The Case Study as a Research Method
Uses and Users of Information -- LIS 391D.1 -- Spring 1997
Introduction
Case study research excels at bringing us to an understanding of a complex issue or object and can extend experience or add strength to what is already known through previous research. Case studies emphasize detailed contextual analysis of a limited number of events or conditions and their relationships. Researchers have used the case study research method for many years across a variety of disciplines. Social scientists, in particular, have made wide use of this qualitative research method to examine contemporary real-life situations and provide the basis for the application of ideas and extension of methods. Researcher Robert K. Yin defines the case study research method as an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used (Yin, 1984, p. 23).
Critics of the case study method believe that the study of a small number of cases can offer no grounds for establishing reliability or generality of findings. Others feel that the intense exposure to study of the case biases the findings. Some dismiss case study research as useful only as an exploratory tool. Yet researchers continue to use the case study research method with success in carefully planned and crafted studies of real-life situations, issues, and problems. Reports on case studies from many disciplines are widely available in the literature.
This paper explains how to use the case study method and then applies the method to an example case study project designed to examine how one set of users, non-profit organizations, make use of an electronic community network. The study examines the issue of whether or not the electronic community network is beneficial in some way to non-profit organizations and what those benefits might be.
Many well-known case study researchers such as Robert E. Stake, Helen Simons, and Robert K. Yin have written about case study research and suggested techniques for organizing and conducting the research successfully. This introduction to case study research draws upon their work and proposes six steps that should be used:
• Determine and define the research questions
• Select the cases and determine data gathering and analysis techniques
• Prepare to collect the data
• Collect data in the field
• Evaluate and analyze the data
• Prepare the report
Step 1. Determine and Define the Research Questions
The first step in case study research is to establish a firm research focus to which the researcher can refer over the course of study of a complex phenomenon or object. The researcher establishes the focus of the study by forming questions about the situation or problem to be studied and determining a purpose for the study. The research object in a case study is often a program, an entity, a person, or a group of people. Each object is likely to be intricately connected to political, social, historical, and personal issues, providing wide ranging possibilities for questions and adding complexity to the case study. The researcher investigates the object of the case study in depth using a variety of data gathering methods to produce evidence that leads to understanding of the case and answers the research questions.
Case study research generally answers one or more questions which begin with "how" or "why." The questions are targeted to a limited number of events or conditions and their inter-relationships. To assist in targeting and formulating the questions, researchers conduct a literature review. This review establishes what research has been previously conducted and leads to refined, insightful questions about the problem. Careful definition of the questions at the start pinpoints where to look for evidence and helps determine the methods of analysis to be used in the study. The literature review, definition of the purpose of the case study, and early determination of the potential audience for the final report guide how the study will be designed, conducted, and publicly reported.
Step 2. Select the Cases and Determine Data Gathering and Analysis Techniques
During the design phase of case study research, the researcher determines what approaches to use in selecting single or multiple real-life cases to examine in depth and which instruments and data gathering approaches to use. When using multiple cases, each case is treated as a single case. Each case’s conclusions can then be used as information contributing to the whole study, but each case remains a single case. Exemplary case studies carefully select cases and carefully examine the choices available from among many research tools available in order to increase the validity of the study. Careful discrimination at the point of selection also helps erect boundaries around the case.
The researcher must determine whether to study cases which are unique in some way or cases which are considered typical and may also select cases to represent a variety of geographic regions, a variety of size parameters, or other parameters. A useful step in the selection process is to repeatedly refer back to the purpose of the study in order to focus attention on where to look for cases and evidence that will satisfy the purpose of the study and answer the research questions posed. Selecting multiple or single cases is a key element, but a case study can include more than one unit of embedded analysis. For example, a case study may involve study of a single industry and a firm participating in that industry. This type of case study involves two levels of analysis and increases the complexity and amount of data to be gathered and analyzed.
A key strength of the case study method involves using multiple sources and techniques in the data gathering process. The researcher determines in advance what evidence to gather and what analysis techniques to use with the data to answer the research questions. Data gathered is normally largely qualitative, but it may also be quantitative. Tools to collect data can include surveys, interviews, documentation review, observation, and even the collection of physical artifacts.
The researcher must use the designated data gathering tools systematically and properly in collecting the evidence. Throughout the design phase, researchers must ensure that the study is well constructed to ensure construct validity, internal validity, external validity, and reliability. Construct validity requires the researcher to use the correct measures for the concepts being studied. Internal validity (especially important with explanatory or causal studies) demonstrates that certain conditions lead to other conditions and requires the use of multiple pieces of evidence from multiple sources to uncover convergent lines of inquiry. The researcher strives to establish a chain of evidence forward and backward. External validity reflects whether or not findings are generalizable beyond the immediate case or cases; the more variations in places, people, and procedures a case study can withstand and still yield the same findings, the more external validity. Techniques such as cross-case examination and within-case examination along with literature review helps ensure external validity. Reliability refers to the stability, accuracy, and precision of measurement. Exemplary case study design ensures that the procedures used are well documented and can be repeated with the same results over and over again.
Step 3. Prepare to Collect the Data
Because case study research generates a large amount of data from multiple sources, systematic organization of the data is important to prevent the researcher from becoming overwhelmed by the amount of data and to prevent the researcher from losing sight of the original research purpose and questions. Advance preparation assists in handling large amounts of data in a documented and systematic fashion. Researchers prepare databases to assist with categorizing, sorting, storing, and retrieving data for analysis.
Exemplary case studies prepare good training programs for investigators, establish clear protocols and procedures in advance of investigator field work, and conduct a pilot study in advance of moving into the field in order to remove obvious barriers and problems. The investigator training program covers the basic concepts of the study, terminology, processes, and methods, and teaches investigators how to properly apply the techniques being used in the study. The program also trains investigators to understand how the gathering of data using multiple techniques strengthens the study by providing opportunities for triangulation during the analysis phase of the study. The program covers protocols for case study research, including time deadlines, formats for narrative reporting and field notes, guidelines for collection of documents, and guidelines for field procedures to be used. Investigators need to be good listeners who can hear exactly the words being used by those interviewed. Qualifications for investigators also include being able to ask good questions and interpret answers. Good investigators review documents looking for facts, but also read between the lines and pursue collaborative evidence elsewhere when that seems appropriate. Investigators need to be flexible in real-life situations and not feel threatened by unexpected change, missed appointments, or lack of office space. Investigators need to understand the purpose of the study and grasp the issues and must be open to contrary findings. Investigators must also be aware that they are going into the world of real human beings who may be threatened or unsure of what the case study will bring.
After investigators are trained, the final advance preparation step is to select a pilot site and conduct a pilot test using each data gathering method so that problematic areas can be uncovered and corrected. Researchers need to anticipate key problems and events, identify key people, prepare letters of introduction, establish rules for confidentiality, and actively seek opportunities to revisit and revise the research design in order to address and add to the original set of research questions.
4. Collect Data in the Field
The researcher must collect and store multiple sources of evidence comprehensively and systematically, in formats that can be referenced and sorted so that converging lines of inquiry and patterns can be uncovered. Researchers carefully observe the object of the case study and identify causal factors associated with the observed phenomenon. Renegotiation of arrangements with the objects of the study or addition of questions to interviews may be necessary as the study progresses. Case study research is flexible, but when changes are made, they are documented systematically.
Exemplary case studies use field notes and databases to categorize and reference data so that it is readily available for subsequent reinterpretation. Field notes record feelings and intuitive hunches, pose questions, and document the work in progress. They record testimonies, stories, and illustrations which can be used in later reports. They may warn of impending bias because of the detailed exposure of the client to special attention, or give an early signal that a pattern is emerging. They assist in determining whether or not the inquiry needs to be reformulated or redefined based on what is being observed. Field notes should be kept separate from the data being collected and stored for analysis.
Maintaining the relationship between the issue and the evidence is mandatory. The researcher may enter some data into a database and physically store other data, but the researcher documents, classifies, and cross-references all evidence so that it can be efficiently recalled for sorting and examination over the course of the study.
Step 5. Evaluate and Analyze the Data
The researcher examines raw data using many interpretations in order to find linkages between the research object and the outcomes with reference to the original research questions. Throughout the evaluation and analysis process, the researcher remains open to new opportunities and insights. The case study method, with its use of multiple data collection methods and analysis techniques, provides researchers with opportunities to triangulate data in order to strengthen the research findings and conclusions.
The tactics used in analysis force researchers to move beyond initial impressions to improve the likelihood of accurate and reliable findings. Exemplary case studies will deliberately sort the data in many different ways to expose or create new insights and will deliberately look for conflicting data to disconfirm the analysis. Researchers categorize, tabulate, and recombine data to address the initial propositions or purpose of the study, and conduct cross-checks of facts and discrepancies in accounts. Focused, short, repeat interviews may be necessary to gather additional data to verify key observations or check a fact.
Specific techniques include placing information into arrays, creating matrices of categories, creating flow charts or other displays, and tabulating frequency of events. Researchers use the quantitative data that has been collected to corroborate and support the qualitative data which is most useful for understanding the rationale or theory underlying relationships. Another technique is to use multiple investigators to gain the advantage provided when a variety of perspectives and insights examine the data and the patterns. When the multiple observations converge, confidence in the findings increases. Conflicting perceptions, on the other hand, cause the researchers to pry more deeply.
Another technique, the cross-case search for patterns, keeps investigators from reaching premature conclusions by requiring that investigators look at the data in many different ways. Cross-case analysis divides the data by type across all cases investigated. One researcher then examines the data of that type thoroughly. When a pattern from one data type is corroborated by the evidence from another, the finding is stronger. When evidence conflicts, deeper probing of the differences is necessary to identify the cause or source of conflict. In all cases, the researcher treats the evidence fairly to produce analytic conclusions answering the original "how" and "why" research questions.
Step 6. Prepare the report
Exemplary case studies report the data in a way that transforms a complex issue into one that can be understood, allowing the reader to question and examine the study and reach an understanding independent of the researcher. The goal of the written report is to portray a complex problem in a way that conveys a vicarious experience to the reader. Case studies present data in very publicly accessible ways and may lead the reader to apply the experience in his or her own real-life situation. Researchers pay particular attention to displaying sufficient evidence to gain the reader’s confidence that all avenues have been explored, clearly communicating the boundaries of the case, and giving special attention to conflicting propositions.
Techniques for composing the report can include handling each case as a separate chapter or treating the case as a chronological recounting. Some researchers report the case study as a story. During the report preparation process, researchers critically examine the document looking for ways the report is incomplete. The researcher uses representative audience groups to review and comment on the draft document. Based on the comments, the researcher rewrites and makes revisions. Some case study researchers suggest that the document review audience include a journalist and some suggest that the documents should be reviewed by the participants in the study.
Applying the Case Study Method to an Electronic Community Network
By way of example, we apply these six steps to an example study of multiple participants in an electronic community network. All participants are non-profit organizations which have chosen an electronic community network on the World Wide Web as a method of delivering information to the public. The case study method is applicable to this set of users because it can be used to examine the issue of whether or not the electronic community network is beneficial in some way to the organization and what those benefits might be.
Step 1. Determine and Define the Research Questions
In general, electronic community networks have three distinct types of users, each one a good candidate for case study research. The three groups of users include people around the world who use the electronic community network, the non-profit organizations using the electronic community network to provide information to potential users of their services, and the "community" that forms as the result of interacting with other participants on the electronic community network.
In this case, the researcher is primarily interested in determining whether or not the electronic community network is beneficial in some way to non-profit organization participants. The researcher begins with a review of the literature to determine what prior studies have determined about this issue and uses the literature to define the following questions for the study of the non-profit organizations providing information to the electronic community network:
Why do non-profit organization participants use the network?
How do non-profit organization participants determine what to place on the electronic community network?
Do the non-profit organization participants believe the community network serves a useful purpose in furthering their mission? How?
Step 2. Select the Cases and Determine Data Gathering and Analysis Techniques
Many communities have constructed electronic community networks on the World Wide Web. At the outset of the design phase, the researcher determines that only one of these networks will be studied and further sets the study boundaries to include only some of the non-profit organizations represented on that one network. The researcher contacts the Board of Directors of the community network, who are open to the idea of the case study. The researcher also gathers computer generated log data from the network and, using this data, determines that an in-depth study of representative organizations from four categories -- health care, environmental, education, and religious -- is feasible. The investigator applies additional selection criteria so that an urban-based and a rural-based non-profit are represented in the study in order to examine whether urban non-profits perceive more benefits from community networks than rural organizations.
The researcher considers multiple sources of data for this study and selects document examination, the gathering and study of organizational documents such as administrative reports, agendas, letters, minutes, and news clippings for each of the organizations. In this case, the investigator decides to also conduct open-ended interviews with key members of each organization using a check-list to guide interviewers during the interview process so that uniformity and consistency can be assured in the data, which could include facts, opinions, and unexpected insights. In this case study, the researcher cannot employ direct observation as a tool because some of the organizations involved have no office and meet infrequently to conduct business directly related to the electronic community network. The researcher instead decides to survey all Board members of the selected organizations using a questionnaire as a third data gathering tool. Within-case and cross-case analysis of data are selected as analysis techniques.
