Degree Outcomes for University of Reading Students

Transcription

1 Report 1 Degree Outcomes for University of Reading Students Summary report derived from Jewell, Sarah (2008) Human Capital Acquisition and Labour Market Outcomes in UK Higher Education University of Reading PhD Thesis This report is for internal use and circulation within the University of Reading 0

2 1. Background to the research This is the first of three reports based on the findings of Dr Sarah Jewell s PhD undertaken at the University of Reading, which utilised University of Reading student data. This first report will focus on the determinants of degree performance at the University of Reading. Readers seeking an executive summary of this report may wish to go straight to Sections 3 and 4, which present the key findings and the discussion of the implications of these. Readers seeking more detail on the data and research underpinning this report are encouraged to contact the author, or to go directly to the thesis, which can be accessed in the University of Reading library. Sarah Jewell undertook her PhD at the University of Reading between September 2005 and October 2008 in the School of Economics, supervised by Dr Zella King (School of Management, Henley Business School) and Dr Alessandra Faggian (School of Geography, University of Southampton). Her thesis, entitled Human Capital Acquisition and Labour Market Outcomes in UK Higher Education, examined degree and labour market outcomes using University of Reading student data. The thesis was primarily from an economic point of view and many of the results are relevant and important to the University of Reading. Therefore all three reports aim to present the results in an accessible manner and to highlight significant findings that may be of importance to the University. The primary aims of the PhD were threefold: To identify the determinants of degree performance, taking into account a broad range of personal characteristics, as well as the effect of degree subject To examine the extent to which students are employed whilst at university, and its effect on their degree performance To analyse the combined effect of personal characteristics, employment at university and degree performance on outcomes in the labour market. The research was conducted using data from the cohorts of University of Reading students graduating in 2006 and Data were collected from three main sources: the University of Reading student database (RISIS), a survey of Reading undergraduates circulated in spring 2006, and the destinations of leavers in higher education (DLHE) survey. The survey collected information on family and socio-economic background, financial situation, term time and vacation employment and attitudes to careers. To investigate the determinants of degree performance we used data from the 2006 and 2007 cohorts of Reading graduates (data on 4,577 students derived from RISIS) with additional insights derived from questions on the survey (completed by 678 students within the cohorts graduating in 2006 and 2007). The survey data permitted us to examine the incidence and reasons for employment, and its effects on degree performance, as well as on labour market outcomes. To analyse outcomes in the labour market, we combined data from RISIS with DLHE data for 2006 and 2007 British domiciled graduates (a total of 3,229 graduates), focussing on destinations, quality of 1

3 graduate employment and salaries. Further information on data collection and the characteristics of the data used is available in a separate document which is available on request Determinants of degree performance Degree outcomes are usually measured by the final degree classification on the scale of first, upper second, lower second, third, pass, fail and other results. Although there are other measures that can capture achievement in higher education such as percentage marks or value-added measures, degree classification is the main measure of degree performance that we examine since it is the measure most commonly used by employers and higher education league tables. The distribution of degree results is provided in Table 1. We excluded students who did not sit their exams (44 students) or had other results (43 students) such as result not yet available or no recommendation. Due to the small number of students getting a pass (30) or failing and not going onto repeat (29) these were combined with the third category. Our analysis is therefore reflective of 4,491 (2,257 in 2006 and 2,234 in 2007) student observations. There is a clustering in the second categories with 56% achieving an upper and 25% a lower second. Approximately 70% of students received a good degree (upper second or above), one of the common measures used in the university league tables. The University of Reading achieves above the UK average on this measure, for example in 2005/2006 approximately 57% of UK students obtained a good degree, 2 but this level of 70% is similar to the percentage achieved by other 1994 institutions. 3 There has been an increase in the number of upper seconds awarded and a decrease in the number of firsts between 2006 and These findings could be due to the differences in characteristics observed in Table 2, particularly variations in degree subject. Table 1: Degree classification Degree classification All % 2006 % 2007 % First Upper second 2, , , Lower second 1, Third, pass or fail Total 4, , , Please contact Sarah Jewell at s.l.jewell@rdg.ac.uk 2 Obtained from 2005/2006 HESA data - accessed from last accessed 07/09/ See the Times Higher league tables for the proportion of good degrees awarded by each institution, which can be viewed at last accessed 07/09/

