Ranking academic institutions based on the productivity,impact,and quality of institutional scholars

Purpose:The quantitative rankings of over 55,000 institutions and their institutional programs are based on the individual rankings of approximately 30 million scholars determined by their productivity,impact,and quality.Design/methodology/approach:The institutional ranking process developed here considers all institutions in all countries and regions,thereby including those that are established,as well as those that are emerging in scholarly prowess.Rankings of individual scholars worldwide are first generated using the recently introduced,fully indexed ScholarGPS database.The rankings of individual scholars are extended here to determine the lifetime and last-five-year Top 20 rankings of academic institutions over all Fields of scholarly endeavor,in 14 individual Fields,in 177 Disciplines,and in approximately 350,000 unique Specialties.Rankings associated with five specific Fields(Medicine,Engineering&Computer Science,Life Sciences,Physical Sciences&Mathematics,and Social Sciences),and in two Disciplines(Chemistry,and Electrical&Computer Engineering)are presented as examples,and changes in the rankings over time are discussed.Findings:For the Fields considered here,the Top 20 institutional rankings in Medicine have undergone the least change(lifetime versus last five years),while the rankings in Engineering&Computer Science have exhibited significant change.The evolution of institutional rankings over time is largely attributed to the recent emergence of Chinese academic institutions,although this emergence is shown to be highly Field-and Discipline-dependent.Practical implementations:Existing rankings of academic institutions have:(i)often been restricted to pre-selected institutions,clouding the potential discovery of scholarly activity in emerging institutions and countries;(ii)considered only broad areas of research,limiting the ability of university leadership to act on the assessments in a concrete manner,or in contrast;(iii)have considered only a narrow area of research for comparison,diminishing the broader applicability and impact of the assessment.In general,existing institutional rankings depend on which institutions are included in the ranking process,which areas of research are considered,the breadth(or granularity)of the research areas of interest,and the methodologies used to define and quantify research performance.In contrast,the methods presented here can provide important data over a broad range of granularity to allow responsible individuals to gauge the performance of any institution from the Overall(all Fields)level,to the level of the Specialty.The methods may also assist identification of the root causes of shifts in institution rankings,and how these shifts vary across hundreds of thousands of Fields,Disciplines,and Specialties of scholarly endeavor.Originality/value:This study provides the first ranking of all academic institutions worldwide over Fields,Disciplines,and Specialties based on a unique methodology that quantifies the productivity,impact,and quality of individual scholars.

Google Scholar University Ranking Algorithm to Evaluate the Quality of Institutional Research

Education quality has undoubtedly become an important local and international benchmark for education,and an institute’s ranking is assessed based on the quality of education,research projects,theses,and dissertations,which has always been controversial.Hence,this research paper is influenced by the institutes ranking all over the world.The data of institutes are obtained through Google Scholar(GS),as input to investigate the United Kingdom’s Research Excellence Framework(UK-REF)process.For this purpose,the current research used a Bespoke Program to evaluate the institutes’ranking based on their source.The bespoke program requires changes to improve the results by addressing these methodological issues:Firstly,Redundant profiles,which increased their citation and rank to produce false results.Secondly,the exclusion of theses and dissertation documents to retrieve the actual publications to count for citations.Thirdly,the elimination of falsely owned articles from scholars’profiles.To accomplish this task,the experimental design referred to collecting data from 120 UK-REF institutes and GS for the present year to enhance its correlation analysis in this new evaluation.The data extracted from GS is processed into structured data,and afterward,it is utilized to generate statistical computations of citations’analysis that contribute to the ranking based on their citations.The research promoted the predictive approach of correlational research.Furthermore,experimental evaluation reported encouraging results in comparison to the previous modi-fication made by the proposed taxonomy.This paper discussed the limitations of the current evaluation and suggested the potential paths to improve the research impact algorithm.