Step 3. Prepare to Collect the Data
The researcher prepares to collect data by first contacting each organization to be studied to gain their cooperation, explain the purpose of the study, and assemble key contact information. Since data to be collected and examined includes organizational documents, the researcher states his intent to request copies of these documents, and plans for storage, classification, and retrieval of these items, as well as the interview and survey data. The researcher develops a formal investigator training program to include seminar topics on non-profit organizations and their structures in each of the four categories selected for this study. The training program also includes practice sessions in conducting open-ended interviews and documenting sources, suggested field notes formats, and a detailed explanation of the purpose of the case study. The researcher selects a fifth case as a pilot case, and the investigators apply the data gathering tools to the pilot case to determine whether the planned timeline is feasible and whether or not the interview and survey questions are appropriate and effective. Based on the results of the pilot, the researcher makes adjustments and assigns investigators particular cases which become their area of expertise in the evaluation and analysis of the data.
Step 4. Collect Data in the Field
Investigators first arrange to visit with the Board of Directors of each non-profit organization as a group and ask for copies of the organization’s mission, news clippings, brochures, and any other written material describing the organization and its purpose. The investigator reviews the purpose of the study with the entire Board, schedules individual interview times with as many Board members as can cooperate, confirms key contact data, and requests that all Board members respond to the written survey which will be mailed later.
Investigators take written notes during the interview and record field notes after the interview is completed. The interviews, although open-ended, are structured around the research questions defined at the start of the case study.
Research Question: Why do non-profit organization participants use the network?
Interview Questions: How did the organization make the decision to place data on the World Wide Web community network? What need was the organization hoping to fulfill?
Research Question: How do non-profit organization participants determine what to place on the electronic community network?
Interview Questions: What process was used to select the information that would be used on the network? How is the information kept up to date?
Research Question: Do the non-profit organization participants believe the community network serves a useful purpose in furthering their mission? How?
Interview Questions: How does the organization know if the electronic community network is beneficial to the organization? How does the electronic community network further the mission of the organization? What systematic tracking mechanisms exist to determine how many or what types of users are accessing the organization information?
The investigator’s field notes record impressions and questions that might assist with the interpretation of the interview data. The investigator makes note of stories told during open-ended interviews and flags them for potential use in the final report. Data is entered into the database.
The researcher mails written surveys to all Board members with a requested return date and a stamped return envelope. Once the surveys are returned, the researcher codes and enters the data into the database so that it can be used independently as well as integrated when the case study progresses to the point of cross-case examination of data for all four cases.
Step 5. Evaluate and Analyze the Data
Within-case analysis is the first analysis technique used with each non-profit organization under study. The assigned investigator studies each organization’s written documentation and survey response data as a separate case to identify unique patterns within the data for that single organization. Individual investigators prepare detailed case study write-ups for each organization, categorizing interview questions and answers and examining the data for within-group similarities and differences.
Cross-case analysis follows. Investigators examine pairs of cases, categorizing the similarities and differences in each pair. Investigators then examine similar pairs for differences, and dissimilar pairs for similarities. As patterns begin to emerge, certain evidence may stand out as being in conflict with the patterns. In those cases, the investigator conducts follow-up focused interviews to confirm or correct the initial data in order to tie the evidence to the findings and to state relationships in answer to the research questions.
Step 6 Prepare the Report
The outline of the report includes thanking all of the participants, stating the problem, listing the research questions, describing the methods used to conduct the research and any potential flaws in the method used, explaining the data gathering and analysis techniques used, and concluding with the answers to the questions and suggestions for further research. Key features of the report include a retelling of specific stories related to the successes or disappointments experienced by the organizations that were conveyed during data collection, and answers or comments illuminating issues directly related to the research questions. The researcher develops each issue using quotations or other details from the data collected, and points out the triangulation of data where applicable. The report also includes confirming and conflicting findings from literature reviews. The report conclusion makes assertions and suggestions for further research activity, so that another researcher may apply these techniques to another electronic community network and its participants to determine whether similar findings are identifiable in other communities. Final report distribution includes all participants.
Applicability to Library and Information Science
Case study research, with its applicability across many disciplines, is an appropriate methodology to use in library studies. In Library and Information Science, case study research has been used to study reasons why library school programs close (Paris, 1988), to examine reference service practices in university library settings (Lawson, 1971), and to examine how questions are negotiated between customers and librarians (Taylor, 1967). Much of the research is focused exclusively on the librarian as the object or the customer as the object. Researchers could use the case study method to further study the role of the librarian in implementing specific models of service. For example, case study research could examine how information-seeking behavior in public libraries compares with information-seeking behavior in places other than libraries, to conduct in-depth studies of non-library community based information services to compare with library based community information services, and to study community networks based in libraries.
Conclusion
Case studies are complex because they generally involve multiple sources of data, may include multiple cases within a study, and produce large amounts of data for analysis. Researchers from many disciplines use the case study method to build upon theory, to produce new theory, to dispute or challenge theory, to explain a situation, to provide a basis to apply solutions to situations, to explore, or to describe an object or phenomenon. The advantages of the case study method are its applicability to real-life, contemporary, human situations and its public accessibility through written reports. Case study results relate directly to the common reader’s everyday experience and facilitate an understanding of complex real-life situations.
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Ismail Aby Jamal
I say man, am I leader...
Saturday, June 25, 2011
DEDICATED TO BERSIH RALLY 9TH OF JULY 2011.....
GANDHI “We will not strike a blow – but we will receive them. And through our pain we will make them see their injustice (quickly) and it will hurt, as all fighting hurts! (Utter silence.) . . . But we cannot lose. We cannot. (He looks down at the police.) Because they may torture my body, may break my bones, even kill me . . . (Up to the house) They will then have my dead body – not my obedience.”
Thursday, February 17, 2011
Perhimpunan Keluarga / Zuriat Engku Paduka Tuan & Engku Muda Tanjung dari Waris Temenggong Muar
How Much Does Higher Education Enhance the Employability of Graduates?
Report to HEFCE
Contents
1. Introduction 2
2. Enhancing Employability in English Universities 11
3. Employability Skills Development and Graduate Employment Outcomes 33
4. Survey Methodology 45
5. Graduates’ Career Progress and Line Managers’ Recruitment Criteria 52
6. The Development and Utilisation of Graduate Skills and Knowledge 64
7. Graduate Skill Gaps and Employer-provided Training 80
8. Employability Skills and Graduate Job Performance and Career Progress: Multivariate Analysis 92
Acknowledgements 111
References 111
Appendices:
A. Departmental Employability Skills Scores 117
B. Telephone Survey Sample Selection Methods and Response Rate 124
C. Supplementary Tables 128
D. Interview Schedule Used in Sample University Departments 133
Geoff Mason, National Institute of Economic and Social Research and Gareth Williams, Sue Cranmer and David Guile, Institute of Education, University of London
Chapter 1:
Introduction
The principal aim of this study was to investigate universities’ efforts to enhance graduate employability and the extent to which they are successful. This report provides new evidence on how higher education courses seek to improve the employability of their graduates, and evaluates the success of these in the light of graduates’ experiences in finding their first employment and their experiences in their early years of employment.
The methodology was designed to obtain a threefold ‘fix’ on the relationship between recent graduate recruits’ work performance and their learning experiences in higher education. One triangulation point was the universities’ own perceptions of the opportunities for employment-relevant learning that they are offering their students. The second was information on graduates’ first employment and their own early work experiences, and their perceptions of the contributions to skills development that had been made by their higher education programmes. The third was to gather systematic opinions of more senior people with direct knowledge of the work performance of individual graduates: the category selected for this was the line managers of individual graduates.
The study had to be selective. Students study a wide range of subjects, and graduates enter a wide range of occupations. It focuses on graduates in five subject areas: biological sciences, business studies, computer science/studies, design studies and history. These subjects were selected in order to obtain a mix of long-standing vocational areas, more recently established vocational subjects and courses where First Destinations data point to a wide range of experiences of initial entry to employment.
Chapter 2 reports on visits to 34 departments in eight universities in order to ascertain what changes have been made in recent years to employability skills teaching and learning. Chapter 3 is an analysis of First Destination survey data for all graduates in the year 2000 from the sample departments. Chapters 4 to 7 give the results of a telephone survey of recent graduates in the subjects being investigated and the parallel survey of their immediate line managers.
Recent Issues in the Development of Graduate Employability
Employability skills and Higher Education
Until the massive expansion of UK higher education in the late 1980s and early 1990s the employability of graduates was largely taken for granted by higher education institutions. Most graduates found satisfactory employment within a short time after graduation and earned sufficiently high incomes to show high private and social rates of return. The types of employment available to graduates were fairly well defined and preparation for employment meant the acquisition, often implicitly, of the knowledge and technical and social skills needed for these occupations. While some employers had complained from the 1970s onwards that many graduates did not have the precise skills they needed, most employers were keen to snap up whatever graduates were available.
The idea that graduates should be expected to possess certain general qualities and attributes as a result of their higher education experience is long established. A century and a half ago, Cardinal Newman suggested that higher education enabled individuals, ‘to see things as they are, to go right to the point, to disentangle a skein of thought, to detect what is sophistical and to discard what is irrelevant… to fill any post with credit and to master any subject with facility’ (quoted in Griffiths 1999). More recently, the Dearing Report (HMSO 1997) defined the aim of higher education as being, ‘to inspire and enable individuals to develop their capabilities to the highest potential levels throughout life, so that they grow intellectually, are well equipped for work, can contribute effectively to society and achieve personal fulfilment’. Both viewpoints, separated by nearly 150 years, recognise the link between higher education and skill development in a way that is often overlooked.
In the 1980s, along with many other changes in the UK economy, complacency about the employability of graduates began to be systematically challenged. The harbinger was the Enterprise in Higher Education Initiative, which offered universities and polytechnics, very short of funds after the massive cuts of the early 1980s, additional resources for developments that laid more emphasis than previously on the needs of a rapidly changing economy. However, it was the rapid shift between 1989 and 1994 to mass enrolment that contributed most to public interest in graduate employability issues.
Since 1990 there have been many reports and papers urging the higher education sector to take key, core, transferable and employability skills into the heart of students’ learning experiences. They have come from the Government, industry (AGR 1993, 1995, CBI 1989, 1995, 1999) and from higher education agencies (CVCP 1998, CIHE 1996, Harvey and Locke, 2002) and higher education researchers (e.g. Harvey et al 1997, Smith et al 2000, McKnight et al, 2001, Brennan, 2000, Brennan et al 2001). The common concern has been that under the intensifying pressure of global competition very large numbers of graduates need to offer employers more than the academic skills traditionally represented by the subject and class of degree.
The belief that the Newman skills have always been ‘implicit’ in the process of knowledge acquisition and, as a corollary, that higher education has always been concerned with the development of the whole person as well as the knowledge, attributes and skills which any educated person should expect to have by the time of graduation, became known in the mid-1990s as ‘graduateness’. It represented an apparent consensus about the value of generic skills (of all kinds) and expressed at a high level of generalisation.
The main focus of the reports of the early 1990s was to propose that universities and colleges should aim to assist graduates to develop the core/transferable/key/generic skills needed in many types of high-level employment. In this report they will all be grouped together under the heading ‘employability skills’, since it is widely assumed that these skills denote graduates’ work readiness (CBI 1989, Hyland 1994, Tribe 1996). Governments from the late 1980s onwards launched various programmes to motivate higher education institutions to sharpen the focus of employability skills in the undergraduate and postgraduate curriculum.
Initially, the consensus about the idea of ‘graduateness’ appeared to provide a way of bridging the challenge that massification had presented; namely a proliferation of different interpretations and values as regards the programmes students were following particularly in modular programmes (Harvey and Knight 1996). It was reasoned that if higher education could make the skills it naturally developed more explicit, then it could be seen to be responding to employers’ and policymakers’ concerns. Soon, however, the concept of ‘graduateness’ was felt not to be sufficiently robust to define the nature of a degree, the necessary threshold standard of a degree or the quality of the degree, especially in a period of unrivalled expansion. (HEQC 1997).
Against this changing background, higher education has been subjected to considerable pressure to offer evidence that graduates have acquired relevant employability skills. The Dearing Report endorsed the economic arguments for developing students’ employability skills. Although the Report acknowledged that employers do not always present consistent messages when it comes to identifying skill needs, it concluded that there was a set of threshold or ‘basic’ skills, which encapsulated the skills employers wanted all graduates to have, and that provision of these should become a central aim for higher education. Dearing defined these skills as Communication, Numeracy, IT and Learning how to Learn at a higher level.
A widely held assumption in the literature has been that graduates who acquire such ‘threshold’ employability skills during their higher education, have improved chances of gaining employment that is appropriate for graduates. This assumption has frequently been cited to counter those who are sceptical about the further expansion of higher education (Keep 1996). The empirical evidence is, however, ambivalent. A number of studies have identified demand from employers in certain sectors of the UK economy for graduates who have specific employability skills (Mason 2001, Westhead 1997). However, other studies have claimed that work experience, for example, is not always viewed positively by employers (Arnold et al 1999).
Employers’ perceptions about the ‘quality’ of graduates from certain universities or university departments still often influence graduate transitions into employment more than whether graduates have followed employability skills courses (Brown and Scase 1994, Purcell et al 1999). Employers who report higher levels of satisfaction with the performance of graduates are more likely to recruit from institutions commanding higher A-level entry scores, thus helping to perpetuate the idea of a graduate elite who possess a broader form of social and cultural capital than graduates from universities with non-traditional entrants that have specifically tried to develop employability skills (Brown and Scase 1994, Hesketh 2001).
Employers have also expressed concern about graduates’ ability to cope with change and to add value by continuing to learn and develop in the workplace (AGR 1995, Harvey et al 1997, Guile and Fonda 1998). Apart from stipulating a continuing demand for key skills, reports and papers also began to articulate the need for additional ‘skills’ that employers expected graduates to display. Two new types of skills were mentioned: meta-cognitive skills such as learning how to learn (AGR 1995), and ‘behavioural attributes’, such as an ability to take responsibility for managing performance at work and career development (Harvey et al 1997).
