The Correlation Between Industrial Placements And Final Degree Results Revised Pdf

The Correlation Between Industrial Placements and Final Degree Results: A Study of Engineering Placement Students

Richard Mendez University of Leicester September 2008

The correlation between industrial placements and final degree results: A study of Engineering Placement Students Richard Mendez University of Leicester Abstract The significance of industrial work placements (i.e. the work-based component of sandwich degrees) on students’ professional development and employability is widely accepted amongst work-related learning professionals and academics alike. Indeed, the recent government sponsored report by the Confederation of British Industry validates such claims. However in recent times, many workrelated learning professionals have begun to explore the assumption that work placements not only improve employability skills, but additionally academic performance.

This paper considers the view held amongst many work-related learning professionals that students undertaking an industrial work placement, often graduate with a higher degree classification. Additionally, it scrutinises the assumption that placement students outperform their non-placement counterparts scholastically.

This paper builds upon results from more comprehensive longitudinal research from Mandilaras (2004) and Gomez et al (2004). Through an institutional study of engineering undergraduates at the University of Leicester, it explores whether students that undertook an industrial work placement as part of their engineering degree, outperformed their non-placement counterparts. The statistical analysis offers evidence that suggests a causal link between completing a placement and achieving higher academic performance in the final year of an engineering degree.

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Introduction The presence of work-related learning and employability themes within higher education has grown in prominence with the advent of successive governmentbacked reports. The most recent being ‘Future Fit: Preparing Graduates for the World of Work’, produced by the Confederation of British Industry Higher Education Task Force (2009) and sponsored by the Department for Innovation, Universities and Skills (DIUS). Reports such as these have encouraged the development of work-related learning activity (e.g. industrial placements) in higher education as a means by which to develop students’ employability and transferable skills.

In light of such interest, the correlation between industrial placements and students’ employability has been comprehensively explored by practitioners such as Bowes & Harvey (1999) and Little & Harvey (2006) amongst others. However there remains a dearth of current literature and research exploring the correlation between placements and final degree attainment.

Amongst the germane literature, research by Mayo & Jones (1985) and the Council for National Academic Awards (Davies, 2003) substantiate claims of correlation. Additionally the Confederation of British Industry’s Higher Education Task Force (2009) reports on the analysis of research from the University of Hertfordshire that concluded with similar findings.

However it is the works of Mandilaras’ (2004) and Gomez et al (2004) that explore this area in greater depth. Using data from the University of Surrey’s Economics Department, Mandilaras rigorously explores whether the industrial placement augments academic performance (i.e. increasing the likelihood of the placement student obtaining an upper second or higher degree class). Similarly, Gomez et al investigate the impact of the industrial placement on Bioscience undergraduates at the University of the West of England, Bristol.

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Mandilaras’ study addresses a host of control variables (including gender, nationality and prior study of mathematics and economics) that might otherwise undermine any assertions about correlation. Moreover, Gomez et al’s study meticulously takes into account variables such as gender, pre-university qualifications and level 1, 2 and 3 aggregate marks (as percentages). Both studies suggest a correlation between placements and final degree results. Mandilaras cites ‘the statistical analysis offers evidence that participation in the placement scheme significantly increases the chances of obtaining an upper second or higher degree class’ (Mandilaras, 2004, p.39). Whilst Gomez et al comment that ‘On average, placement students gain an advantage of nearly 4% in their final year performance’ (Gomez et al, 2004, p.373).

In exploring the possibility of correlation, this paper compares the final degree results of engineering placement students with that of their non-placement counterparts for three cohorts: engineering finalists of 2005, 2006 and 2007 at the University of Leicester. The analysis section discusses these results and their implications.

Background: Engineering at the University of Leicester The Department of Engineering at the University of Leicester is renowned for its research and academic excellence, having achieved a rating of 5A in the latest HEFCE Research Assessment Exercise. The department has roughly 240 undergraduate students, 80 taught postgraduate students, and 50 postgraduate and postdoctoral researchers. Its well-established industrial placement programme gives students the opportunity to embark upon a full year in industry within the following degree programmes: General Engineering Mechanical Engineering

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Electrical and Electronic Engineering Communications and Electronic Engineering Embedded Systems Engineering

Students are fully supported in securing industrial placements. They are given a suite of preparatory sessions, placement support materials, visits from the placement tutor during the year in industry and information about suitable placement employers. Indeed the Engineering Department has long-standing relationships with a host of engineering employers who have offered placements to Leicester students, but ultimately, it is the responsibility of the student to secure their own placement.

