In the Shadow of Celebrity? World-Class University Policies and Public Value in Higher Education

The growing popularity of the concept of world-class universities raises the question of whether investing in such universities is a worthwhile use of public resources. Does concentrating public resources on the most excellent universities improve the overall quality of a higher education system, especially if definitions of excellence and world-class are made by external ranking organizations? This paper addresses that question by developing a framework for weighing up trade-offs between institutional and system performance, focusing on the potential system-wide improvements which world-class university programmes (WCUPs) may bring. Because WCUPs are in a relatively early stage of their development, systemic effects are not yet clear. We therefore analyse the ex ante reasons that policy makers have for adopting WCUPs to see if they at least seek to create these systemic benefit

Proposal for a multilevel university cybermetric analysis model

The final publication is available at Springer via http://dx.doi.org/10.1007/s11192-012-0868-5Universities’ online seats have gradually become complex systems of dynamic information where all their institutions and services are linked and potentially accessible. These online seats now constitute a central node around which universities construct and document their main activities and services. This information can be quantitative measured by cybermetric techniques in order to design university web rankings, taking the university as a global reference unit. However, previous research into web subunits shows that it is possible to carry out systemic web analyses, which open up the possibility of carrying out studies which address university diversity, necessary for both describing the university in greater detail and for establishing comparable ranking units. To address this issue, a multilevel university cybermetric analysis model is proposed, based on parts (core and satellite), levels (institutional and external) and sublevels (contour and internal), providing a deeper analysis of institutions. Finally the model is integrated into another which is independent of the technique used, and applied by analysing Harvard University as an example of use.Orduña Malea, E.; Ontalba Ruipérez, JA. (2013). Proposal for a multilevel university cybermetric analysis model. Scientometrics. 95(3):863-884. doi:10.1007/s11192-012-0868-5S863884953Acosta Márquez, T., Igartua Perosanz, J.J. & Gómez Isla, J. (2009). Páginas web de las universidades españolas. Enred: revista digital de la Universidad de Salamanca, 5 [online; discontinued].Aguillo, I. F. (1998). Hacia un concepto documental de sede web. El Profesional de la Información, 7(1–2), 45–46.Aguillo, I. F. (2009). Measuring the institutions’ footprint in the web. Library Hi Tech, 27(4), 540–556.Aguillo, I. F., Granadino, B., Ortega, J. L., & Prieto, J. A. (2006). Scientific research activity and communication measured with cybermetrics indicators. Journal of the American Society for Information Science and Technology, 57(10), 1296–1302.Aguillo, I. F., Ortega, J. L., & Fernández, M. (2008). Webometric Ranking of World Universities: introduction, methodology, and future developments. Higher Education in Europe, 33(2/3), 234–244.Ayan, N., Li, W.-S., & Kolak, O. (2002). Automatic extraction of logical domains in a web site. Data & Knowledge Engineering, 43(2), 179–205.Barjak, F., Li, X., & Thelwall, M. (2007). Which factors explain the Web impact of scientists’ personal homepages? Journal of the American Society for Information Science and Technology, 58(2), 200–211.Berners-Lee, T., & Fischetti, M. (2000). Tejiendo la Red. Madrid: Siglo XXI.Björneborn, L., & Ingwersen, P. (2004). Toward a basic framework for webometrics. Journal of the American Society for Information Science and Technology, 55(14), 1216–1227.Buenadicha, M., Chamorro, A., Miranda, F. J., & González, O. R. (2001). A new web assessment index: Spanish Universities Analysis. Internet Research, 11(3), 226–234.Castells, M. (2001). La galaxia Internet. Barcelona: Plaza y Janés.Chu, H., He, S., & Thelwall, M. (2002). Library and Information Science Schools in Canada and USA: a Webometric perspective. Journal of Education for Library and Information Science, 43(2), 110–125.Crowston, K., & Williams, M. (2000). Reproduced and Emergent Genres of Communication on the World Wide Web. The Information Society: an International Journal, 16(3), 201–215.Goldfarb, A. (2006). The (teaching) role of universities in the diffusion of the Internet. International Journal of Industrial Organization, 24(2), 203–225.Ingwersen, P. (1998). The calculation of web impact factors. Journal of Documentation, 54(2), 236–243.Katz, R. N. (2008a). The tower and the cloud: Higher education in the age of cloud computing. USA: Educause.Katz, R. N. (2008b). The gathering cloud: is this the end of the middle. In R. N. Katz (Ed.), The tower and the cloud: Higher education in the age of cloud computing (p. 2008). USA: Educause.Li, X. (2005). National and international university departmental Web site interlinking: a webometric analysis. [Unpublished doctoral dissertation]. Wolverhampton, UK: University of Wolverhampton.Li, X., Thelwall, M., Musgrove, P., & Wilkinson, D. (2003). The relationship between the links/Web Impact Factors of computer science departments in UK and their RAE (Research Assessment Exercise) ranking in 2001. Scientometrics, 57(2), 239–255.Middleton, I., McConnell, M., & Davidson, G. (1999). Presenting a model for the structure and content of a University World Wide Web site. Journal of Information Science, 25(3), 217–219.Orduña-Malea, E. (2012). Propuesta de un modelo de análisis redinformétrico multinivel para el estudio sistémico de las universidades españolas (2010). Valencia: Polytechnic University of Valencia.Ortega, J. L., & Aguillo, Isidro. F. (2007). La web académica española en el contexto del Espacio Europeo de Educación Superior: estudio exploratorio. El profesional de la información, 16(5), 417–425.Pareja, V. M., Ortega, J. L., Prieto, J. A., Arroyo, N., & Aguillo, I. F. (2005). Desarrollo y aplicación del concepto de sede web como unidad documental de análisis en Cibermetría. Jornadas Españolas de Documentación, 9, 325–340.Saorín, T. (2012). Arquitectura de la dispersión: gestionar los riesgos cíclicos de fragmentación de las webs corporativas. Anuario ThinkEPI, 6, 281–287.Tang, R., & Thelwall, M. (2003). U.S. academic departmental Web-site interlinking: disciplinary differences. Library & Information Science Research, 25(4), 437–458.Tang, R., & Thelwall, M. (2004). Patterns of national and international web inlinks to US academic departments: an analysis of disciplinary variations. Scientometrics, 60(3), 475–485.Thelwall, M. (2002a). A research and institutional size based model for national university Web site interlinking. Journal of Documentation, 58(6), 683–694.Thelwall, M. (2002b). Conceptualizing documentation on the Web: an evaluation of different heuristic-based models for counting links between university web sites. Journal of the American Society for Information Science and Technology, 53(12), 995–1005.Thelwall, M. (2003). Web use and peer interconnectivity metrics for academic Web sites. Journal of Information Science, 29(1), 11–20.Thelwall, M. (2009). Introduction to Webometrics: quantitative web research for the social sciences. San Rafael: Morgan & Claypool.Thelwall, M., & Harries, G. (2004a). Can personal Web pages that link to universities yield information about the wider dissemination of research? Journal of Information Science, 30(3), 243–256.Thelwall, M., & Harries, G. (2004b). Do better scholars’ Web publications have significantly higher online impact? Journal of American Society for Information Science and Technology, 55(2), 149–159.Thelwall, M., Vaughan, L., & Björneborn, L. (2005). Webometrics. Annual Review of Information Science and Technology, 39, 81–135.Thomas, O., & Willet, P. (2000). Webometric analysis of Departments of librarianship and information science. Journal of Information Science, 26(6), 421–428.Tíscar, L. (2009). El papel de la universidad en la construcción de su identidad digital. Revista de universidad y sociedad del conocimiento, 6(1), 15–21.Van Vught, F. A. (2009). Diversity and differentiation in higher education. In F. Van Vught (Ed.), Mapping the higher education landscape: toward a European classification of higher education (pp. 1–16). The Netherlands: Springer.Yolku, O. (2001). Use of news articles and announcements on official websites of universities. Turkish Online Journal of Educational Technology, 10(2), 287–296

