All information presented in this bulletin has been validated and quality assured by HEIs prior to publication. HEIs are given a set period of time to submit the information to HESA. Following submission, both HESA and DfE perform a series of validation checks to ensure that information is consistent both within and across returns. Trend analyses are used to monitor annual variations and emerging trends. Queries arising from validation checks are presented to HEIs for clarification and, if required, returns may be amended and/or re-submitted. Finally, prior to publication, the data are presented to HEIs for a final sign- off. More detail is available via the link: Quality of HigherEducation Statistics.
HESA is the official agency for the collection of information on publicly funded HigherEducation (HE) institutions in the UK. It was set up in 1993 following the White Paper ‘HigherEducation: a new framework’, which called for more coherence in HE statistics. This joint approach throughout the UK had ensured direct comparisons between countries and individual institutions can be made. The specification and definitions of data are subject to a major review every few years. From time to time it is necessary to change definitions which can impact the comparability of time series data. When this does happen any discontinuities in the data are made clear and/or data are backdated to take account of the new definitions. For example, from the 2007/08 academic year the definition of HESA’s Standard Registration Population changed to exclude those students who were writing up or on sabbatical. In order to maintain time series accuracy, all historical data published or released by DfE in and after the 2007/08 enrolments bulletin uses the new Standard Registration Population definition.
On receipt of data from HESA, DfE statisticians produce two NI specific datasets, one for NI students enrolled at UK HEIs and the second for all students enrolled at NI HEIs. These data sets are cross‐verified, across a range of variables, with previously published HESA data. Once the datasets are completed and verified they are then used to prepare the Enrolments and Qualifications statistical bulletins. Prior to publication, DfE’s bulletins will undergo rigorous checking procedures including peer review of syntax used to analyse data from the HESA databases, parallel production of data tables using pivot tables and statistical software packages, and extensive proof reading of commentary, tables, notes to readers and
This statistical bulletin has been produced by the Department for the Economy (DfE) and presents information on HigherEducation (HE) qualifications gained by NorthernIreland (NI) domiciled students at HigherEducationInstitutions (HEIs) in the UK in the 2017/18 academic year, and by all students at NI HEIs in the same time period. The statistics presented in this bulletin cover a range of topics, including changes over the last ten years, mode and level of study, subject of study and classification of first degree. National Statistics
The bulletin is divided into two sections. Section 1 focuses on the destinations of NI domiciled students who gained a qualification at a HEI in NI, England, Scotland or Wales. Section 2 concentrates on the destinations of all NI, GB and other EU students who gained a qualification at a NI HEI. This division into two sections reflects the two distinct policy and operational responsibilities of the Minister and the Department. Furthermore, it is clear from customer feedback, the nature of questions on HE asked in the NorthernIreland Assembly, and coverage of HE issues in the local media, for example, that these two aspects are of interest to readers. Therefore it has been decided to present
The statistical bulletins are used by a variety of customers, both internal and external. For example, they are used by DfE policy development officials to monitor existing policies, and for future planning; by other government departments and agencies such as the NorthernIreland Statistics and Research Agency (NISRA); by prospective students to inform their choices around highereducation; and by local businesses to quantify the supply of graduates in their business area. Customers’ views on the bulletins and feedback from previous years have been very positive. Results from previous customer surveys can be viewed at https://www.economy-
8. Target population – The HESA DLHE report’s target population includes all UK and European Union (EU) domiciled leavers at a UK HEI and who obtained relevant qualifications (see note 10) reported to HESA for the reporting period 1st August 2014 to 31st July 2015. The coverage of the survey was expanded to include additional HE qualifications and now includes Non-EU domiciled leavers as part of a pilot. Surveying these leavers was undertaken with a clear distinction that the information collected should not be published until carefully reviewed.
The coverage of the survey has been expanded to include additional HE qualifications and now includes Non-EU domiciled leavers where it was previously restricted to UK and European Union domiciled leavers only. Surveying these leavers was undertaken as a pilot from 2011/12 with a clear distinction that the information collected should not be published until carefully reviewed. These leavers are therefore excluded from this bulletin. Additionally, there were leavers who obtained postgraduate research qualifications from dormant status (For example those returning to submit a thesis or to retake exams during the reporting period). The destination outcomes of these leavers are considered to be materially different in nature to the outcomes of the other postgraduate research leavers included in the survey so these leavers have been excluded.