4 We now move on to describe the effect of personal characteristics, qualifications on entry and degree subject on degree classification. 2.1 Personal characteristics Figure 1 shows that women get a greater number of upper seconds, whilst men get more firsts (although only marginally), lower seconds and thirds. This picture fits that of recent studies, 4 where women generally perform better and men are over-represented at the third level but not necessarily at the first level (as seen in the past). Figure 1: Degree classification by gender There are variations among non-traditional students. Table 2 and Figure 2 show that, like men, both overseas and mature students have a more varied distribution with firsts, lower seconds and thirds more likely. There are variations between the various nationality groups, with students from Asia doing the best in terms of firsts but also obtaining the greatest number of thirds and below. Students from Africa get a lower proportion of firsts and upper seconds with the most frequent category being the lower second. 4 For example see Simonite (2005), Powdthavee and Vignoles (2007) and Fielding et al. (2008) 3

5 Table 2: Degree classification by nationality Nationality Group No of obs. First (%) Upper second (%) Lower second (%) Third and below (%) British 4, Overseas European-EU Asia Africa Other The other group covers North and South America, Australia, the Middle East and Other non-eu European countries Figure 2: Degree classification by age 2.2 Qualifications on entry Given the variety of qualifications that students enter with, we equated as many qualifications as possible to the same scale, based on the existing UCAS scale. 5 Qualifications can be broadly grouped into A-levels, qualifications comparable to A- levels and qualifications not directly comparable to A-levels. Table 3 provides an overview of the distribution of degree classification by qualification on entry, with the qualification types broken down into further groups. 5 Full details of this approach is available in a separate document outlining the data collection, which is available on request. 4

6 The fact that there is a greater variation in performance for overseas and mature students could be a product of their differing entry qualifications. Table 3 confirms that students entering with qualifications commonly taken by overseas or mature students i.e. non-a-level qualifications, tend to achieve a greater number of firsts but also proportionally more lower seconds and below. It is not possible to ascertain if overseas and mature students performance is determined by entry qualifications or by other factors attributed specifically to these groups, such as greater motivation or life experience (in terms of older students). However, we did find that overseas and mature students have significantly higher career importance scores (the importance of having a career relative to other life roles), an approximate measure of student motivation. Table 3: Degree classification by qualification on entry Qualification Type No of obs. First (%) Upper second (%) Lower second (%) Third and below (%) A-Levels 3, Comparable to A-Level qualifications Overseas qualifications converted to UCAS points (exc. International Baccalaureate) International Foundation Programme International Baccalaureate University of Reading science foundation year Other qualifications covered by UCAS tariff Qualifications not directly comparable to A-Levels Higher (above A-level standard) Overseas Other (inc. entered on mature student basis) Non-University of Reading foundation course (higher or foundation level) Access course All Table 3 ignores the actual level of attainment of prior qualifications which may reflect a student s underlying ability. The distribution of our UCAS points or equivalent measure was divided into four groups (quartiles) ordered by point score, with the first group containing those with the lowest point scores and the top group containing those with the highest scores. This approach enables an easier understanding of the relationship between point score and degree classification. Figure 3 implies there is a strong connection between point score and final degree classification. Students across all groups (or abilities) are more likely to get an upper second than any other classification, but the proportion getting a first increases with point score with 27% of those in the top 5