Quality Assurance Driving Factors as Antecedents of Knowledge Management: a Stakeholder-Focussed Perspective in Higher Education

Similar to many other types of organisations, the successful development of higher education institutions generally depends on proactive multi-stakeholder management strategy. As a social responsibility of universities, quality assurance (QA) of higher education is already an established research domain. However, the issues that serve as driving factors in higher education’s quality are acknowledged in this vast knowledge stream in a dispersed way. An objective of this paper is to provide a quick snapshot of the major QA driving factors in higher education. Another objective here is to discuss the significance of these existing QA driving factors in higher education as prospective antecedents of knowledge management among the key stakeholders in the higher education sector and beyond. An inductive constructivist approach is followed to review the relevant QA driving factors from the extant scholarly views. A number of relevant factors are précised from the literature that would be instrumental to uphold quality in higher education. The discussion demonstrates that these factors are also significant to transfer and share knowledge between the key stakeholders not only for universities, but also for businesses, governments and other organisational stakeholders. The paper proposes a framework of the QA drivers’ application for meaningful knowledge transfer between diverse stakeholders and clarifies the framework’s managerial implications. This conceptual framework specifies different scenarios and perspectives of QA drivers’ application in the global education sector. The academic novelty is based on the inductive approach applied in the paper. QA practitioners will be able to follow these factors as steering phenomena to effectively assure quality, in relation to their multi-stakeholder relationships in higher education and beyond

Differential profiling of lacrimal cytokines in patients suffering from thyroid-associated orbitopathy.

The aim was to investigate the levels of cytokines and soluble IL-6R in the tears of patients with thyroid-associated orbitopathy (TAO) disease. Schirmer's test was adopted to collect tears from TAO patients (N = 20, 17 women, mean age (±SD): 46.0 years (±13.4)) and healthy subjects (N = 18, 10 women, 45.4 years (±18.7)). Lacrimal cytokines and soluble IL-6R (sIL-6R) were measured using a 10-plex panel (Meso Scale Discovery Company) and Invitrogen Human sIL-6R Elisa kit, respectively. Tear levels of IL-10, IL-12p70, IL-13, IL-6 and TNF-α appeared significantly higher in TAO patients than in healthy subjects. Interestingly, IL-10, IL-12p70 and IL-8 levels increased in tears whatever the form of TAO whereas IL-13, IL-6 and TNF-α levels were significantly elevated in inflammatory TAO patients, meaning with a clinical score activity (CAS) ≥ 3, compared to controls. Furthermore, only 3 cytokines were strongly positively correlated with CAS (IL-13 Spearman coeff. r: 0.703, p = 0.0005; IL-6 r: 0.553, p = 0.011; IL-8 r: 0.618, p = 0.004, respectively). Finally, tobacco use disturbed the levels of several cytokines, especially in patient suffering of TAO. The differential profile of lacrimal cytokines could be useful for the diagnosis of TAO patients. Nevertheless, the tobacco use of these patients should be taken into account in the interpretation of the cytokine levels