Opportunities and challenges for international institutional data comparisons

Lepori, Benedetto; Borden, Victor M. H.; Coates, Hamish

doi:10.1080/21568235.2022.2094817

Cited by 6 publications

(3 citation statements)

References 52 publications

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“…Studying the specific case of Brazilian universities, which constitute the central focus of this tutorial database, it becomes evident that these institutions operate within diverse contextual frameworks. These contexts encompass several facets, such as varying academic orientations [29], differing levels of public or private investment [30], differences in the quality of professor training [31], geographical locations with distinct demographic characteristics [32], different social demands for which their existence is justified [33], and different aspirations for internationalization [34], among other factors.…”

Section: Multilevel Perspectivementioning

confidence: 99%

Multilevel Ordinal Logit Models: A Proportional Odds Application Using Data from Brazilian Higher Education Institutions

Freitas Souza,

Lima,

Corrêa

2024

Axioms

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This tutorial delves into the application of proportional odds-type ordinal logistic regression to assess the impact of incorporating both fixed and random effects when predicting the rankings of Brazilian universities in a well-established international academic assessment utilizing authentic data. In addition to offering valuable insights into the estimation of ordinal logistic models, this study underscores the significance of integrating random effects into the analysis and addresses the potential pitfalls associated with the inappropriate treatment of phenomena exhibiting categorical ordinal characteristics. Furthermore, we have made the R language code and dataset available as supplementary resources for the replication.

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Section: Multilevel Perspectivementioning

confidence: 99%

Multilevel Ordinal Logit Models: A Proportional Odds Application Using Data from Brazilian Higher Education Institutions

Freitas Souza,

Lima,

Corrêa

2024

Axioms

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“…These data should be collected and managed nationally and internationally by appropriate organisations with adequate expertise and a public-interest mandate. An example of such an initiative is the European Tertiary Education Register (ETER), [34] as well as the recently announced European Higher Education Sector Observatory, under the auspices of the European Commission. [35] Governments and other national bodies should embrace a more holistic and context-sensitive view of higher education quality -in contrast to the reductionist, one-size-fits-all model promoted by global rankings -and should stimulate universities to develop their own strategies in this direction.…”

Section: Conclusiónmentioning

confidence: 99%

Nuevamente sobre el impacto negativo de los rankings universitarios en la gestión de los sistemas de educación superior universitaria.

Barsky

2024

Debate Universitario

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En el primer número de la revista Debate Universitario de noviembre de 2012, publiqué un artículo: “Acerca de los rankings internacionales de las universidades y su repercusión en la Argentina”. Hacía varios años que venía participando en los esfuerzos de universidades privadas por mejorar sus posiciones en el ranking mundial y latinoamericano de universidades que confeccionaba la consultora QS, siglas que corresponden a los socios fundadores Quacquarelly y Symonds. La consultora la dirige Nunzio Quacquerelly (Symonds parece haberse apartado muy tempranamente de la empresa) y ha sido siempre extremadamente audaz para instalarse en el mercado de los rankings, al descubrir el vacío institucional existente y la ansiedad de los dirigentes de las universidades por ocupar un lugar destacado en sus listados.

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“…While the systematic collection of institutional-level data in the US started already in the 1960s and evolved to an integrated data system in the 1980s already 15 , no similar system existed in Europe until recently. Data at the level of individual HEIs were mostly collected for administrative purposes and not always made available to the general public; national fragmentation also made the comparability of national data problematic 16 .…”

Section: Background and Summarymentioning

confidence: 99%

The European Tertiary Education Register, the reference dataset on European Higher Education Institutions

et al. 2023

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The European Tertiary Education Register (ETER) is the reference dataset on European Higher Education Institutions (HEIs). ETER provides data on nearly 3,500 HEIs in about 40 European countries, including descriptive information, geographical information, students and graduates (with various breakdowns), revenues and expenditures, personnel, and research activities; as of March 2023, data cover the years from 2011–2020. ETER complies with OECD-UNESCO-EUROSTAT standards for educational statistics; most data are collected from National Statistical Authorities (NSAs) or ministries of participating countries and are subject to extensive checks and harmonization. The development of ETER has been funded by the European Commission and is part of the current efforts to establish a European Higher Education Sector Observatory; it is closely connected to the establishment of a broader data infrastructure in the field of science and innovation studies (RISIS). The ETER dataset is widely used in the scholarly literature on higher education and science policy, as well as for policy reports and analyses.

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Opportunities and challenges for international institutional data comparisons

Cited by 6 publications

References 52 publications

Multilevel Ordinal Logit Models: A Proportional Odds Application Using Data from Brazilian Higher Education Institutions

Multilevel Ordinal Logit Models: A Proportional Odds Application Using Data from Brazilian Higher Education Institutions

Nuevamente sobre el impacto negativo de los rankings universitarios en la gestión de los sistemas de educación superior universitaria.

The European Tertiary Education Register, the reference dataset on European Higher Education Institutions

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