Past students have taken up industrial work placements with a host of blue-chip employers such as Toyota, Corus and Caterpillar. Students are assessed on the basis of an industrial placement report that must be submitted on completion of the placement. Assessment is marked on a pass/fail basis.

Methodology Whilst this study does not maintain the level of scrutiny of Mandilaras’ work, it does take into consideration key variables. Firstly it accounts for the varied academic abilities of students based on level 1aggregate marks (as percentages) from the degree. Secondly, it also factors in the students’ year of graduation. Finally it addresses academic ability based upon students completing a MEng degree and those completing a BEng degree. Efforts were made to ensure the students sampled included those likely to get a third, as well as those on target for an upper second (2:1) and a first degree classification, thus negating suggestions of skewed results or statistical bias. This section of the paper will now discuss these variables in more detail.

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In attempting to assess whether the engineering industrial placement enhances students’ academic performance, the research methodology selected was that of a comparative study. As such, this study scrutinised the academic performances of 80 engineering finalists (compared with the 124 economics students sampled in Mandilaras’ study and the 164 bioscience students in Gomez et al’s study). 40 of those sampled had undertaken an industrial work placement and the remaining 40 had not.

Mechanisms were put in place to provide optimum sampling and avoid skewed results or statistical bias. Firstly, whilst the selection of students (i.e. the 40 placement students and the 40 non-placement students) was randomised, the selection for each group was established from a pool of student sub-groups. The three sub-groups were categorised on the basis of students’ academic attainment in the first year of their engineering degree. Hence, one sub-group consisted of students whose first year credit-weighted average mark equated to a third class degree (average <50%), whilst the other two sub-groups represented those achieving first year credit-weighted average marks of an upper second/2:1 (60% = average <69%) and a first class average mark (>=70%) respectively. Based on this spread of first year academic performance amongst the sample, one could reasonably argue that the binomial distribution of the sample was legitimate.

The year of graduation was another area under scrutiny from the aforementioned sample. Hence, finalists from 2005, 2006 and 2007 were included. The rationale for this was to counter any statistical anomalies that might occur if the study had focused solely on one particular year.

Finally, both BEng and MEng students across all engineering disciplines (e.g. Mechanical Engineering, Electrical & Electronic Engineering) were included in the study. MEng students are known to perform better academically (which is the reason why they take the more rigorous MEng degree). Had this study omitted BEng students, then any conclusions drawn from the statistical analysis would

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have been flawed, given that the sample population would have consisted of the more academically-able MEng students, hence those more likely to attain a higher degree class in any case.

For the method of analysis, it was decided that measuring academic performance by percentage increase/decrease would be expedient. Therefore this study measured: overall percentage increase in degree results for the 40 placement students overall percentage increase in degree results for the 40 non-placement students the top ten individual percentage increases in degree results by placement/non-placement students

Overall percentage increase was calculated by first calculating the percentage increase of individual academic results (i.e. subtracting the base year results from the final year results, then dividing this figure by the base year figure and finally multiplying by 100). In essence, it calculates the extent to which the student in question has augmented their academic performance from the start of their degree to the time they completed. The formula for this is as follows:

(y X - y 1) X 100 y1 where y1 = base year (first year’s final mark/score) y X = final year’s final mark/score

Secondly, once the percentage increase was calculated for all 40 individual samples in the two main groups (i.e. placement and non-placement), they were

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totalled up for each group respectively. Hence the 40 individual percentage increases for placement students were added together to provide the overall percentage increase in degree results and the same was done for the nonplacement group. The omission of a regression analysis is a noticeable flaw with the methodology.

Analysis The computation of overall percentage increase in both groups of 40 illustrates a substantial difference in academic attainment. The overall percentage increase for placement students equals 112%. This figure subsumes the placement students from 2005-7 and thus addresses (to an extent) statistical anomalies that may occur in any given year.

In contrast, the corresponding statistic for the non-placement cohort equates to 72.8%, thus representing an overall percentage difference of 39.2% between the two cohorts over the same period. Figure 1 illustrates this difference. Figure 1: Overall percentage increase in degree results, 2005-7 for placements students and non-placement students

Non-placement students, 2005-7

Placement student, 2005-7

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50

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100

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The other measure employed to test for a causal relationship between an industrial placement and better academic performance, is the recording of the top ten highest individual percentage increases in degree results by placement/non-placement students.

As with the overall percentage increase, this measure is obtained by considering all engineering disciplines and the years 2005-7. By isolating the best performers, this measure enables one to track which group featured most in the top ten of highest percentage increases. Figure 2 illustrates the results of the top ten highest percentage increases regardless of year, whilst figure 3 shows the best individual performance broken down by year and group.