7 group achieving one. A greater percentage of students in the top group obtain a first than a lower second with the opposite case for all other groups. The proportion getting a lower second and below also falls, as one moves up through the groups. Figure 3: Degree classification distribution by point score quartiles 2.3 Degree subject and gender differences One possible reason for the differences in classification observed by gender could be that males and females tend to choose different subjects, as shown in Table 4, which examines subjects at university school level (defined as of 2007). The majority of subjects have a gender imbalance. For example, psychology and clinical language studies have almost six times more women than men, whereas construction management and engineering has almost eight times as many men. Subjects that are relatively gender neutral include: chemistry, human and environmental sciences. The number of students enrolled varies across degree subject group, so Table 4 also examines the overall subject distribution by gender (with the most frequent subject for women highlighted in red and blue for men). The most popular subject for men is business (16.2%), compared with psychology and clinical studies for women (14.5%). Humanities are a common field for both sexes, partly reflecting its overall size. A greater proportion of women choose law, English and American literature and humanities, whilst more men opt for systems and software engineering. Overall there is a clear indication that men choose more science based subjects, with women selecting more humanities and life science orientated fields. 6

8 Table 4: Degree subject group distribution by gender ordered by female to male ratio Subject distribution Degree subject group Number of Students Female to male ratio Female (%) Male (%) Construction management and engineering Systems and software engineering Mathematics, meteorology and physics Business Agriculture Humanities Politics and sociology Human and environmental sciences Chemistry, food sciences and pharmacy Biological sciences Law Art, communication and design English and American literature Modern languages Education Psychology and clinical language studies Health and social care Total 4, It is commonly observed that achievement in art subjects tends to be less dispersed than science subjects, so their different distributions may partly explain the variation in performance by gender. Table 5 compares the proportion in each degree classification category across subjects and splits this by gender. The two fields of study which gave the highest proportion of firsts (mathematics and systems engineering) have a low female to male ratio but a greater proportion of women who achieve firsts. English and American literature has the greatest number of upper seconds, and has almost three times more women than men. With the exception of business and education, a larger proportion of men get more thirds and below than women across all subjects. This pattern is also true for lower second awards, with art and communication design and English and American literature the only two exceptions and no difference in agriculture. Women get more upper seconds than men in each degree subject except in mathematics, meteorology and physics; and agriculture (reflecting they got more firsts in these subjects than men). Since men and women have different degree classification distributions in each subject group, this signifies that any differences by gender are not solely down to, but influenced by, field of study. In 11 subject groups women get a greater number of firsts than men, but the degree subjects with the greatest number of first awards tend to have a higher ratio of men, suggesting men are more attracted to disciplines that award a greater number of firsts. This finding may explain why across all subjects there are marginally more men (15.7%) obtaining firsts than women (15.1%). What is interesting is that it is in male dominated subjects, such as construction management and engineering; 7

9 mathematics, meteorology and physics; and agriculture, that there is a bigger gap in the proportion awarded a first, and this gap is in favour of women. The subjects where the likelihood of getting a first is greater for men tend to be female-dominated subjects such as biology, law, art communication and design and English and American literature. However, the subjects with the highest female to male ratios tend to have a greater proportion of women obtaining firsts. These findings indicate that women who choose certain male dominated courses actually outperform their male (counterparts, possibly due to only choosing the subject if they have a high aptitude for it or they are driven to achieve by being in a male dominated environment. The same is true of men who choose female dominated subjects. 8

10 Table 5: Degree classification distribution by subject and gender ordered by female to male ratio Degree subject group Female to All (%) Female (%) Male (%) male ratio First Upper second Lower second Third and below First Upper second Lower second Third and below First Upper second Lower second Third and below Construction management and engineering Systems and software engineering Mathematics, meteorology and physics Business Agriculture Humanities Politics and sociology Human and environmental sciences Chemistry, food sciences and pharmacy Biological sciences Law Art, communication and design English and American literature Modern languages Education Psychology and clinical language studies Health and social care All