This focus drew attention to the way firms were using qualifications. Instead of viewing them simply as a statement of graduates’ achievement at the point of recruitment, qualifications were frequently used as indications of potential to achieve in a particular occupational field during their working lives (Chisholm 1999). Furthermore, the increasing proliferation of employability skills lists highlighted the confusion surrounding nomenclature and classification of types of skill (e.g. personal attributes, process skills, technical competencies) that purportedly enhanced graduates’ employability (Atkins 1999, Bennett et al 2000).
In general, the term employability skills has become a ‘chameleon’ concept. Sometimes it is employed to define either a limited set of ‘threshold’ skills or a wide range of ‘knowledge’, ‘skills’ and ‘attributes’ that graduates are expected to demonstrate that they have acquired while studying in higher education (CVCP 1998, Hillage and Pollard 1998). On other occasions, it represents the demand, in many professional occupations, for a mix of the traditional disciplinary and technical knowledge, which have always been developed in higher education, as well as employability skills (Mason 2000). The term ‘employability’ has also been used to convey the idea of graduates’ ‘propensity’ to find work (Harvey 2001).
The term ‘skills’ is itself frequently used to refer to both the characteristics of jobs (e.g. task demands and role requirements) and the qualities of people who perform them (e.g. abilities, talents and capabilities). For example, most employability skills lists propose qualities such as ‘teamworking’, ‘flexibility’ or ‘problem-solving’ as skills that individuals are expected to have developed. These qualities, however, are not strictly speaking ‘skills’ so much as a description of how work is organised. What constitutes a ‘team’ is subject to local definition, and needs to be defined in relation to the working context.
Innovations in teaching and learning
The two most common approaches to skill development have been either to ‘embed’ skills within degree courses or to offer students ‘parallel’ or ‘stand-alone courses. These two approaches are best viewed as representing two ends of a spectrum. At one end, total embedding can refer to a style of delivery whereby the students may not be aware that they are developing employability skills. At the other, ‘bolting-on’ skill modules to the curriculum can result in learning of skills isolated from mainstream academic concerns, and students’ motivation to study them is marginalized.
The stand-alone model has been used to deliver extra-curricular employability skill courses to students by Careers Services. Patterns of careers provision and student attendance vary widely from one HEI to another. Nevertheless, careers programmes have often been perceived by students as helping them to:
• Understand employers’ changing skill demands;
• Produce CVs and develop presentation skills;
• Prepare themselves for undergoing psychometric tests in employers’ assessment centres (Arnold et al 1999).
The effectiveness of stand-alone university courses run by employers and activities, such as the ‘outdoor’ adventure courses that universities offer to students to develop their employability skills, has been found to vary considerably (Hattie et al 1997; Bennett et al 2000; Goldfinch et al 1999). It seems that, all too often, although evaluations of courses designed to develop teamworking skills record that students value the opportunity to develop these skills in university or adventure settings, there has been very little follow-up to establish whether general teamworking abilities have improved. Where stand-alone courses have been perceived to support skill development, it is normally because departments have explicitly provided students the opportunity to use the skills they had been introduced to later on as part of their course of study.
Many higher education institutions reviewed course design in the early 1990s in an attempt to enhance student choice and to introduce greater flexibility of course delivery. One outcome of these developments was a significant extension of modular degree programmes and semesterisation. In general, departments and teams chose to modularise their courses in two main ways. They have either ‘divided up’ existing courses into smaller blocks or they have formulated new criteria, often based on the identification of conceptual learning outcomes and employability skill learning outcomes, in order to redesign teaching, learning and assessment processes (Jenkins and Wallace 1994, Toohey 1997, Dunne 1997). Research evidence suggests that the ‘dividing-up’ approach has rarely resulted in any significant development of employability skills. Staff have continued to adhere to traditional learning and teaching styles, since they felt under pressure to ‘cover content’ with reduced time (Bennett et al 2000; Drummond et al 2000; Chance 1993).
There are some claims that the second approach, which can be referred to as, ‘explicit embedding and integration’ has proved more effective in developing employability skills. Where courses have been re-designed along these lines and a wider range of learning and teaching strategies (for example, small group work, projects and presentations) have been employed to support students to develop skills, students have affirmed that they:
• are aware of the range of employability skills that departments are promoting through the curriculum (Drummond et al 2000);
• can identify the learning activities which have been used to help them to develop employability skills (Arnold et al 1999, Kemp and Seagrave 1995);
• can cite evidence of the employability skills they have developed (Fallows and Steven 2000).
However, much of this evidence is based on student self-reports before they have graduated. Students were being asked to speculate about their skill development and its potential applicability to employment before they had any substantial experience of employment.
One of the key challenges for HE staff is to alert students to the wider relevance of skill development beyond the immediate context where they first encounter those skills. The conventional educational wisdom has stressed that this issue is most effectively addressed if universities employ a range of assessment methods, for example, self-assessment, peer-assessment and formative assessment (i.e. feedback) to assist students to identify their skill development. This, however, is not as straightforward as it sounds. The original role of self-assessment and peer-assessment was to support self-reflection and self-development. Thus, developing the skill of self-assessment in a university context does not necessarily mean students will be able to distinguish themselves from their peers in a competitive university environment, let alone in a competitive labour market. Lecturers and departmental teams need structured opportunities to mull over how to evolve their academic practice to support graduates to connect their university-based learning more directly to the requirements of the world of work.
Another assumption underlying the drive to develop graduates’ employability skills is that skills gained in higher education are transferable to employment. Recent developments in learning theory have argued that simple ideas of transfer are questionable. Some writers are now arguing that the activities in which knowledge and skills are developed and deployed are not separable from the contexts where they are learnt (Engestrom and Gronin, 2001). In this sense, it is a form of ‘situated’ knowledge and skill that people have to learn to relate to other situations and the expertise of other people.
The idea that knowledge and skill is ‘situated’ suggests that account has to be taken of the social and cultural basis of learning when considering the question of transfer. This emphasis upon social and cultural context implies that, irrespective of the context of development (i.e. university courses or company training schemes), universities and companies face a common challenge when supporting learners to transfer skills such as teamworking and problem-solving. They have to assist learners to identify how to ‘re-situate’ forms of knowledge and types of skill they have already acquired in another context. At one level, this process of ‘re-situation’ involves supporting students and trainees to participate in different ‘communities of practice’ in order to learn how to relate their knowledge, understanding and skill to the demands of a new situation. At another level, it involves assisting students and trainees to develop new forms of knowledge and skill, by learning how to work collaboratively to transform the working practices of those communities (Guile and Young, 2001).
In the past the main purpose of work experience was to help students to develop specific forms of vocational or professional competence, deemed to be central to a specific degree subject, which would enable them to fulfil the licence to practise requirements associated with specific professions. Work experience in many undergraduate and postgraduate courses underwent many significant developments in the 1990s. A range of employer-sponsored programmes (for example, Shell’s Technology and Enterprise Programme, and government- sponsored initiatives such as the Teaching Company Scheme) were introduced to extend the range of opportunities for students to gain direct experience of work. Furthermore, all work experience programmes have increasingly used ‘learning contracts’ and ‘learning outcomes’ to record and review students’ skills in order to enhance evidence of their work-related learning, employability skills and key skills (Foster and Stephenson, 1998).
In general, work experience has been widely perceived to enhance students’ employability skills (Brennan et al 2001). It has been claimed that work experience:
• Enhances students’ personal maturity and academic performance, self-confidence (Auburn et al 1994), motivation (Kiely and Ruhnke, 1998) and their ability to manage the transition to employment more effectively than students who have not undertaken work experience (Purcell et al, 1999; Jones et al, 1995);
• Supports students to clarify career choices, gain substantial experience in supervisory or management positions and develop confidence about their future performance in workplaces (Kiely and Ruhkne, 1998);
• Supports effective learning transfer (Westhead 1997), in other words, provides opportunities for students to relate theoretical learning to the practical experience in the workplace (Auburn et al, 1998) or to enhance and extend the key skills that are developed through formal study in the workplace (Arnold et al 1999).
At the same time Guile and Griffiths (2001) argue that, by overlooking the extent to which knowledge and skill use are domain-specific or context-dependent, many work experience programmes fail to recognise that it is not work experience in itself that results in the development of employability skills but rather the meaningful engagement in the discourse and activities associated with specific ‘communities of practice’. This suggests that if work experience is to be productive, it needs to be located in a setting closely related to that of subsequent employment, a conclusion borne out by the Graduate Apprenticeship Programme (Fallows and Weller, 2000) as much as longstanding experience of students in Psychology (Auburn et al, 1994) and Medicine and Law (Bennett et al, 2000).
Conclusion
Substantial resources are now being invested in efforts to develop HE students’ employability skills while they are at university. Current policy rests on three assumptions:
• That employability skills can be effectively developed in HE;
• That there is a consensus about which employability skills should be developed;
• Those employability skills, once developed, can be easily transferred into employment.
This review of the literature suggests that all these assumptions are contentious in their own way. There is little agreement amongst researchers about what it is in the higher education experience that may impact on the employability of graduates, and the limited amount of empirical evidence is ambivalent.
With regard to the effects of employability skills development on graduate performance in employment, some studies have shown that work experience during undergraduate study is positively associated with finding a first job, but to date there has been very little to substantiate claims that explicit teaching of generic employability skills contributes positively to graduates’ job performance in their early years of employment and to subsequent career progress. A key aim of the empirical work described in the remainder of this report, therefore, is to identify what a sample of university departments claim to be doing with respect to employability skills development and to try to form a view of the extent to which this affects various measures of labour market performance of their graduates.
Chapter 2:
Enhancing Employability in English Universities
2.1 Undergraduate Courses
Semi-structured interviews were held with sixty academic staff and ten careers staff in thirty-four departments in five subjects in eight universities comprising 4 pre-1992 (old) and 4 post-1992 (new) universities. In one of the Old Universities the departments were located in three colleges which are identified separately (Table 2.1). The interviews sought respondents’ views on definitions of employability; learning, teaching and assessment of employment related skills and knowledge; employer involvement with programmes of study; student work experience; and other employability initiatives.
Table 2.1
Universities in the Sample
Old A: a large pre-1992 Civic university in the Midlands
Old B: a former College of Advanced Technology in the south of England which became a Technological University in 1964
Old C: a large pre-1992 Civic university in the north of England
Old D, Old E and Old F: two medium-sized colleges and one large college of London University
New A: a medium sized post-1992 university in the north of England, focused very much on serving a local community
New B: a very large post-1992 university located in the same city as Old C
New C: a medium sized post-1992 university in the Midlands
New D: a large post-1992 university in the south of England
The main aims of the interviews were:
• To investigate employability-enhancing strategies in the sample of departments;
• To provide background information from which to inform development of the questionnaires for the telephone survey of graduates and line managers;
• To provide a context for the evaluation of graduates’ and line managers’ responses to survey questions about the development and utilisation of employability skills.
Copies of the interview instruments are provided in Appendix A.
It was anticipated that the post-1992 universities would be more likely to stress employability than their pre-1992 counterparts. However, this was not unambiguously the case. All departments in the sample emphasised their awareness of, and commitment to an employability agenda. There were a wide range of perceptions of graduate employability and the methods by which departments sought to enhance it, with many differences between individual departments and subjects within both New and Old Universities.
2.1.1 Perceptions of Employability
Respondents were invited to give their own definitions of graduate employability. This produced distinct subject differences within two broad categories: subjects with a specific occupational orientation, computing and design in the sample, and subjects without a clear occupational focus, biology and history. The fifth subject, business studies, occupied an intermediate position, having a distinct vocational orientation but linked to a wide range of occupations in business and management.
In biological sciences all respondents emphasised the importance of employability and acknowledged their responsibility for producing graduates who were employable both within the biological sciences field and outside it. Respondents at the Technological University (Old B) commented that it was important to be ‘employable’ as opposed to being ‘employed’ to cope with the various changes and redundancies that they may face in their working careers when the average person changes jobs 9 times in a lifetime. Respondents from a Civic university (Old A) stressed that biological sciences students would be expected to have above average numeracy and literacy skills which would be useful in entering both biology-related and unrelated fields. Respondents at one New University (New A) said it is the range of skills that students develop during the course that makes them employable, not the subject discipline. At another (New C) interviewees stressed the importance of students being able to choose their jobs and work at an appropriate level, not just be forced to accept any job.
The respondents in the history departments, who were all from pre-1992 universities, showed a different approach to the employability skills agenda. At Old C the notion that degrees should be direct preparation for employment was rejected. These respondents claimed that companies should be responsible for providing their own training and that this was not the job of the university. However, they were confident that the academic quality of their graduates ensured good employment prospects. Most of the respondents from history departments emphasised that many of the skills required of a good historian are those required in a wide range of graduate employment, such as finding out new information, extracting it, analysing it and organising it into a coherent and convincing argument. The respondents at Old A University said that they were more interested in the subject specialism than in generic skills, but that they had been moved to making generic skills more explicit due to politicians’ doubts about the usefulness of history in many branches of employment. However, respondents at a technological university (Old B) were emphatic about their commitment to employability and have embedded employability skills in their courses and have recently tried to make these more explicit to students.