Figure 2: Top ten student placing by highest percentage increases

where

= placement student and

= non-placement student

25 1st 20

2nd 3rd

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6th 7th

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8th 9th

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10th 1st

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7th

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Figure 3: Single highest percentage increase by any one student, by year (per cohort)

25 20 15 Placement students

10

Non-placement students

5 0 2005

2006

2007

Whilst figures 2 and 3 illustrate that it is in fact a non-placement student that achieves the accolade of having the highest percentage increase amongst all those sampled (albeit only by 0.3%), closer inspection of the results highlights two salient points.

Firstly, placement students feature seven times in the compilation of the top ten highest percentage increases in figure 2. When assessing the BEng and MEng cohorts individually, (not included within this paper) the results remain the same; placement students still dominate the majority of places in the top ten.

Secondly, figure 3 illustrates the marginal superior percentage increase of the non-placement student compared with the placement student for 2005. This marginal difference stands at 0.3% (2005 figures: placement student figure, 19.2%, non-placement student figure, 19.5%).

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However, when observing years 2006 and 2007, it is indeed the placement student that has the superior percentage increase with a difference over the non-placement student of 2.9% for both 2006 and 2007 (2006 figures: – placement student figure, 10.1%, non-placement student figure, 7.2% and 2007 figures: placement student figure, 15.5%, non-placement student figure, 12.6%).

The findings from the two measures, (that of overall percentage increase and that of top ten individual percentage increases) seem to corroborate earlier studies and point towards a strong correlation between participation in placements and academic achievement. This argument is strengthened by the fact that the biggest gains in percentage increase occurred amongst those who were previously underperforming (i.e. those achieving a credit-weighted average mark of a third - average <50%).

Discussion So why are industrial work placements responsible for augmenting academic performance in students? The Confederation of British Industry’s Higher Education Task Force (2009) stresses the significance of improved student confidence resulting from a year in industry. In their report they claim ‘increased confidence is widely mentioned by universities, employers and students as a beneficial outcome of work-related learning and formal work placements’ (Confederation of British Industry, 2009, p.17).

However this does not fully explain why a work placement student should go on to attain a better degree result. Others have postulated that metacognition (learning to learn) is responsible for the improved performance of the student returning to their final year of study after their placement.

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Raelin (2000) identifies metacognition as an inherent value-added trait of workbased learning, whilst Moreland (2005) views metacognition and the related cognitive and learning styles as components of the broader field of work-related learning. It is possible that the nature and environment of an industrial work placement (and contact with professional work colleagues) instils the metacognitive skills necessary for personal reflection, development and enriched independent learning. Therefore, on returning to university, the student transfers this new approach to her/his studies and excels.

Another hypothesis is that put forth by Mandilaras (2004). Mandilaras identifies some potential explanations for the improved academic attainment of returning placement students. In his paper he asserts ‘it is possible that the placement experience enables the students to mature more quickly than they otherwise would. Spending a year working in often competitive environments makes them realise that their future professional development is to an extent, related to their academic performance. Hence their ambition is stimulated, they come back to university more focused and determined to do well’ (Mandilaras, 2004, p.48).

Clearly, there is a level of credibility associated with this hypothesis. Anecdotal evidence aside, the belief that a student fully immersed in a professional work context for the duration of a year, might then return to their studies with a more mature outlook is highly plausible. Additionally Gomez et al (2004) provide further insights that might explain this phenomenon. Gomez et al postulate ‘One simple factor that may be important is that students returning from placement are tackling the rigours of the level 3 study one year older than they would otherwise be’ (Gomez et al, 2004, p.382).

Here Gomez et al suggests the academic improvement of the placement student may stem from the fact that the placement student will be completing their final year studies a year later. The supposition being, the older student is better Page 12

equipped to perform well in the final year of their degree than their younger, non-placement counterparts. Gomez et al goes on to say ‘Quite often, a placement student undertakes a final year research project in a completely different area to that experienced during their placement, although some....skills will be generic. Therefore, it is more likely that the generic skills of team-working, communication, self-reliance and confidence, time keeping, etc., transfer to their approach to the project. Placement students may also benefit from seeing the practical applications of their studies outside the academic world and therefore relate to their studies with a greater insight (Gomez et al, 2004, p.382).

As Gomez el al suggest, could the explanation for the academic-enhancement properties of placements lie in the fact that placements equip students with highly developed transferable skills?