11 3. Key findings We present the key findings and a discussion of the implications of these here, and as such they can be read as an executive summary. The main body of the report, including data and more detailed exploration of the statistical analysis, can be found in Section 3. The thesis used regression techniques to specifically test the determinants of degree performance, with most of the descriptive statistics backed up by the regression results. Regression results enable one to see the effect of a variable whilst controlling for a whole range of factors. We do not report the regression results (these are available on request 6 ) but provide a summary. Firstly regressions were run using the entire 2006 and 2007 cohorts, with the following key findings On average women tend to perform as well as or better than men in all subjects. There is a wider variation in male performance, with men more likely to get lower seconds and below There is some evidence that women are more likely to get a first than men in certain male dominated subjects, such as systems and software engineering, mathematics, meteorology and physics There are gender differences in the way factors influence degree performance. Age has a much stronger positive effect for men, suggesting that factors, such as immaturity and motivation, may be hindering young males performance. Older students on average perform better but there is greater variation in their performance There is greater variation in the performance of overseas students with differences across nationalities There were few socio-economic class effects. The only significant result was that males from non-professional backgrounds were more likely to gain a third or below than those from professional backgrounds Qualifications on entry to higher education (as measured by UCAS point scores) and type of qualification are a strong predictor of degree performance. Those with higher UCAS scores get better degrees, and this is a powerful factor On a like for like basis those who attended an independent school perform worse, particularly in terms of getting a first and especially for men There are more firsts awarded in science subjects particularly in biology and software and systems engineering. At the same time more thirds are awarded in sciences particularly in maths, meteorology and physics, construction management and engineering. Modern languages and business degrees have lower odds of a first or upper second, whilst law has the highest probability of a lower second There are variations across subjects in the strength of the relationship between UCAS points (or equivalent) on entry and degree performance, with strong correlations for agriculture, mathematics, meteorology and physics, business and biology. Weaker correlations exist for art, communication and design, law, politics and sociology 6 Please contact Sarah Jewell at s.l.jewell@rdg.ac.uk 10

12 Students who undertook a four year course e.g. with a placement year or year abroad, did better in their degrees than those on three year courses The affect of the various determinants of degree performance varied between traditional (young British students with A-levels) and non-traditional students. Further insights were provided from the analysis of the information collected from our Employment and Attitudes to Careers Survey. No evidence that socio-economic and financial situation (having family support, loans or scholarships) have a direct impact on degree performance. However, these factors do impact on the decision to undertake term time employment, with term time employment under certain circumstances having an adverse effect on degree performance (see below). Students who come from a background where both parents have a degree (but not if only one parent has a degree) are more likely to get a first compared with an upper second. This could be due to a greater natural ability (that is not captured by qualifications on entry) or a greater parental interest in education (since we are controlling for socio-economic class and parents earnings). Having a higher career importance score, relative to other life roles, leads to a greater probability of a first, but this only holds for women (with women, on average, having a significantly higher career importance score ). A higher weight placed on having a career could point towards greater motivation and be an indicator of students preferences e.g. they are willing to give more time and effort to their studies. Peer effects (as estimated by term time accommodation) have little impact on degree performance. However, students living in private accommodation without other students are more likely to get a lower second and below than an upper second. This is after controlling for age and motivation (as estimated by career importance score), since these students are more likely to be older students. On average, term-time employment has no significant effect on degree performance but has a negative impact (particularly in terms of the likelihood of getting a first) for those who work out of financial necessity (who are disproportionately from lower socioeconomic backgrounds) and those who work with a high intensity (with those working out of financial necessity also more likely to work with a greater intensity) 7. Based on end of year marks, the effect of term time employment is greatest on final year marks, with those working out of financial necessity more likely to work in their final year and for longer. 4. Discussion of implications This research has shown that particular groups have different degree outcomes: mature students, those with non-traditional qualifications and overseas students have a greater variation in performance, indicating a greater diversity of students in these groups. Therefore universities may need to understand the greater variation in needs within these groups of students, especially as we identified (results not reported) that the effect of the various determinants of degree 7 We provided a more in depth analysis of student employment and its effect on degree performance in the second report of this series. 11

