A new approach to the <scp>QS</scp> university ranking using the composite <scp>I</scp>‐distance indicator: Uncertainty and sensitivity analyses

Dobrota, Marina; Bulajić, Milica; Bornmann, Lutz; Jeremić, Veljko

doi:10.1002/asi.23355

Cited by 85 publications

(63 citation statements)

References 69 publications

(81 reference statements)

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“…The main idea of incorporating the I‐distance in the DEA is to obtain the lower and upper bound in the GAR by calculating the correlation between the obtained I‐distance values and the indicators . The I‐distance solves the problem of incorporating a large number of indicators with different measurement units into one synthetic indicator without duplicating the information.…”

Section: Methodsmentioning

confidence: 99%

Going beyond health efficiency: What really matters?

Radojičić

Jeremić

Savić

2019

Health Planning & Management

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Both citizens and policymakers demand the best possible results from a country's healthcare system. It is of utmost importance to accurately and objectively assess the efficiency of a healthcare system and to note the key indicators, where resources are lost, and possibilities for improvement. This paper evaluates the efficiency of health systems in 38 countries, mainly members of the Organization for Economic Co-operation and Development, using data envelopment analysis (DEA). In the first stage, bootstrapped Ivanovic distance is used to generate weights for the indicators, thus taking into consideration different country's goals, but not to the extent of reducing the possibility of comparison. The analysis shows that human resources are the most important health system resource and countries should pay special attention to developing and employing competent medical workers. The reorganization of human resources and the funds allocated to them could also increase efficiency. The second stage examines environmental indicators to find the causes of inefficiency. No proof is found that any one basic health system funding model produces better health outcomes than the others. Obesity is identified as a major issue. K E Y W O R D Sefficiency evaluation, data envelopment analysis, health systems,

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Section: Methodsmentioning

confidence: 99%

Going beyond health efficiency: What really matters?

Radojičić

Jeremić

Savić

2019

Health Planning & Management

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“…Ranking as a hierarchical structure is used in the academic environment for many purposes, among others for evaluating quality in higher education [9,16], for determining the success of different departments within a university [5], for student selection [15] and for ranking specific student attributes to determine the probability of success [35,37]. In this section, the three selected models will be discussed and applied to the same data set.…”

Section: Ranking As Feedback In Learningmentioning

confidence: 99%

Mathematical modelling for academic performance status reports in learning analytics

Merwe

Kruger

Toit

2018

ORiON

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The fast changing nature of the educational environment and the subsequent increase in the volumes of generated learner data, have found existing data analysis techniques lacking in certain fields. These techniques form part of the analysis and reporting phases of learning analytics and need to adapt to accommodate the changing face of education. In this paper, a set of interrelated algorithmic solutions that utilise mathematical programming models to generate and provide learning feedback in the form of academic performance status reports, is presented. Three existing mathematical models, more specifically the benchMark program, an outputs-only data envelopment analysis and a traditional analytic hierarchy process were evaluated for providing the information required to assist students in improving their academic achievement. The requirements include providing students with their current academic performance status, setting interim improvement goals and calculating improvement targets towards reaching those goals. The evaluated models did not address the requirements satisfactorily. The solution proposed in this paper consists of an algorithm that implements a linear programming model to generate performance status reports based on the current assessment scores of a group of students in a module. The output is used in a second algorithm that utilises the remaining improvement opportunities available to generate a participation future time perspective. The resulting schedule together with each individual student's current assessment scores, is used to calculate discrete improvement goals for each student as well as targets towards reaching those goals. A third algorithm provides a lecturer with some insight into the mastering of module content.

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“…Hence, since 2009, the THE model has been separated from QS, which provided a new ranking system in cooperation with the Thomson Reuters database. In this new model, 13 indices were considered (Appendix 2), categorized into 5 groups as education, research, knowledge transfer (number of citations), industrial income, and international reputation (6,(12)(13)(14)(15)(16)(17).…”

Section: The Rankingmentioning

confidence: 99%

The Interacting Role of University Ranking and Globalization of Education

Ahmadi

Taghavinia

Arabshahi

et al. 2017

Strides Dev Med Educ

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Background: Based on the plan of revolution and innovation in medical education that was issued by the Iranian Ministry of Health and Medical Education, and the extensive role of such programs in the qualitative promotion of universities, The academic ranking of world universities is of great importance, since the qualitative and quantitative implementation of academic ranking can influence the realization of the university's goals. Hence, the current study aimed at collecting data about the academic ranking of world universities as well as its criteria and indices and their relationship with globalization. Methods: To gain access to reputable databases in university ranking, an extensive search was performed in Google Scholar. Thereafter, after getting access to reputable databases such as Shanghai Jiao Tong University (SJTU), Times higher education world University ranking (THE), Quacquarelli Symonds world University rankings (QS), Webometric, and Islamic world science citation center (ISC), data were collected and classified. Results: Based on the collected data, the history of university rankings and ranking systems, as well as criteria and indices pertaining to the academic ranking of world universities, was derived, and the specificities of the criteria and indices were discussed. Conclusions: University rankings are usually performed on a combination of performance-associated indices and criteria. Efforts to achieve a desirable position based on the criteria and indices of the ranking system play an important role in the promotion of educational quality and globalization.

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A new approach to the QS university ranking using the composite I‐distance indicator: Uncertainty and sensitivity analyses

Cited by 85 publications

References 69 publications

Going beyond health efficiency: What really matters?

Going beyond health efficiency: What really matters?

Mathematical modelling for academic performance status reports in learning analytics

The Interacting Role of University Ranking and Globalization of Education

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