In business studies there was a clear Old–New University split in definitions of employability. All the New Universities offered definitions that suggested both academic rigour and employment related transferable skills are important. However, none of the Old University business departments referred to key skills at all in their definitions. One (Old A) referred to the reputation of the Business School as an influence on the success of their graduates in finding jobs. At another (Old C) respondents were confident that their graduates are attractive to employers because, for instance, they turn out ‘good accountants’. However, the definition from Old B emphasised that graduates should be equipped for change. Most respondents thought that business studies graduates would enter a field of employment related to their area of study.
All computing departments were aware of the ease with which at that time their graduates were finding employment. Their definitions of employability raised some issues that contrasted with the other four subjects. Respondents claimed that it would be difficult not to teach their students to be employable. It was emphasised in all departments that computer science graduates were highly sought after, with the majority entering employment immediately after leaving university. However, it was also widely reported that this led to resistance from students in engaging with broader employability skills and the theoretical underpinnings of their own subject. The respondents at New B said that it was difficult convincing students that they needed other communication and problem-solving skills: often students felt that because they were doing IT, the world owed them a living. Similarly, the respondents at ‘Old D’ College, and ‘Old C’ Universities emphasised that when employers recruited their students, they would take their technical skills for granted but would be looking for adaptability and transferable skills. It was difficult to convince students of this. Two universities (Old A and Old C) reported that some students lacked motivation and aptitude for IT because they had made their degree choice based on future employment prospects rather than as a reflection of their own interests.
Differences between IT and other subjects were pointed out by many of the respondents. One was that the number of women studying for IT degrees was very low and it was claimed by respondents at New D and Old A Universities that the number of women being recruited to computing courses was falling. Another claim about the special position of computing was that the rate of change in IT made it difficult to keep up with new developments both in terms of cost and training. In addition, the recruitment of new staff was particularly difficult because of the higher salaries available outside HE.
All four departments in design studies (all in post-1992 universities) stressed that most students began their degrees with the intention of working in this field after university and that the courses are largely focussed explicitly on this range of occupations. Many of the definitions offered showed a high level of commitment to the employability of their graduates and an understanding of the issues involved. At one (New A) interviewees stressed that students were provided with two sets of skills, those for their chosen profession and other more general skills that would be appropriate in any kind of employment they went into. In two departments (New A and New C) we were told that their graduates often took other kinds of employment to enable them to continue to practice their vocational interests independently. University departments of design saw their responsibility as the preparation of graduates who would have the choice. Respondents at New B reported that design graduates are more likely to be self-employed than those in other subjects. Those at New D stressed the need for graduates to have the skills and confidence to be able to manage their own careers, including how to build networks, make contacts and secure employment. The New C respondents said that employers require design graduates to be adaptable, particularly in the ‘creative industries’; they need to be able to respond quickly to changing customer demands.
.
2.1.2 The balance between employability skills and academic skills in the curriculum
A key aim of the university interviews was to gain an impression of how the employability agenda is integrated into courses. Respondents were asked to indicate the degree of importance in teaching and assessing their students on a number of items ranging from traditional academic objectives such as teaching specialist subject knowledge and theoretical understanding to the development of more explicit employability-enhancing skills such as oral and written communication skills, numeracy, literacy, C & IT (communications and information technology) skills, problem-solving skills, ‘understanding of the world of work’ and team working skills. While most respondents claimed that both academic and employability skills were important or very important, there were both subject and institutional differences in the academic–employability balance. A summary of the main responses is given in Tables 2.2A and 2.2B. There are full details in Appendix A.
Table 2.2A
Importance of employability skills (a) in undergraduate teaching
University Old A Old B Old C Old D Old E Old F New A New B New C New D
Biology 3.2 4.0 3.6 3.4 3.4 3.1 4.0 3.8 3.8
Business studies 3.9 3.6 3.4 3.7 3.4 3.8
Computing 2.4 3.5 3.3 3.1 3.4 4.0 3.7 3.4 3.4
Design 3.8 3.4 3.6 4.0
History 3.6 3.6 2.9 3.0 2.7 3.1
(a) Employability skills defined as: Communication, Numeracy, Literacy, C&IT, Problem-solving, Understanding world of work, Team-working. The emphasis given to teaching and learning of each of these skills was ranked by departmental interviewees on the following four-point scale: 4=Very important, 3=Fairly important, 2=Not very important, 1=Not at all important.
Table 2.2B
Relative importance of employability skills compared to subject knowledge/theoretical understanding (b)
University Old A Old B Old C Old D Old E Old F New A New B New C New D
Biology 1.0 4.0 4.0 1.0 1.0 1.0 2.0 4.0 2.0
Business studies 4.0 4.0 1.0 4.0 2.0 3.0
Computing 1.0 3.0 1.0 1.0 2.0 2.0 3.0 2.0 1.0
Design 1.0 2.0 2.0 2.0
History 2.0 1.0 1.0 1.0 1.0 1.0
(b) Defined as the difference between score given to employability skills LESS score given to subject knowledge/theoretical understanding where these two dimensions of teaching were ranked by interviewees on a four-point scale. These differences were then transformed into a four-point scale.
In biological sciences, the non-vocational nature of the subject was stressed in both New and Old University departments. Several respondents claimed that subject specialisation and theoretical understanding were less important than skills and that generic employability skills training was a major feature of their courses. For instance, the respondents at New A said that the subject specialism was the vehicle through which to deliver a range of employment related skills. Similarly, respondents at Old A emphasised a wide range of graduate destinations, reinforcing the view that biological sciences is frequently non-vocational and therefore graduates need generic skills enabling entry to a wide range of occupations. Old C University also downplayed the importance of subject specialisation and theoretical understanding compared with that of employability skills. These respondents emphasised that this was because a significant number of graduates did not enter biological sciences occupations and thus deeper subject knowledge was seen to be less important than employability skills.
In contrast the relative importance of employability skills compared to subject knowledge and theoretical understanding in all six history departments scored very low. In this subject area, despite a similar wide range of graduate occupations as in biology, the focus remains firmly on subject-related skills and knowledge. It is possible that this is linked to the relatively high A-level scores of many history students and their previous education, which ensures prior possession of many of the social skills sought by employers. By contrast biology, in common with many other science subjects, has to accept less well qualified entrants.
Employability was very high on the agenda of nearly all the business studies departments in the sample. business studies differs from the other subjects in the sample in that specialist subject knowledge and theoretical knowledge are intrinsically related to the development of generic employability skills. There were more claims of embedding employability issues in the regular teaching than in other subjects and less evidence of a distinction between academic objectives and the employability agenda.
The responses from computer studies may also be seen as reflecting its distinct position in the graduate labour market. There is more emphasis on the specialist and theoretical aspects of the subject in relation to generic employability skills than in the other subjects. This could be because computer science skills are in such high demand by employers that the dominant focus of student learning is on specialist subject knowledge. All the departments in the sample were able to cite major firms competing for their graduates.
This contrasts with design studies, which also has very specific labour market links but is an area where general employability skills are treated very seriously. This may be because many design graduates enter a very competitive economic environment with many small enterprises in which graduates will be required to have a range of management and business skills as well as technical proficiency in design. Design graduates also have to prepare for the possibility of self-employment where they will have to compete for commissions.
2.1.3 Teaching and assessment of employability skills
The picture was more complicated when respondents were asked about recent changes in teaching and assessment in the light of the employability debate of recent years. All the departments in the sample were conscious of these issues and all claimed to have responded to some extent.
Most biological sciences departments seem to have been quick off the mark in adapting courses. Examples included core modules developing research and professional skills focussed on employability; practice interviews with employers; key skills profiling for students throughout the degree; oral presentations; web page design; self-testing on web site. In terms of overall number of examples of innovative practice in employability, it was three Old University departments that offered the most examples, once more confounding the stereotype that employability skills are more highly emphasised in the post-1992 universities.
Some of the examples were implicit rather than explicit: for example, Old A University cited the breadth of biological sciences as enhancing adaptability whilst New D said that final year projects produced independent learners. The respondents at Old B University cited the placement and reflective log strategies as being beneficial in preparing students for employment in different contexts. For this purpose tutors at New B had introduced ‘contextualising’, or ‘real-world’ examples in their teaching. At New D University, numeracy was cited as particularly important for many types of employment, and they were seeking to enhance this through stand-alone mathematics and statistics courses at level 1. They also pointed out that the financial need to have part-time jobs was increasing their students’ self-management skills.
There was little evidence of employability skills being explicitly introduced in history courses. Old A and Old B Universities were able to provide examples of innovative course content, teaching and assessment methods with the explicit aim of improving employability. However, their scores were low compared with the other subjects. Examples of employability approaches included putting more emphasis on oral presentations by students, group research projects presented to peers and staff, writing book reviews or articles instead of normal assignments to stress practical application, an independent research project in final year and increased use of IT, the Internet in particular.
Business studies respondents reported a variety of efforts to prepare their graduates for employment in different contexts; it was felt that the subject specialism addressed this in its academic content in a way that was different from the other subjects. Most departments provided examples of new employment-focussed teaching, learning and assessment methods introduced in the last 5 years. Some examples are video feedback on presentation skills; team building exercises in the Lake District; key skills unit with focus on understanding of the world of work; more group assessment; increased weighting in assessment for problem solving, numeracy, literacy and lower weighting for theoretical knowledge. Most of the departments had embedded key skills in their mainstream courses with some also offering stand-alone courses provided by the department. Recognition for employability skills developed prior to the course was offered through APL/APEL in some post-1992 universities.
In terms of overall scores for innovative practice in employability skills in business studies, two of the New Universities and Old B University had the highest scores (Table 2.3). Old A and New D Universities are situated in the middle of the sample on this issue. Respondents from the lowest scoring department at Old C University were confident that the high calibre of their students combined with the academic rigour of the courses ensured their graduates’ employability.
Table 2.3
Major employment skills - related innovations in courses in the past 10 years
University Old A Old B Old C Old D Old E Old F New A New B New C New D
Biology 2 4 4 4 3 3 3 3 3
Business studies 3 4 1 4 4 3
Computing 1 3 3 3 4 3 4 3 2
Design 3 4 3 3
History 2 2 1 1 1 1
Scores:
4 = Wide-ranging efforts to change traditional course content and teaching
3 = Moderate efforts to change traditional course content and teaching
2 = Some minor efforts to change traditional course content and teaching
1 = No evidence of efforts to change traditional course content and teaching methods
While most of the business studies departments had embedded key skills in their mainstream courses, a number also offer stand-alone courses provided by the department. For instance, Old A University offers a Professional Skills course which includes some focus on employability. New B offers an ‘Advanced Writing Skills course’ to address problems with basic grammar, etc. New C provides all business studies students with ‘developing learning’ core modules that seek to enhance both employability and study skills through the subject specialism. New D University had a similar foundation course.
All the computer science departments in the sample emphasised their commitment to enhancing the employability of their graduates. They were all making efforts to introduce generic employability related modules to counteract excessive specialisation. These frequently took the form of stand-alone courses in learning and communication skills; group working embedded in courses; and video recorded presentations and peer assessment to improve students’ presentation skills. Respondents in two Old Universities said that they had talks by employers and recent graduates telling students what to expect if they went to work for particular employers. One of these departments is developing ways of connecting summer vacation work experience to the degree. About half the respondents, mainly in New Universities, reported that APL/APEL accreditation could be given, exempting students from particular modules if they could show that they had relevant experience. In practice, this was rarely used.
Nevertheless employability scores for computer science teaching, learning and assessment indicators were relatively low. This is because computer science specialist skills were so sought after by employers, that the main employability focus of their studies was on their specialism. Old B and New B universities placed the highest importance on employability skills compared with subject knowledge. However, at even lower scoring universities such as Old A, Old C and Old F, respondents reported that they were confident that their students were highly employable with most entering employment immediately after graduation. Both Old C and Old F reported that major computer employers such as Logica and Hewlett-Packard actively sought to recruit their graduates. At New D, another low-scoring department in terms of relative emphasis on employability skills, it was reported that the department ran a joint degree with IBM. These examples demonstrate that the weightings given by respondents to employability skills for computer science cannot necessarily be taken as an indicator of their graduates’ success in finding work or how highly major computer companies value their degrees.
Design studies departments, which were all in New Universities, had the closest course-related links to specific employment. All the departments emphasised the importance of both subject specialism and generic employability skills. Examples of innovations that were cited included:
• Fashion promotion placements;
• Distance packages so that students who are offered jobs before the end of their course can complete their degrees;
• Learning contracts for students that involve them reflecting, proposing, negotiating, taking responsibility for their own work;
• Earn as you learn schemes whereby students can get paid work assignments;
• Assessed fashion shows produced by students on CD Rom disks.
New A University has projects set by employers who give formative feedback on what has been produced. It was suggested that some of their innovations had been in response to the mass expansion in student numbers rather than employability directly. Also advances in IT had produced innovations, for example the introduction of PowerPoint. New D University provides business planning components in many courses. These include visiting bank managers, carrying out market analyses and writing business plans.
Most of the employability skills in design studies courses were embedded. However, there were some complementary stand-alone courses, including a CV course at New B University to prepare students for their exhibitions at the end of their degrees, and to form part of their portfolio to take into the work place. New C offered some stand-alone courses which could be offered across the programmes, visual culture theory for example. They also offered Career Planning modules. New D reported that they offered extra IT skills courses in specialisms such as multimedia and animation.
2.1.4 Work experience and employer involvement in course provision
Work experience varies widely by subject. There was very little work experience for students in history departments. In contrast the four New University design departments all reported considerable practical work experience as part of the courses.