The insights provided by Mandilaras and Gomez et al are supported by other areas of research that scrutinise the relationship between industrial placements and transferable/employability skills. For example, Knight & Yorke (2004) refer to the survey that sought the views of employers and recently appointed graduate employees. The findings from this study suggests overwhelming consensus from both cohorts that work placements are a major factor in the development of transferable skills and personal development.

Additionally, in their contribution to the Learning & Employability series of publications, Knight & Yorke (2004) claim that ‘the thick sandwich (i.e. sandwich degree) typically involves a one-year placement.....The experience is widely held to benefit the student....anecdotal evidence attests to greater self-confidence and awareness’ (Knight & Yorke, 2004, p.16).

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It is not difficult to recognise that the application of skills needed in a professional work environment may cross over to those necessary to excel in academia. Indeed, it has been reported by engineering academic staff at the University of Leicester, that students returning from a year in industry display an enhanced level of maturity, focus and generic skills, thus giving some weight to the hypothesises put forth by Mandilaras and Gomez et al.

Whilst caution must be exercised concerning the results of this study (they cannot be deemed fully conclusive by any measure), these findings are profound for they justify the presence and further development of work-based learning elements in the curricula of universities, not only as a means by which to enhance students’ employability, but also as a mechanism by which to possibly augment academic learning. Indeed work placements remain the best mechanism by which to illustrate to students, the application of their academic studies to the world of work and vice versa.

Conclusion By utilising data from the University of Leicester’s Department of Engineering, this paper has examined the efficacy of industrial work placements on improving academic performance amongst engineering students. Evidently, the findings illustrate a causal link between placements and improved academic performance. The robustness of the statistical evidence is limited by the sample size and the sampling methods adopted. The omission of any regression analysis limits the evidence gained from this study.

Additionally, further research might usefully compare placement students’ results with those of the entire cohort/year of engineering students. Limitations aside, the findings from this research provides justification for the presence of quality-assured industrial work placements in academia, as such programmes not only augment the employability of the student, but they also enhance their maturity and academic prowess.

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This paper also informs work-related learning practitioners and academics alike, that the continual development of work-based learning within curricula should be actively encouraged in order to aid students in comprehending the application of their studies to industry.

Acknowledgement I would like to extend my gratitude to Dr Aldo Rona from the Department of Engineering at the University of Leicester for his assistance during the compilation of this research.

References Bowes, L. & Harvey, L. (1999) The Impact of Sandwich Education on the Activities of Graduates Six Months Post-Graduation, Birmingham: Centre for Research into Quality. Confederation of British Industry (2009) Future Fit: Preparing Graduates for the World of Work, London: Confederation of British Industry Higher Education Task Force. Davies, L. (2003) Experience-based Learning within the Curriculum – a synthesis study, Sheffield: Association for Sandwich Education and Training. Gomez, S., Lush, D. & Clements, M. (2004) Work Placements Enhance the Academic Performance of Bioscience Undergraduates, Journal of Vocational Education and Training, vol. 56, no 3, pp. 373-386. Knight, P. & Yorke, M. (2004) Learning, Curriculum and Employability in Higher Education, London: RoutledgeFalmer. Knight, P. & Yorke, M. (2004) Embedding Employability into the Curriculum, York: Higher Education Authority. Little, B. & Harvey, L. (2006) Learning Through Work Placements and Beyond, Sheffield: Centre for Research and Evaluation.

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Mandilaras, A. (2004) Industrial Placement and Degree Performance: Evidence from a British Higher Institution, International Review of Economics Education, vol. 3, no. 1, pp. 39-51. Mayo, R. & Jones, and L. (1985) Proceedings of the Fourth World Conference on Co-operative Education, pp 428-31, Edinburgh: Napier College. Moreland, N. (2005) Work-related Learning in Higher Education, York: Higher Education Authority. Raelin, J. (2000) Work-based Learning: The New Frontier of Management Development, New Jersey: Prentice Hall.

About the author Richard Mendez (MBA, BA) is the Work-related Learning & Employability Tutor/Officer at the University of Leicester. He is responsible for developing and teaching aspects of work-related learning within academic departments. His most recent work has included the development of a credit-based employability module embedded within the Mathematics with Management degree programme at Leicester.

Richard is also the programme convenor for Access to Employability, a programme that aims to enhance the employability of students with disabilities through specialist workshops and pre-arranged work placements with local employers. Richard is a member of the Chartered Management Institute (CMI), the Association for Sandwich Degree Education and Training (ASET) and an affiliate member of the Association for Graduate Careers Advisory Services (AGCAS).

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