconomic advantage and academic outcome is summarised in Figure 23. The completion rate increases and the non-completion rate decreases as the level of advantage increases. The difference in completion between the most disadvantaged quartile and the most advantaged quartile, however, is only 6.4 per cent. There is a slight tendency for the proportion of students in the still studying category to decline as advantage increases.
Figure 23 Undergraduate academic outcomes by socio-economic status
The modelling demonstrates that socio-economic status is only statistically significant in terms of completion for students entering university on a basis other than TER. Socio-economic status, is statistically significant for all women and for men in the two lowest SES quartiles. The completion rates for those in the second highest quartile of more advantaged is not statistically different to those for the most advantaged male group, which is the group that all other socio-economic quartiles were tested against. In all cases the impact on completion rates is small but negative. There is a 4 per cent improvement in the completion rate for females in the top socio-economic group as compared to the lowest while for men the improvement is 3 per cent (Figure 24).
Students in the 1992 cohort can be classified as having an urban, rural or isolated background. The data indicate that students from urban areas have a higher probability of completion than students from rural or isolated geographic areas (Figure 25).
Figure 25 Undergraduate academic outcomes by geographic location
The logistic regression analysis indicates that geographic locality is significant only for women. In the group with a TER, women from isolated areas are significantly less likely to complete than women from urban areas (the control group). They were 5 per cent less likely to complete an award (Figure 26). Completion rates for women with a rural background were indistinguishable from those of women in the base comparison group of urban background.
Figure 26 1992 commencing students completions by geographic location—crude and adjusted
In the group without a TER, however, women with a rural background are more likely to complete than those with an urban or isolated background. The difference in the adjusted completion rates for urban and rural women is significant but is only around two per cent. The difference between the rates at which rural and isolated women complete is also significant and higher at just over 10 per cent.