In biological sciences, most of the Old Universities make little provision for work experience while in most of the New Universities it is widespread, but there was one exception on each side. One is Old B, an ex-College of Advanced Technology with a long tradition of providing work experience to undergraduate students, which has been retained since the upgrade to university status nearly 40 years ago. Conversely, New D resembles most of the Old Universities in providing little work experience and experiencing low take up of what is offered. It was suggested by the respondents that this was due to the shortage of local employers with whom close relationships could be built.
Table 2.4
Student Involvement in Work Experience
University Old A Old B Old C Old D Old E Old F New A New B New C New D
Biology 1 4 1 1 1.5 3 3 3 1
Business studies 3 4 1 4 4 4
Computing 1 4 3 2 1 2 2 4 4
Design 4 4 4 3
History 1 1 1 1 1 1
Scores:
4 = Average 50% or more of undergraduate students undertake work placements as part of their studies
3 = Average 10-49% of students undertake work placements as part of their studies
2 = Less than 10% of students undertake work placements as part of their studies; some involvement with industry-based project work of different kinds
1 = Less than 10% of students undertake work placements as part of their studies; no involvement with industry-based project work of any kind
The provision and take up of work experience in both Old and New Universities for business studies was higher than in any of the other subjects. For instance, at New C and New B universities, most students completed sandwich courses, with shorter placements provided for the remainder; 75% of students went on sandwich placements at both Old B and New D universities; roughly 40% of students did a summer internship with a company as part of their degree at Old A University. One exception was in the business studies department at Old C where no sandwich courses were offered by the department and there was a very low take up of other shorter placements.
In contrast to the other subjects in the sample, computer science departments reported that students were able to find course-related part-time and summer paid work. Old E and Old F had particularly low scores on work experience as part of their courses. However, the respondents at Old F indicated that 95% of students gained relevant work experience through paid employment during their time at university. The buoyancy of the local labour market and shortage of IT specialists permitted this. Respondents in Old A University expressed concerns that industry based projects are not academically challenging enough for students. They reported that employers often require that a routine piece of software be written and whilst this could involve a lot of work, it would often not be very difficult to carry out. Similarly, respondents at New B said that they rarely used client projects because they preferred students to learn by venturing into unknown territory and making mistakes. This provided a better learning experience for high-level computer specialists than delivering a fairly standard product to a client.
The design studies departments reported a very high level of work experience. At New C, 100% of their knitwear and fashion management students completed a sandwich course. New B said that 100% of their students undertook work experience and New A reported that 85% of their students undertook work experience.
In contrast all the history departments recorded low scores on work experience. All history departments scored the lowest mark possible, with only Old B University (5% of students do optional work experience) and Old C University (some links with royal armoury and other museums) citing any examples at all.
Employer involvement in course provision often overlaps with work experience, and is widespread and often integral in design studies whilst almost non-existent in history. In other subjects differences between institutions were reported but not on any clear Old/New University lines. It was suggested in both biology and history departments that the range of employment that graduates enter was so broad that it would be difficult to identify specific employers who might make a contribution that would be generally useful. Only one department, in a New University, reported heavy employer involvement in lecturing on and assessing business studies courses. Others reported that feedback from employers is sought before starting new courses. Design courses often have a specific type of employer involvement resulting from the widespread use of part-time staff who are practising professionals in the area.
In biological sciences, employer involvement in course planning/design, teaching and assessment did not occur at all in more than half the sample of departments, but was extensive in the remainder. Old B and New A Universities claimed a high degree of employer involvement in the design and delivery of its course, and Old C and New A also claimed extensive involvement. The remaining departments all claimed that absence of employer participation was at least partly because it would be difficult to identify particular categories of employer who would be likely to employ biology graduates extensively (Table 2.5).
In contrast the business studies departments’ scores were clustered together around the middle of the range. Old C University reported that feedback from employers was always sought before the introduction of new courses. Only one department, New C, claimed high involvement of employers in lecturing and assessing as well as involvement in course planning and design. It was pointed out by several universities offering work experience that the placement visits brought them very useful contacts with employers through visiting students. These visits often provided a rich source of informal feedback about the appropriateness of the student’s skills for the work environment, which reflected on the university’s course provision.
Table 2.5:
Employer Involvement in Course Provision
University Old A Old B Old C Old D Old E Old F New A New B New C New D
Biology 1 4 3 1.5 1 3 1 4 1
Business studies 2 2 2 3 3 3
Computing 4 2 2 1 1 2 2 2 4
Design 4 4 4 3
History 1 2 1 1 1 1
Scores:
4 = Some employer involvement in course planning/design, teaching and assessment
3 = Some employer involvement in course planning/design and teaching but not assessment
2 = Some employer involvement in course planning/design but not teaching or assessment
1 = No employer involvement in course planning/design or teaching or assessment
In computing employer involvement was generally low but in two departments – at Old A and New D Universities – it was reported to be very high.
In design studies New A had an established tradition of employer projects using companies such as Marks and Spencer and Reebok. New C ran a similar scheme. It was also emphasised by New A, New B and New C that a high number of their tutors are practising artists working independently outside education.
In history only Old B University had any employer involvement. It was stressed by Old A University and implied by others that work experience and employer involvement would not be useful because of the wide range of jobs their graduates enter.
2.1.5 Review of departmental employability skills provision for undergraduates
There were differences between subjects in the perceptions and definitions of employability given by respondents. In biological sciences, for instance, respondents reported that although they were committed to teaching subject knowledge and theoretical understanding, their awareness of the frequently non-vocational nature of the subject had led them to prepare students for a wide range of occupations borne out by their commitment to employability factors. Conversely, while the history respondents reported a similar non-specific occupational ethos, they had not, in the main, responded with increased employability skills provision. Instead they focussed on equipping their graduates with the skills they saw as essential for a good historian, in the belief that these skills themselves were transferable into a wide range of occupations.
On the whole, the respondents in computer studies, business studies and design saw their students as vocationally orientated. However, there are variations in how this was manifested. For instance, business studies teachers in New Universities reported that the majority of their students learned employability issues alongside subject knowledge and theoretical understanding. However, most of the Old University respondents were confident that the academic content of their courses would ensure their graduates’ employability.
All the respondents in computer science departments considered their subject very vocational with a high labour market demand for IT graduates. At the same time, most actively sought to enhance specialist knowledge with more generic skills. However, it was widely reported that the easy routes into employment for computer sciences graduates led to resistance by students to key skills and other employability enhancing factors that could improve their performance when they are established in the work place.
The design departments reported that their subject was vocational and most students intended to enter fields of employment related to their studies. Courses sought to equip students with employability-enhancing attributes to enable them to work well in any field, whether it was their chosen profession or other work to earn money to support their design interests.
Respondents in all subjects except history were able to provide examples of recently introduced approaches to teaching, learning and assessment that are intended to enhance employability, although the extent to which these were deployed varied between universities. All the departments visited stated that their principal intention was to embed key skills in the curriculum rather than addressing them by stand-alone courses. Where stand-alone courses within the departments did exist, these had been introduced to enhance particular non-academic skills that were seen to be lacking in students. There were few patterns identified here with a wide range of courses being offered across the board. For instance, stand-alone Communication Skills courses were as likely to be found in history departments as they were in computer science departments.
In relation to preparation for employment in different contexts, many of the history and biological sciences department respondents reported implicit aspects of their subjects that could enhance employability. For instance, the breadth of biological sciences was reported to enhance adaptability in graduates whilst the history interviewees said that the skills needed to become a good historian could be transferred to many types of employment. These responses reflected the wide range of occupations that the graduates of biological sciences and history enter.
With regard to employability skills developed prior to the courses, most of the departments were able to give recognition for work experience, but it was reported that students rarely had the appropriate experience. This was across the board with the exception of biological sciences at New B University, which had a large intake of mature, part-time students, whose studies complemented their established area of work. With regard to accreditation for part-time jobs, it was reported that jobs were rarely related to the students’ field of study. However, computer science students sometimes found work designing web pages and writing software whilst design students could find work in the clothing retail trade. These were rarely accredited, although examples were given (such as by the business studies department at Old B University) of students being encouraged to reflect and write about their experiences of part-time work and the management they received.
2.2 Postgraduate taught Masters courses
The interviews in university departments included a brief discussion of taught postgraduate courses up to Masters degree level. The aim was to form a view about whether the main driver of such courses was employability or other considerations.
Masters level courses fall into two categories: those which build on existing subject knowledge and those which help graduates to diversify into new, often more vocational, areas (conversion courses). Within biological sciences, the courses fall into the former group in that students are expected to already hold a degree in a relevant science related area if not in biological sciences itself. In terms of subject knowledge and theoretical understanding, the courses are designed either to extend the broader biological sciences knowledge base or to specialise in a particular aspect such as Human Genetics or Toxicology.
Respondents in biology departments reported their commitment to employability at postgraduate level as they had done at undergraduate level, although with variations in how this was interpreted. For instance, Old A University said that they sought to develop a range of skills extending from the establishment of a sound knowledge base to production of more articulate, positive and enthusiastic postgraduates. They reported that they had taken key skills for granted in their intake during the last six or seven years although they continued to develop them; for instance, there was greater emphasis on presenting data. Old B University said their aim was to take reasonable undergraduates and give them subject specific knowledge and top up skills. Old C University sought to continue the skills and academic base they provided at undergraduate level but to a more advanced level. Old F reported that their agenda was different with regard to postgraduate students, as often they had already begun their academic research careers whereas undergraduates had not yet established their field of work.
Masters degrees in biological sciences were driven by a combination of employer and student demand. For instance, when a new Masters degree in Biotechnology was established at New C University, it was preceded by seeking the views of the industrial members of the Courses Committee and canvassing the opinions of undergraduates in order to check out the potential market. Similarly, the respondents at Old A University said that their Masters courses were the result of demands from both British industry and the developing world. Home students often used these courses as a way of converting to specialist areas with good employment potential. In general, the respondents believed that graduates chose to do a Masters within biological sciences to improve their employability. For example, some students took a Masters to specialise in a particular field such as Medical Genetics, viewed as a new area affording huge employment opportunities (Old B University). However, the respondent at Old C University said that the material covered in the Masters probably used to be the equivalent of the third year of the degree but that the undergraduate curriculum had been condensed by the increased emphasis on transferable skills. Some respondents said that doing a Masters was a bridge to starting a PhD (Old E) and/or to improve on initial degree grade (Old A).
In business studies all the departments in the sample offered a range of courses that were open to most graduates almost irrespective of their first-degree subject. They all offered MBAs for example. Standard course pre-requisites across the board were several years of related business experience. However, Old A University said that exceptions to this were made for overseas students as some countries had the expectation that the MBA would be undertaken immediately after the first degree. Most of the departments also offered a range of conversion courses such as Marketing and Management and Information Systems. It was widely reported that these courses recruited first-degree graduates without work experience.
All the business studies departments claimed that students took Masters courses to improve their employment potential. Most of the respondents thought a combination of deepening subject knowledge and theoretical understanding and developing transferable skills was necessary to do this. For instance, respondents at Old C University commented that key skills could not be taken for granted in their postgraduate student intake and that they had to address these whilst developing subject knowledge. Similarly, the respondents at New C said that medium sized firms would not expect to have to train a postgraduate; they would assume their expertise. This meant that it was essential that the postgraduate was able to fulfil the job description on arrival with the company.
Business studies departments reported a high demand for their postgraduate courses from both home and overseas students. Old A University said that they were overwhelmed by international demand and felt that the department was driven financially by the need to recruit overseas students due to the higher fee income. By contrast, the respondents at New C reported that their courses were in response to local employer demand combined with demand from students. Blue chip companies were keen to employ their postgraduates. Similarly, New D University had started their E-Commerce Masters as the result of employer demand, particularly from IBM, building on links established with the computer science department through running joint first-degree courses.
The focus of computer sciences Masters courses varied but was entirely specialist employment-related. At New D University, it was reported that a very high number (90-95%) of students went directly into employment at the end of their conversion courses, even though some of them had been unemployed at the start of the course. At Old C University, students on traditional courses used them to refocus their careers and seek promotion. At Old B, it was reported that a total of 35% of students were from Europe and overseas and returned to their home countries leaving the remaining 60% to ‘plug gaps in the UK IT labour market’.
In computer sciences, most of the respondents said that employer demand was derived from the IT skills shortage in the UK workforce. Some courses were designed to focus on specific employer demands such as Java (Old B University) or were the result of establishing joint degree provision between the University and a local employer, (Siemens, New C). In relation to students’ past work and Degree experiences, a wide variety of reasons were cited for student demand which ranged from unemployed applicants to teachers ‘desperate to escape teaching’, to those already working in the IT field who require skills’ updating. Overall, the respondents in computer science said that they aimed to equip students with up-to-date skills.
Design department responses varied in terms of where the demand for their courses came from. For instance, New C University said that they responded to both employer and student demand however, 50% of their students were from overseas non-European countries. Meanwhile, New D University responded to student demand as most of their students were already employed. Departments reported that they tended to take students’ employability skills for granted at postgraduate level, as they had already gained work experience and continued to work during their courses.
History departments reported low demand for MA courses with the exception of local history courses. Masters courses were mainly academic and recreational in nature. The students following them were generally established in employment or retired, and the courses were not focused on employability. The history respondents reported that they did not expect their Masters students to have enhanced their careers by taking their courses beyond practising the ‘good historian’ skills that they sought to instil at undergraduate level. Only occasionally were the courses reported to enhance employability, such as in the case of archivists or history teachers.