All information presented in this bulletin is based on data that have been validated and quality assured by FE colleges prior to publication. FE colleges are given a set period of time to submit the information to the Statistics & Research Branch (Tertiary Education), which performs a series of validation checks to ensure that information is consistent both within and across returns and analyses to monitor annual variations and emerging trends. Queries arising from validation checks are presented to FE colleges for clarification and, if required, returns may be amended and/or re-submitted. Finally, prior to the publication of this information, the data are presented to FE colleges for final sign–off. A short quality assessment on this analysis is available for further information in Annex C: Quality measures.
2. The data presented in this bulletin are based on data supplied by the HigherEducation Statistics Agency (HESA). HESA is the official agency for the collection of information on publicly funded HigherEducation (HE) institutions in the UK. It was set up in 1993 following the White Paper ‘HigherEducation: a new framework’, which called for more coherence in HE statistics. HE institutions include all publicly-funded universities. The HESA data presented in this bulletin relate to students at HE institutions in the UK and therefore do not include HE enrolments at FE colleges in NI or GB, or at institutions in the Republic of Ireland. 3. A new specification of the HigherEducation Statistics Agency (HESA)
The bulletin is divided into two sections. Section 1 focuses on NI domiciled students enrolled at HEIs in NI, England, Scotland or Wales. Section 2 concentrates on all students enrolled at NI HEIs. This division into two sections reflects the two distinct policy and operational responsibilities of the Minister and the Department. Furthermore, it is clear from customer feedback, the nature of questions on HE asked in the NorthernIreland Assembly, and coverage of HE issues in the local media, for example, that these two aspects are of interest to readers. Therefore it has been decided to present breakdowns of information on HE along these two dimensions in this bulletin.
This statistical bulletin has been produced by the Department for Employment and Learning (DEL), NorthernIreland (NI) and presents information on HigherEducation (HE) qualifications gained by NI domiciled students at HigherEducationInstitutions (HEIs) in the UK in 2013/14 and by all students at NI HEIs. The statistics presented in this bulletin cover a range of topics including changes over the last ten years, mode and level of study, subject of study and classification of first degree.
This paper critically analyses the role of Personal Tutoring (PT) as a mechanism for providing student support in HigherEducation (HE) in the UK. The discussions presented will draw on the experiences of PT at City University, London (City), as well as the author’s own experiences as a student, to establish a better sense of what PT means today. Focus will be placed on the benefits and challenges of typical PT systems in HE, as influenced by widening participation policies and strategies to improve retention rates. In carrying out this analysis, this paper will conclude by arguing the case for PT to remain a necessary process, rather than be replaced entirely by central support departments.
41 published research is one of the main criteria for success in HEIs, research collaboration with established researchers is considered vital to promote young academics to do research. In other words, mentorship is crucial in HEIs, especially in research activities as it is a way to inspire and guide junior academics into research. A review article by Jacobi (1991), emphasising on relationship between mentoring and academics success, has extracted five elements of mentorship in academia: (1) focuses on achievement or acquisition of knowledge; (2) composes of three key components (i.e. emotional and psychological support, direct assistance with career and professional development, and role modelling); (3) focuses on reciprocal relationship between mentor and mentee; (4) is personal in nature, involving personal or direct interaction; and (5) focuses on the mentors‘ broad experience, influence, and achievement. Using a combination of survey and focus group study, Phillips (2009) has examined the impact of peer mentoring schemes in 94 UK universities, involving first year students attending a UK university. He reported that all students would seek guidance from peer mentor if one was available. It can be argued that young academics working in HEIs would also want to seek advice and supervision from someone with more knowledge, experience, and accomplishment, i.e. a mentor.
The costs reported in panel A of Table 4 may be compared with the HigherEducation Funding Council for England (HEFCE) resource rates for the four subject price groups for undergraduates. For the year 2002/03 (which is the appropriate comparison with the figures estimated here) these were, respectively for groups A, B, C and D, £12939, £5750, £4313 and £2875. Group A refers to clinical medicine, dentistry and veterinary science; group B refers to laboratory based subjects; group C refers to subjects with a studio, laboratory or fieldwork element; and group D refers to all other subjects. Groups A and B correspond exactly to our definitions of medicine and other science respectively, while groups C and D are combined into undergraduate non-science. The pattern of AICs in these figures corresponds with the pattern observed in the statistical estimates and this raises the question of whether the statistical cost functions are simply describing a funding formula. This is unlikely to be the case for several reasons. First, while the pattern is the same, the level in the case of undergraduate medicine is considerably different. Second, the specification of the model includes several variables that are not formula funded – including postgraduate numbers, research, and third mission work. Indeed, only about 40% of universities' income comes from the funding council. The specification of the model is, moreover, non-linear, whereas formula funding is linear in nature. Third, the analysis is in line with other work of this kind – including work such as that of Cohn et al. (1989) which was conducted in the USA where resources are not allocated by formula. Finally, and in our view most tellingly, the use of SFA provides a safeguard against the misrepresentation of expenditures as costs since the functions estimated by SFA tell us what the parameters would be for a technically efficient institution. Nevertheless the possibility cannot be entirely dismissed that, as Bowen (1980) has argued, ‘each institution raises all the money it can’ and ‘each institution spends all it raises’.