13 performance varied between traditional (young British students with A-levels) and non-traditional students. There is a need for further investigation into why women, on average, do better than men. For example, do women thrive better in the higher education environment, do women put in more effort, or do women fare better under the current examination set up? However, as shown in the third report of this series of reports, women then have worse labour market outcomes. Are the attributes that aid women in their degree performance a hindrance when it comes to the labour market? We discuss this more below. More research is needed to investigate differences in subject choice, particularly by gender, since we found that women were more likely to get a first than men in subjects that were male dominated. This highlights that subject choice may be connected to unobserved predictors of degree performance such as motivation, ambition and natural aptitude. If certain subjects attract students with such qualities, this may also mean subject has a signalling effect in the labour market if employers believe that students with desirable attributes are attracted to certain subjects. The third report of this series shows that some subjects have advantages in the labour market such as engineering and construction management, business, vocational subjects and mathematics and IT. There is an issue that some factors such as being female, coming from a state school positively affect degree outcomes. However, these same people tend to have worse labour market outcomes (as seen in our third report). Therefore, more research is needed to investigate why certain people thrive in the higher education environment but not in the labour market. Again this may be indicative that the underlying personal attributes such as conscientiousness, agreeableness which may aid degree performance (Farsides and Woodfield, 2003, 2007) are not the same attributes that are awarded in the labour market such as greater antagonism or risk taking (Mueller and Plug, 2006). We might also speculate that there is ongoing gender, class and ethnic bias in labour market recruitment. Other research has shown that, on average, there are personality differences between men and women (Muller and plug, 2006 Heincek, 2007), which may partly explain the gender differences we have seen. Our results bring up the issue that the current degree classification system may no longer be a good comparative measure across subjects (and possibly universities) i.e. one size does not fit all. There are clear subject differences across degree outcomes, with arts and humanities subjects tending to be clustered in the middle (upper and lower seconds) and science based subjects tending to have a wider range of results. These patterns suggest that students could benefit from strategic selection of subjects in which they are more likely to get a good degree and that have the highest rewards in the labour market, rather than a subject they enjoy or excel in. These findings support the need for change in the degree classification system, as recommended by the recent Burgess report (Burgess, 2007), since it is becoming increasingly difficult for employers to distinguish among the growing number of upper second achievers. 12

14 References BURGESS, R. (2007) Beyond the honours degree classification: Burgess Group Final Report. Universities UK. FARSIDES, T. & WOODFIELD, R. (2003) Individual differences and undergraduate academic success: the roles of personality, intelligence and application. Personality and Individual Differences, 34, FARSIDES, T. & WOODFIELD, R. (2007) Individual and gender differences in 'good' and 'first class' undergraduate degree performance. British Journal of Psychology, 98, FIELDING, A., CHARLTON, C., KOUNALI, D. & LECKIE, G. (2008) Degree attainment, ethnicity and gender: Interactions and the modification of effects. The Higher Education Academy/Equality Challenge Unit. HEINCEK, G. (2007) Does it pay to be nice? Personality and earnings in the UK. Lazer discussion paper. University of Erlangen-Nuremberg. MUELLER, G. & PLUG, E. (2006) Estimating the Effect of Personality on Male and Female Earnings. Industrial and Labor Relations Review, 60, POWDTHAVEE, N. & VIGNOLES, A. (2007) Succeeding in higher education: a widening participation issue. Institute of Education, University of London. SIMONITE, V. (2005) Gender difference added? Institutional variations in the gender gap in first class degree awards in mathematical sciences. British Educational Research Journal, 31, SMITH, J. & NAYLOR, R. (2001b) Dropping Out of University: A Statistical Analysis of The Probability of Withdrawal for UK University Students. Journal of Royal Statistical Society A, 164, UNITE (2006) UNITE Student Experience Report. 13