2.2.1 Work experience on Masters courses
There were wide variations between departments in terms of work experience as part of the Masters courses in biology. At one end of the scale, New C University offered work experience for all full-time students; and also taught some modules within the local hospital pathology laboratory. Old C University offered placements with English Nature and similar bodies for those studying Biodiversity and Conservation. Students following other Masters courses were offered the opportunity to undertake industry-based projects often within the NHS. However, strikingly, when compared with its emphasis on undergraduate work experience, Old B University offered little work experience as part of its biology masters courses.
In business studies, work based assignments were a common feature of most Masters courses. At New D University all full-time Masters students undertook placements whilst all part-time students were assessed on projects, based on their work places. Most of the other departments provided industry-based projects particularly for full-time students, whilst part-time students were assumed to be gaining relevant work experience within their jobs. However, at Old B University it was reported that there was minimal work experience of this type due to the large numbers of overseas students recruited.
Similarly, the respondents in computer science departments reported that about 95% of their students would undertake industry-based projects, although there were no reported work placements provided. In design, it was reported that no placements were provided at New D University where all students were normally working in related employment. However, New C University, whilst not having placements, did provide group industry-based projects for students. History departments reported no work experience or industry-based projects.
2.2.2 Employer involvement in Masters courses
All the business studies respondents reported that employers had been involved to different extents in consultations about new courses or those under review. This tended to be done through dinners, industrial liaison panels or, at New D University, through several staff being members of the local industrial professional development group. However, employer involvement in teaching was usually limited to guest speaker slots. Similarly, on the whole, there was no employer involvement in assessment with the exception of occasional membership of final examination boards.
There was also a range of responses with respect to previous work experience of entrants to postgraduate courses in biology. New C University said that they had many part-time hospital employees who did it to gain professional accreditation whilst continuing their jobs. Old B University said that students had either work experience or a degree in a related area before they started the course, with part-time students often continuing to work in a related area during the course. However, at Old C University, the majority of biology postgraduate students had relevant degree rather than work experience.
Sources of funding of postgraduate students were sought in order to test the claim sometimes made that employers often paid fees in order to enhance relevant professional skills. However, this does not appear to be widespread. In biology all the departments in the sample reported that the majority of students were self-funded. Two of the universities said that a small number of studentships were available, (3 at Old A University, 5 at Old C), funded by the research councils. Old A and New C Universities also stated that some of the students were funded by ESF (European Social Fund) due to the proven skills shortage in subjects such as Biotechnology. Old B University said they did have several day release students and New C University also had some part-time students funded by the NHS, but it was generally thought that the number of students funded by their employers had fallen in recent years. In business studies all the departments in the sample reported similar patterns of funding in relation to home students. Most part-time MBA students are sponsored by their employers but most of the full-time MBA students are self-funded. Conversion course students in the business studies area, often following on from their First degrees, are largely funded by loans and family contributions.
The patterns of funding for computer sciences were similar to biology in that full-time students tended to be self-funded with the exception of a small number in receipt of research council scholarships. A small percentage of full-time students received grants from the ESF. There did not appear to be a large number of part-time students funded by their employers as had been the case with MBAs. The majority of design and history students were self-funding, with the exception of a small number of university scholarships and research council grants.
2.3 Overview of employability skills development in sample departments
The picture that emerges from the university visits is one of widespread interest by academic staff in employability as an issue that must be addressed in the provision of undergraduate courses, but there are wide differences between universities and between subjects about how it is most appropriate to treat the issue. The spectrum ranges from some history departments where it is widely believed that the knowledge and skills acquired in becoming a competent historian are useful in a wide range of occupations, to design studies where often something approaching an apprenticeship model of learning is applied. Generic employment concerns were much less often expressed for postgraduate programmes, most of which had specific subject-related aims. It is possible to discern some differences of approach between pre-1992 and post-1992 universities, but there is no sharp distinction within subjects that are offered in both categories of institution.
The significant differences between subjects seem to depend in large part on a combination of (a) the range of occupations that graduates enter and the state of the labour market for graduates with specialist knowledge in that area and (b) the levels of prior educational achievement of students on the courses. The main characteristics of the five subjects in these respects may be described as follows:
History:
• High entry qualifications of course recruits;
• Graduates enter a wide range of occupations;
• Main concern of teachers is to train competent historians;
• Little attention to generic employability issues;
• Postgraduate courses largely personal development in nature.
Biological sciences:
• Relatively modest entry qualifications of course recruits;
• Graduates enter a wide range of occupations;
• Relatively little attention on undergraduate courses with training biology related specialists;
• Considerable concern with generic employability in course provision;
• Postgraduate courses tend to be vocationally specific.
Business studies:
• Wide range of entry qualifications of course recruits;
• Graduates enter range of occupations but mostly within ‘business/management’;
• Several sub-disciplines have close links with particular professions;
• Close relationship between employability issues and content of many courses;
• High demand for Masters courses often from graduates converting from other subjects.
Design studies:
• Modest academic qualifications at entry: other criteria for student selection;
• Graduates enter well defined range of occupations: many in small businesses;
• Specialist course content mainly concerned with professional and craft skills;
• Considerable emphasis on business related generic employability skills;
• Limited amount of postgraduate courses are vocationally specific.
Computing:
• Fairly high entry qualifications of course recruits;
• Extremely high demand for graduates in specialist occupations;
• Students concentrate almost exclusively on acquiring specialist skills;
• High demand for Masters courses often from graduates converting from other subjects.
Formal course related work experience is widespread in business studies and in many biology departments, though numbers undertaking this continue to fall due to financial constraints. Work experience is much less visible in other subjects for a variety of reasons. Historians (all in Old Universities) tend to consider it not helpful. In computing it is generally considered more important for students to learn computer skills well. The design studies departments (all in New Universities) reported a very high level of work experience and also close integral links through widespread use of part time staff with a foothold in the ‘real world’. Most students in all subjects now gain some practical work experience in vacations and many also work during term time through financial necessity. Whilst this undoubtedly enables them to develop skills such as self and time management, it is no substitute for a carefully monitored and supervised work experience placement.
The extent to which any particular graduate has been exposed to employability skills training, and the precise form it takes, will vary considerably depending on the subject of his or her first degree and the institution where it was obtained.
Chapter 3:
Employability Skills Development and Graduate Employment Outcomes
3.1 Measures of graduate employability
Recent efforts to develop ‘performance indicators’ for HE institutions in the UK have made use of available data from the annual First Destinations Survey of full-time undergraduate leavers from UK universities, which is carried out by the Careers Service at each university and captures information on students’ employment outcomes roughly six months after graduation. The performance indicators developed to date have typically focused on:
1. The probability of graduates finding employment after graduation (as against being unemployed or economically inactive)
2. The probability of graduates finding employment in a job deemed, by specified criteria, to be of ‘graduate quality’
For example, in a study of 1993 leavers from pre-1992 Universities, Smith, McKnight and Naylor (2000) find that the probability of graduates being unemployed or inactive six months after graduation is inversely related to the class of degree and is strongly influenced by the subject studied, measures of prior educational attainment (such as A-level point scores) age at graduation and social class background. Most of these factors are also found to strongly affect the probability of student leavers in employment being in a ‘graduate occupation’ although age at graduation has only a weakly significant effect for female graduates and no significant effect for males.
The definition of a ‘graduate occupation’ by Smith et al includes both ‘traditional graduate’ and ‘graduate track’ occupations as defined by McKnight (1999) in the following categorisation:
• ‘Traditional graduate’ occupations, e.g. doctors, lawyers, qualified engineers, teachers, high-level managerial and technical occupations;
• ‘Graduate track’ occupations, e.g. low level management jobs, technician jobs, skilled caring jobs, high level sales jobs; these are jobs which require high levels of education, are increasingly filled by graduates and which often constitute entry routes to higher level positions;
• ‘Non-graduate’ occupations (those which do not require high level qualifications).
Six months after graduation is a very early stage in graduates’ careers and the Moving On survey of 1995 graduates (Elias, McKnight et al, 1999) found that the likelihood of being under-employed in a non-graduate occupation declines over the first few years after graduation as some individual graduates manage to secure graduate-level employment after first accepting a period of lower-level employment. However, an initial period of under-employment was found to have lingering negative effects on those graduates’ salary and career development, suggesting that data on employment status six months after graduation are useful indicators of future labour market prospects.
Later work in a similar vein by HEFCE (2001) has developed benchmarks for institutional performance with regard to graduate employability using a multi-level model which relates employment indicators for individual graduates in 1999-2000 to vectors of:
1. Student-level factors
• Subject of study;
• Entry qualifications;
• Age on entry;
• Gender;
• Ethnic group;
• Whether or not on sandwich course;
• Social class;
• Whether or not from low participation neighbourhood;
• Degree classification.
2. Institutional-level factors
• Average A-level / Scottish Highers score;
• Unemployment rate among 20-29 year olds in institution’s locality;
• Percentage of jobs classified as ‘graduate jobs’ in institution’s locality.
The HEFCE work combines data from the First Destinations Survey of student leavers with data from the Combined Student Module Record held by HESA (Higher Education Statistics Agency), supplementary files supplied by UCAS (Universities and Colleges Admissions Service) and the Labour Force Survey.
3.2 Employability skills development and graduate employment outcomes
For the present study the availability of the dataset prepared by HEFCE enabled us to explore the impact on graduate employment outcomes of the departmental-level measures of involvement in employability-skills development, which we developed following our university research visits described in the previous Chapter. Our approach was to estimate a similar specification to that used for the HEFCE benchmarks for all available June 2000 graduates from the 34 departments we had visited and then to expand the set of independent variables to include departmental-level measures of:
• Teaching, learning and assessment of employability skills;
• Student participation in work experience;
• Employer involvement in course design and delivery,
based on the employability scores shown in Tables 2.1 to 2.5 above (see Appendix A for further details).
Given that our departmental data were gathered during research visits in early 2001, it was necessary to review the measures in order to ensure that so far as possible they reflected teaching and learning practices during the period 1996/7 to 2000 when most 2000 graduates were attending university. This led to appropriate downward adjustments being made for 10 out of the 34 departments who had only recently introduced certain innovations in respect of employability skills teaching, and it was these adjusted measures of involvement in employability skills development which were included in the statistical analysis (see Tables 3A.1 and 3A.2 in the Annex to this chapter, for variable definitions and descriptive statistics).
In total, data were supplied for 5,763 graduates in year 2000 from the 34 departments in the five selected subject areas, of which 4,676 completed First Destinations returns. In our analyses we focus on the 3,589 graduates among this group who were either employed or unemployed at the time of the 2000 First Destinations Survey (Table 3.1).
Table 3.1 Employment status of 1999-2000 graduates from selected university departments who completed First Destinations returns
Number Percent
Employed 3284 70.2
Unemployed 305 6.5
Further study or training 712 15.2
Not available for employment 371 7.9
Overseas student returning overseas 4 0.1
TOTAL 4676 100.0
Table 3.3 shows the results of a logistic regression analysis of the factors determining the probability that individual graduates from the 34 departments are employed as against being unemployed. The odds ratios reported for each independent variable effectively compare the probability of an ‘event’ occurring, all else being equal, with the probability of it not occurring. Thus for example, in the base specification (Equation 1), the probability of graduates with a First Class or Upper Second degree being employed is roughly a third higher than for graduates with a lower class of degree (after controlling for all the other potential influences represented in the equation). The probability of being employed is also found to be significantly and positively associated with students having participated in a sandwich placement during their studies. However, statistical association tells little about causation. It is possible that this relationship partly reflects unobserved characteristics of students who choose to undertake sandwich courses, for example, a high level of motivation to gain employment-related skills and to develop contacts relevant to future employment.
The significant negative influences, all else being equal, are being male, attending a university with a relatively high unemployment rate among 20-29 year olds in its locality and having taken a degree in design studies. This result for design graduates reflects the markedly different early employment patterns of graduates in that subject who tend to take longer to develop a career; for example, needing to establish a portfolio and make useful contacts in order to win contracts for freelance and commissioned work (Blackwell and Harvey, 1999).
These findings are all broadly consistent with those of the HEFCE study based on 1999-2000 graduates in a full range of degree subjects (HEFCE, 2001) and point to the suitability of the base specification for testing the effects of entering our departmental-level measures of employability skills development as independent variables. The initial results in Table 3.3, Equation 2 suggest that none of the three measures are significantly associated with the probability of graduates finding employment. Given the unsurprisingly high correlation between the individual-level sandwich variable and the departmental-level work experience variable (Table 3.2) it was considered appropriate to omit the latter variable in Equation 3, but this has no impact on the significance levels attached to the two remaining employability skills variables. Similar results are obtained in Equation 4, which omits the Old University variable (which is negatively correlated with all three measures of employability skills development) along with several other variables that failed to signify in the first three equations.
Table 3.2: Correlations between sandwich, Old University and employability skills variables (n=3589)
Sandwich Olduniv tchlngass workexper empinvlt
sandwich 1
olduniv -0.29 1
tchlngass 0.20 -0.21 1
workexper 0.41 -0.53 0.31 1
empinvlt 0.15 -0.44 0.22 0.65 1
for definitions of variables see Annex Table 3A.1
The second set of logistic regressions, shown in Table 3.4, model the probability that employed graduates from the 34 departments are in graduate-level occupations, that is, in either ‘traditional graduate’ or ‘graduate track’ occupations as defined above. The base specification is similar to that in Table 3.3 except that the measure of unemployment of 20-29 year olds in each university’s locality is replaced with a measure showing the percentage of jobs that are of graduate level in each locality. Table 3.4, Equation 1 shows that the coefficients on the degree class, sandwich variables and ‘percent graduate-level jobs’ variables are all positive and significant, as are the coefficients on three of the four subject dummy variables (as compared to the reference category of biological sciences). The exception is history, which is negatively signed and weakly significant. Interestingly, in contrast to the earlier analysis of factors determining the probability of being employed rather than unemployed, the coefficient on the male variable is now positive and weakly significant, supporting an argument that, all else being equal, male graduates are more likely than females to remain unemployed rather than accept a job below graduate level.