Secondly, while it is common in the literature to use a Hausman test to evaluate the performance of RE versus FE models, it is not appropriate to do so in the present context. The quadratic specification of the cost function is chosen for theoretical reasons, and in practice the estimation of such equations is characterised by a high degree of multicollinearity. This is of little importance in terms of the ability of the equation to evaluate costs, but it does mean that the individual parameters are estimated with a high degree of imprecision. The Hausman test is based on a comparison of the parameter vectors and, as such, is unlikely to be informative in this context. Thirdly, we use the results of our cost equation estimates later in this paper to estimate measures of economies of scope and ray economies of scale. This would not be difficult to achieve using the results of a FE estimator, since this estimator does not provide a unique parameter for the intercept term. Fourthly, it would be difficult for institutions to effect any substantial change in the values of the explanatory variables in the short term, but it is of course possible for them to become more or less efficient; the error term is therefore independent of the explanatory variables and RE estimation is appropriate. Despite our preference, on all these grounds, for the RE estimator, we undertook some early experimentation using the FE model. The distribution of institution-specific constants was roughly normal with the exception of two outliers - Oxford and Cambridge. For this reason we include an OXBRIDGE dummy in the RE specification of the model.
Amongst undergraduates, medical students are found to be the most costly, and non- science students the least. Amongst postgraduates, those on taught courses are costly, while research students (presumably because they provide a source of cheap teaching and research assistance) are relatively inexpensive. This last finding contrasts spectacularly with the results obtained by HEFCE’s cost transparency exercise (probably because the latter calculates the gross costs of research students rather than, as here, the net costs). Location in London and quality considerations do not appear to impact significantly on the analysis. Estimates of economies of scale and economies of scope vary according to the choice of estimating technique. The RE model suggests that ray economies of scale and econo- mies of scope are ubiquitous (though generally not huge). The SFA model suggests some product-specific economies of scale in research, but diseconomies elsewhere, and product- specific economies of scope in undergraduate science, but diseconomies elsewhere. As a consequence, the RE model predicts that uniform expansion of all outputs can most efficiently be realised by expansion of the existing institutions rather than by creation of new ones, whereas the SFA model predicts that such an expansion should be effected by creating new (efficient) institutions, so long as the one-off set-up costs are less than the
(research and teaching requires different resources). Third, tensions arise among academics due to the funding mechanisms and the inequity of rewards for research and for teaching (McLernon & Hughes, 2003). Due to research being more rewarding compared to teaching, academics aim for research excellence while sacrificing their teaching duties (Baker et al, 1998). This issue is not just unique to UK, but is an issue of international relevance. For instance, the Boyer Commission report (1998) addresses this issue by calling for significant changes in undergraduate education in the United States. With this background knowledge on the UKhighereducation system, the next section discusses the relationship between research and teaching in highereducation.
The figures should include payments made directly to the publishers as well as any payments made to subscription agents or intermedi- aries for the purchase of, and/or access to, the publishers’ academic journals. Institutions were asked to provide data for the payment for journal packages such as Jisc Collections’ NESLi agreement, as well as for individual journals, and to include VAT where possible. Since the authors are relying solely on data provided by the HEIs it is not possible to independently verify whether all of these aspects of the requests have been adhered to. While this may result in some inaccuracies in individual figures, the authors do not consider that the overall scale will be unduly affected.
This article seeks to highlight some of the key issues for HEIs in relation to IT governance and summarises a new framework approach to IT governance in highereducation, which has been developed for the Joint Information Systems Committee (JISC).Throughout this article the term ‘IT’ in its broadest sense, to denote not only physical hardware and software and infrastructural systems but also to encompass the holistic issues associated with how an institution uses technology to support its business.