When the departmental-level employability skills measures are added to Equation 2, the coefficients on the work experience and employer involvement variables are both found to be positive and significant while that on the teaching, learning and assessment variable is negative but insignificant. These findings remain stable for both the employer involvement and teaching/learning/assessment variables in Equations 3 and 4 which omit the departmental work experience variable, the Old University variable and other variables for the reasons described above. In both the latter specifications, a one unit change in the level of employer involvement in course design and delivery is associated – all else being equal -- with an estimated 29% increase in the probability of graduates being employed in a graduate-level job.
Table 3.3 Logistic regressions using graduates’ employment status as dependent variable
Dependent variable: emp2=1 if employed (base: employed plus unemployed)
1. Base specification 2. Add in employability skills measures 3. Drop departmental-level measure
of participation in work experience 4. Drop Old University, low participation
neighbourhood and social class variables
Independent variables Odds ratio Coef. Robust Std. Err. Odds ratio Coef. Robust Std. Err. Odds ratio Coef. Robust Std. Err. Odds ratio Coef. Robust Std. Err.
---------+ ------------ ----------- -------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
male 0.54 -0.62 0.14 *** 0.54 -0.61 0.14 *** 0.54 -0.62 0.14 *** 0.53 -0.63 0.14 ***
alevsc1 1.02 0.02 0.01 * 1.03 0.03 0.01 ** 1.03 0.03 0.01 * 1.02 0.02 0.01 *
dalevscx 0.53 -0.63 0.39 0.51 -0.67 0.39 * 0.52 -0.65 0.39 * 0.51 -0.68 0.37
dclass12 1.32 0.28 0.13 ** 1.32 0.28 0.13 ** 1.31 0.27 0.13 ** 1.32 0.28 0.13 **
ddesign 0.55 -0.6 0.19 *** 0.46 -0.78 0.24 *** 0.52 -0.65 0.22 *** 0.55 -0.6 0.21 ***
sandwich 2.31 0.84 0.19 *** 2.18 0.78 0.19 *** 2.27 0.82 0.19 *** 2.28 0.82 0.19 ***
olduniv 0.84 -0.17 0.18 0.9 -0.11 0.19 0.85 -0.17 0.18
unemp 0.89 -0.12 0.05 ** 0.88 -0.13 0.06 ** 0.88 -0.13 0.06 ** 0.88 -0.13 0.06 **
constant 3.69 0.61 *** 3.37 0.69 *** 3.43 0.71 *** 3.42 0.70 ***
Number of observations = 3589 Number of obs = 3589 Number of obs = 3589 Number of obs = 3589
Wald chi2 (19) = 97.22 Wald chi2 (22) = 99.28 Wald chi2 (21) = 97.88 Wald chi2 (16) = 94.43
Log likelihood = -985.0 Log likelihood = -983.8 Log likelihood = -984.7 Log likelihood = -987.4
***Statistically significant at 1% level or better **5% level *10% level
Table 3.4 Logistic regressions using graduates’ occupational category as dependent variable
Dependent variable: demp4=1 if employed in traditional graduate or graduate-track occupation
1. Base specification 2. Add in employability skills measures 3. Drop departmental-level measure of participation in work experience 4. Drop Old University, low participation neighbourhood and social class variables
Independent variables Odds ratio Coef. Robust Std. Err. Odds ratio Coef. Robust Std. Err. Odds ratio Coef. Robust Std. Err. Odds ratio Coef. Robust Std. Err.
--------- ------------ ----------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
male 1.19 0.17 0.09 * 1.21 0.19 0.09 ** 1.20 0.18 0.09 ** 1.20 0.18 0.09 **
age 1.01 0.01 0.01 1.01 0.01 0.01 1.01 0.01 0.01 1.01 0.01 0.01
dethnic 1.04 0.04 0.16 0.99 -0.01 0.16 1.04 0.04 0.16 1.07 0.07 0.15
dethnicx 0.92 -0.08 0.23 0.90 -0.11 0.23 0.88 -0.12 0.23 0.90 -0.10 0.23
alevsc1 1.01 0.01 0.01 1.01 0.01 0.01 1.01 0.01 0.01 1.02 0.02 0.01 **
dnonalev 0.67 -0.41 0.13 *** 0.66 -0.41 0.13 *** 0.66 -0.41 0.13 *** 0.65 -0.43 0.12 ***
dalevscx 0.85 -0.16 0.37 0.77 -0.26 0.36 0.79 -0.24 0.36 0.78 -0.25 0.35
dclass12 1.51 0.41 0.09 *** 1.56 0.44 0.09 *** 1.55 0.44 0.09 *** 1.54 0.43 0.09 ***
dcomput 4.29 1.46 0.16 *** 3.82 1.34 0.17 *** 4.35 1.47 0.16 *** 4.33 1.47 0.16 ***
dbus 2.01 0.70 0.13 *** 1.49 0.40 0.17 ** 1.91 0.65 0.13 *** 1.91 0.65 0.13 ***
dhist 0.76 -0.27 0.16 * 0.71 -0.34 0.19 * 0.76 -0.27 0.19 0.81 -0.21 0.18
ddesign 1.48 0.39 0.14 *** 0.90 -0.11 0.17 1.04 0.04 0.16 0.98 -0.02 0.16
dlpn 0.88 -0.13 0.14 0.85 -0.16 0.14 0.86 -0.15 0.14
dlpnx 1.26 0.23 0.21 1.18 0.17 0.21 1.19 0.18 0.21
dsocclas 1.03 0.03 0.12 1.01 0.01 0.12 1.01 0.01 0.12
dsocclax 1.02 0.02 0.14 1.00 0.00 0.14 1.00 0.00 0.14
sandwich 2.15 0.77 0.14 *** 1.92 0.65 0.14 *** 1.99 0.69 0.14 *** 1.94 0.66 0.14 ***
olduniv 1.16 0.15 0.13 1.29 0.26 0.14 * 1.17 0.15 0.13
gradperc 1.02 0.02 0.01 ** 1.03 0.03 0.01 *** 1.03 0.03 0.01 *** 1.04 0.04 0.01 ***
tchlngass 0.85 -0.16 0.10 0.85 -0.17 0.10 0.85 -0.16 0.10
workexper 1.19 0.17 0.07 **
empinvlt 1.16 0.15 0.07 ** 1.29 0.25 0.06 *** 1.29 0.25 0.06 ***
constant -0.63 0.43 -1.15 0.56 ** -1.12 0.55 ** -1.24 0.53
Number of obs = 3284 Number of obs = 3284 Number of obs = 3284 Number of obs = 3284
Wald chi2(19) = 257.05 Wald chi2(22) = 263.11 Wald chi2(21) = 263.47 Wald chi2(16) = 259.84
Log likelihood = -1679.2 Log likelihood = -1666.2 Log Likelihood = -1669.1 Log Likelihood = -1670.9
These findings point to the following main conclusions:
1. In terms of the factors influencing initial labour market outcomes for graduates, structured work experience during courses appears to be a highly positive influence and predominates over other approaches seeking to develop employability skills in HE. However, the apparent strength of the relationship between sandwich participation and subsequent employment may in part reflect unobserved characteristics of students who choose to follow courses with a sandwich component.
2. After controlling for gender, age, intellectual ability (proxied by A-level scores), degree class, degree subject and a range of other potential influences -- employer involvement in course design and delivery is also positively associated with an occupation-based measure of the quality of initial employment found by graduates. However, there is no evidence of a significant independent effect of the efforts devoted by university departments to the teaching, learning and assessment of employability skills.
We now go on to report the results of a new survey of matched pairs of graduates and line managers which enabled us to investigate the impact of employability skills development using a wider range of indicators of graduate labour market performance than have hitherto been available.
Chapter 3 Annex
Table 3A.1 Definitions of variables
emp2 = 1 if employed (base: employed plus unemployed)
demp4 = 1 if employed in graduate or graduate-track occupation
male
age
dethnic = 1 if non-white
dethnicx = 1 if ethnic background not known
alevsc = A-level score
dnonalev = 1 if didn't take A-levels
dalevscx = 1 if took A-levels but A-level score unknown
dclass12 = 1 if First class honours or 2.1 degree
dcomput = computer science Subject dummies: reference category = biological sciences
dbus = business studies
dhist = history
ddesign = design studies
dlpn = 1 if from low participation neighbourhood
dlpnx = 1 if neighbourhood participation rate unknown
dsocclas = 1 if parents in social classes IIIm, IV or V
dsocclax = 1 if parental social class unknown
sandwich = 1 if went on sandwich placement
olduniv = 1 if attended Old University
unemp = unemployment rate among 20-29 year olds in university's locality
gradperc = percentage of jobs in institution's locality classified as graduate jobs
tchlngass = measure of teaching, learning and assessment of employability skills in department [1-4 point scale]
workexper = measure of student participation in work experience at department level [1-4 point scale]
empinvlt = measure of employer involvement in course design, teaching and assessment in department [1-4 point scale]
Table 3A.2 Descriptive Statistics
Dependent variable: emp2=1 if employed (base: employed plus unemployed)
Variable Obs Mean Std. Dev. Min Max
---------+ ------------ ---------- ----------- --------- -----------
emp2 3589 0.92 0.28 0 1
male 3589 0.53 0.50 0 1
age 3589 23.61 3.64 20.5 67.1
dethnic 3589 0.12 0.32 0 1
dethnicx 3589 0.03 0.17 0 1
alevsc1 3589 18.39 5.69 2.5 29.5
dnonalev 3589 0.28 0.45 0 1
dalevscx 3589 0.02 0.14 0 1
dclass12 3589 0.56 0.50 0 1
dcomput 3589 0.24 0.42 0 1
dbus 3589 0.20 0.40 0 1
dhist 3589 0.08 0.27 0 1
ddesign 3589 0.17 0.38 0 1
dlpn 3589 0.10 0.30 0 1
dlpnx 3589 0.06 0.23 0 1
dsocclas 3589 0.17 0.38 0 1
dsocclax 3589 0.23 0.42 0 1
sandwich 3589 0.25 0.43 0 1
olduniv 3589 0.41 0.49 0 1
unemp 3589 7.86 1.24 5.68 9.51
tchlngass 3589 2.82 0.57 1.48 3.75
workexper 3589 2.69 1.29 1.0 4.0
empinvlt 3589 2.54 1.09 1.0 4.0
Dependent variable: demp4=1 if employed in traditional graduate or graduate-track occupation
Variable Obs Mean Std. Dev. Min Max
---------+ ------------ ---------- ----------- --------- -----------
demp4 3284 0.75 0.43 0 1
male 3284 0.52 0.50 0 1
age 3284 23.56 3.55 20.5 67.1
dethnic 3284 0.12 0.32 0 1
dethnicx 3284 0.03 0.18 0 1
alevsc1 3284 18.46 5.71 2.5 29.5
dnonalev 3284 0.27 0.44 0 1
dalevscx 3284 0.02 0.13 0 1
dclass12 3284 0.57 0.50 0 1
dcomput 3284 0.24 0.42 0 1
dbus 3284 0.21 0.41 0 1
dhist 3284 0.08 0.27 0 1
ddesign 3284 0.16 0.37 0 1
dlpn 3284 0.10 0.30 0 1
dlpnx 3284 0.06 0.23 0 1
dsocclas 3284 0.17 0.38 0 1
dsocclax 3284 0.22 0.42 0 1
sandwich 3284 0.26 0.44 0 1
olduniv 3284 0.42 0.49 0 1
gradperc 3284 27.79 5.91 22.45 39.20
tchlngass 3284 2.81 0.57 1.48 3.75
workexper 3284 2.69 1.30 1 4
empinvlt 3284 2.52 1.09 1 4
Table 3.5 Logistic regressions using graduates’ employment status as dependent variable
Dependent variable: emp2=1 if employed (base: employed plus unemployed)
1. Base specification 2. Add in employability skills measures 3. Drop departmental-level measure
of participation in work experience 4. Drop Old University, low participation
neighbourhood and social class variables
Independent variables Odds ratio Coef. Robust Std. Err. Odds ratio Coef. Robust Std. Err. Odds ratio Coef. Robust Std. Err. Odds ratio Coef. Robust Std. Err.
---------+ ------------ ----------- -------------- ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------ ------------
male 0.54 -0.62 0.14 *** 0.54 -0.61 0.14 *** 0.54 -0.62 0.14 *** 0.53 -0.63 0.14 ***
age 0.98 -0.02 0.02 0.98 -0.02 0.01 0.98 -0.02 0.02 0.98 -0.02 0.01
dethnic 0.82 -0.2 0.19 0.79 -0.23 0.19 0.82 -0.2 0.19 0.77 -0.27 0.18
dethnicx 1.22 0.2 0.39 1.2 0.18 0.39 1.21 0.19 0.39 1.2 0.18 0.39
alevsc1 1.02 0.02 0.01 * 1.03 0.03 0.01 ** 1.03 0.03 0.01 * 1.02 0.02 0.01 *
dnonalev 0.83 -0.18 0.17 0.82 -0.2 0.17 0.82 -0.2 0.17 0.81 -0.21 0.15
dalevscx 0.53 -0.63 0.39 0.51 -0.67 0.39 * 0.52 -0.65 0.39 * 0.51 -0.68 0.37
dclass12 1.32 0.28 0.13 ** 1.32 0.28 0.13 ** 1.31 0.27 0.13 ** 1.32 0.28 0.13 **
dcomput 1.1 0.1 0.19 1.04 0.04 0.21 1.12 0.11 0.19 1.14 0.13 0.19
dbus 1.36 0.31 0.22 1.13 0.12 0.24 1.34 0.29 0.22 1.4 0.34 0.22
dhist 1.11 0.11 0.29 1.19 0.18 0.35 1.25 0.23 0.35 1.25 0.22 0.34
ddesign 0.55 -0.6 0.19 *** 0.46 -0.78 0.24 *** 0.52 -0.65 0.22 *** 0.55 -0.6 0.21 ***
dlpn 0.78 -0.25 0.18 0.77 -0.26 0.18 0.77 -0.26 0.18
dlpnx 1.21 0.19 0.28 1.18 0.16 0.28 1.2 0.19 0.28
dsocclas 0.81 -0.21 0.16 0.81 -0.21 0.16 0.81 -0.21 0.16
dsocclax 0.85 -0.17 0.18 0.85 -0.16 0.18 0.85 -0.16 0.18
sandwich 2.31 0.84 0.19 *** 2.18 0.78 0.19 *** 2.27 0.82 0.19 *** 2.28 0.82 0.19 ***
olduniv 0.84 -0.17 0.18 0.9 -0.11 0.19 0.85 -0.17 0.18
unemp 0.89 -0.12 0.05 ** 0.88 -0.13 0.06 ** 0.88 -0.13 0.06 ** 0.88 -0.13 0.06 **
tchlngass 1.05 0.05 0.14 1.07 0.07 0.14 1.08 0.07 0.14
workexper 1.13 0.12 0.08
empinvlt 0.99 -0.01 0.08 1.05 0.05 0.07 1.05 0.05 0.07
constant 3.69 0.61 *** 3.37 0.69 *** 3.43 0.71 *** 3.42 0.70 ***
Number of obs = 3589 Number of obs = 3589 Number of obs = 3589 Number of obs = 3589
Wald chi2(19) = 97.22 Wald chi2(22) = 99.28 Wald chi2(21) = 97.88 Wald chi2(16) = 94.43
Log likelihood = -985.0 Log likelihood = -983.8 Log likelihood = -984.7 Log likelihood = -987.4
***Statistically significant at 1% level or better **5% level *10% level
Chapter 4:
Survey Methodology
4.1 Sampling strategy and outcome
To develop measures of graduate labour market performance we took into account, not just employment and occupational status, but also their performance in the workplace. We carried out an unusual telephone survey of recently-qualified graduates in the five subjects of interest – biological sciences, business studies, computer science/studies, design studies and history – and with their line managers. ‘Paired interviews’ were expected to pose problems in terms of securing a satisfactory response rate from prospective participants but judged to be worthwhile as a means of breaking new ground in empirical investigation of graduate employability skills issues.
In total interviews were carried out with 247 graduates and 210 line managers in 120 establishments between May and August 2001. After carrying out 18 paired interviews during a pilot survey, this left a main sample for analysis of 192 paired graduates/ line managers and another 37 graduates whose line managers could not be contacted for interview in the time available. The average length of interviews was 20 minutes for graduates and 15 minutes for line managers. Initial contacts with employers thought likely to have recently recruited target graduates were made on the basis of information supplied by Careers Services at the ten universities which we had visited. In order to boost the number of interviews, it was necessary to extend the sampling frame to graduates from universities besides those visited in the first phase of the study. However, we continued to confine the sample to graduates in the five selected subject areas in order to make best use of the subject-specific information on employability skills teaching gathered during university visits.
Further details of sampling methods are provided in Appendix B. In total just over 210 establishments were contacted. Allowing for the relatively high proportion of establishments which did not employ any graduates in one of the chosen subjects, we estimate that the effective response rate at establishment level was roughly 27% of all establishments who were in principle eligible to participate (see Appendix Table B1 for details of this calculation). This response rate is not high for a telephone survey, but most telephone surveys do not attempt the difficult task of securing the separate agreement of linked pairs of respondents.
4.2 Description of achieved sample
Given the relatively small size of our achieved sample of graduates and line managers, our focus on graduates in only five subject areas and the unorthodox way in which the sample had been compiled, we were concerned to establish how and to what extent – on a range of criteria – the graduates in our sample differed from the wider population of individuals graduating from UK universities in the same time period.
As described, interviews were carried out with 229 individual graduates and 192 line managers. Throughout this report we focus primarily on the 192 graduates who were ‘paired’ with line managers since the main strength of our research method was the ability it gave us to compare and combine responses from both graduates and line managers in our data analysis. Accordingly, unless otherwise stated, all survey data reported here refer to the 192 paired graduates and their line managers.
Table 4.1 shows the composition of the graduate sample in terms of degree subjects, years of graduation and age. Some 93% of the graduates had studied one or other of our five target subject areas, with the largest numbers in business studies (79) and the smallest in history (20) and design (13). A small proportion (7%) of the graduates were found on close inspection to have studied subjects outside our target areas. The small numbers in history and design reflect the fact that we only visited (and sought First Destinations contacts from) four departments in each of those subjects as compared to eight departments in biology, business studies and computing. As a result particular caution must be attached to survey findings relating to history and design.
Just under half (47%) of the graduates had attended one of the departments where interviews were carried out in the earlier phase of the study (Chapter 3). The remainder had attended a range of universities in different parts of the UK. In total about 40% of the sample had graduated from pre-1992 Universities and 60% from New Universities and colleges.
About 87% of these graduates entered the labour market between 1998-2001, with a fairly even distribution across those three years. Just over three quarters of them (78%) were born between 1974 and 78. This age distribution – and the spread of years of graduation – largely corresponded with sampling objectives.
Table 4.1: Composition of sample of graduates
A. SUBJECT AREA
Number of respondents Percent of total
Biological sciences 32 17
Business studies 79 41
Computing 34 18
Design studies 13 7
History 20 10
Other subjects 14 7
TOTAL 192 100
B. YEARS OF GRADUATION
Number of respondents Percent of total
1996 or earlier 11 6
1997 15 8
1998 48 25
1999 51 27
2000 or later 67 35
TOTAL 192 100
C. YEAR OF BIRTH
Number of respondents Percent of total
1973 or earlier 27 14
1974 17 9
1975 21 11
1976 37 19
1977 39 20
1978 37 19
1979 or later 13 7
No information 1 1
TOTAL 192 100
In Table 4.2 we review a number of salient characteristics of graduates in our sample and compare them against what is known about the wider population of graduates in similar age-groups. About 54% of sample graduates were female, in line with the gender split among recent graduates as a whole. In ethnic background some 91% were White compared to 85% in the wider graduate population. The sample of graduates had above average shares who had acquired A-levels or equivalent before starting university and had an above average share of people holding vocational qualifications certified by BTEC or SCOTVEC; the main disparity with the wider population of university graduates is the smaller proportion in the sample who are classified to ‘other qualifications’ apart from A-levels or BTEC/SCOTVEC awards.
The sample also turns out to be biased towards graduates who studied full-time and those who attended New Universities (60% of the sample compared to an estimated 42% of annual new graduates in the UK). The proportions gaining First or Upper Second class honours degrees were above those for graduates as a whole but the proportion which had gone on to gain postgraduate qualifications was much the same as in the wider population.
In respect of work experience gained before graduating, some 41% of sample graduates had undertaken some form of work experience with an employer as part of their course, substantially higher than in the wider population and only partly reflecting our focus on subjects such as computer science and business studies where there is an above average level of involvement in sandwich courses. However, in terms of other kinds of work experience gained as a student, the sample was in line with wider trends in having very high proportions of graduates who had undertaken paid work during term-time or vacations.
Given that we sought to identify employers via university Careers Service records, we anticipated that the sample would be biased towards graduates who had stayed on with their initial employer and this turned out to be the case. Just over two-thirds of sample graduates had started work with their present employer within six months of graduating whereas Labour Force Survey data suggest that only 23% of employed graduates in the 23-27 age group have been with their current employer since the age of 22.
However, in other respects the employment characteristics of sample graduates were not too badly out of line with the wider population, for example, 78% of them were employed in service industries and 16% in manufacturing, roughly in line with the overall distribution of graduates. In terms of occupational distribution, there was a relatively low proportion of sample graduates in occupations below associate professional level, but the 22% of sample graduates reporting that their degree-level skills and knowledge were ‘under-utilised’ in some way was roughly in line with findings based on much larger samples of recent graduates.
These sample characteristics have important implications for our investigation of the extent to which higher education has succeeded in enhancing the employability of graduates. Given that sample graduates are above the national average in terms of measures of educational attainment such as degree class, and have displayed a greater tendency to stay in employment with their initial main employer, it seems likely that the average quality of ‘matching’ between graduates and employers – in terms of meeting each other’s needs and requirements – is higher for sample graduates than for graduates as a whole. This likelihood needs to be borne in mind in later evaluation of our survey findings which we now go on to report. For example, any evidence that we find of shortfalls in graduate employability skills is likely to understate the extent of such shortcomings among graduates as a whole. Conversely, any evidence of employability skills being well developed in higher education will need to be treated with some caution unless and until other confirmatory evidence based on a wider survey of graduates and employers can be found. Nonetheless, we believe that the rare opportunity we have had to gather data from matched pairs of graduates and line managers has generated a great deal of new and interesting information relevant to debates about graduate employability skills formation.
Table 4.2: Characteristics of graduates in sample compared to what is known of wider population of graduates in similar age-group
Graduate characteristics Sample Population
Gender 54% female, 46% male
54% female, 46% male
(UK-domiciled First degree graduates, 1999, HESA)
Race 91% White
9% Other ethnic backgrounds
85% White
15% ethnic minority
(UK-domiciled First degree graduates, 1999, HESA)
Entry qualifications 84% A/AS levels or equivalent,
13% BTEC/SCOTVEC,
3% Other qualifications
70% A/AS levels or equivalent,
8% BTEC/SCOTVEC,
22% Other qualifications
(UCAS, 1997)
A-level score distribution 31% 26 points or more,
13% 21-25 points,
24% 16-20 points,
15% 11-15 points,
14% 6-10 points,
3% 5 points or fewer
24% 26 points or more,
17% 21-25 points,
26% 16-20 points,
17% 11-15 points,
15% 6-10 points,
1% 5 points or fewer
(UCAS, 1997)
Type of university 40% graduated from Old Universities,
60% from New Universities
58% graduated from Old Universities,
42% from New Universities
(Estimate for late 1990s, IER, Projections of Occupations and Qualifications, 1999/2000)
Mode of study 95% studied full-time for First degree
72% of First degree graduates studied full-time
(UK-domiciled First degree graduates, 1999, HESA)
Degree class 11% First class,
58% Upper second,
26% Lower second
5% Other 8% First class,
43% Upper second,
35% Lower second
14% Other
(UK-domiciled First degree graduates, 1999, HESA)
Postgraduate qualifications 19% hold postgraduate qualifications, primarily Masters degrees
18% of 23-27 year old graduates hold postgraduate qualifications
(Labour Force Survey, 1998)
Work experience as part of course
41% had undertaken work experience with an employer as part of their degree course
8% of all undergraduate students did sandwich course
Biology -- 7%
Computer science –29%
Business studies – 24%
Creative arts and design 4%
Humanities 0%
(UK-domiciled First degree graduates, 1999, HESA)
Paid work during term-time 52% did paid work during term-time while studying for their degree
47% of full-time students work during term-time
(Callender/Kemp survey, 1998-99, DfEE Research Report No. 213)
Table 4.2: (continued)
Characteristics of graduates in sample compared to what is known of wider population of graduates in similar age-group
Graduate characteristics Sample Population
Paid work during vacations 86% did paid work during vacations while studying for their degree
82% of full-time students work during summer vacations
(Callender/Kemp survey, 1998-99, DfEE Research Report No. 213)
Labour market history
11% were unemployed for three months or more since leaving university
Unemployment rate for sample of 1995 graduates reduced from 19% to 3% over first three years after graduation
(Moving On, 1999, IER/ AGCAS/ CSU)
68% started work with present employer within six months of completing university studies
In 1998 an estimated 23% of 23-27 year old graduates in employment had been with their current employer since the age of 22
(Labour Force Survey, 1998)
Current employment:
98% now work full-time for current employer
93% of 23-27 year old graduates in employment work full-time for current employer (Labour Force Survey, 1998)
1% self-employed 3.1% of 23-27 year old graduates in employment were self-employed (Labour Force Survey, 1998)
Sectoral distribution of employment 78% service industries
16% manufacturing industries
6% other industries
81% service industries
15% manufacturing industries
4% other industries
(23-27 year old graduates in employment, Labour Force Survey, 1998)
Occupational distribution of employment 10% managers and senior officials
33% professional occupations
37% associate professional occupations
8% administrative and secretarial occupations
2% other occupations
10% no information provided
[SOC2000 classification]
16% managers and
administrators
34% professional occupations
22% associate professional occupations
15% clerical and secretarial occupations
13% other occupations
[SOC1990 classification]
(23-27 year old graduates in employment, Labour Force Survey, 1998)
Indicator of ‘under-utilisation’ of graduate-level skills and knowledge
22% say their skills and knowledge are ‘too high’ for current jobs
72% say ‘about right’
6% say ‘too low’
Sample of 1995 graduates found 71% using degree-level skills and knowledge three years after graduation
(Moving On, 1999, IER/ AGCAS/ CSU)
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