Careers360 Ranking Methodology

The increase in number of seats for MBBS programme by over 35 percent in the last 5 years and opening of new institutions like AIIMS is indicative of the concern shown by different stakeholders, including the policymakers, towards medical education in the country. Though this growth is not proportionate to the need for medical professionals, the efforts in the direction are likely to show some positive outcomes in the domain.

Assessment of institutions

Out of the universe of around 500 Indian institutes that offer over 65,000 seats in MBBS programme, the first stage of shortlisting of 222 institutes was done on the basis of cut-offs in the state and national-level entrance tests as well as publication count in the last three years (2016-2018). Analysis of data set was carried out to assess rank/score in entrance tests and cut-offs. This was further corrected using normalization. The next level of analysis was carried out by applying a set of scientometric techniques looking at PubMed and Clarivate Analytics’ Web of Science (WoS) for searching publication records. The WoS covers scholarly articles from over 33,000 referred journals and is considered one of the most trusted sources of citation analysis. PubMed – a reputed academic-research database at the National Institute of Health, USA was used to make the evaluation process more robust. PubMed includes Medline records and has over 25 million bibliographic information of scholarly literature covering almost all the fields of life sciences, including health, biomedicine and chemical sciences. The data on number of core faculty, key departments, intake et al were taken from the database of Medical Council of India and Pharmacy Council of India as well as the official websites of institutes. Data submitted by institutes and information garnered from authentic sources like Annual Reports, NIRF website and et al were also considered

Publication and citation

For ranking purpose, the publication records of institutes were searched using an inbuilt ‘affiliation search’ box. For institutes or universities which have departments other than medicine, their publication records were restricted to publications from medicine departments only. The search, which was limited to three-year period (2016-18), retrieved a set of results such as publication count, number of citations received, citation per paper and h-index. The records from PubMed database were also searched in a similar fashion for 2015-17.

Patents

Patenting in the field of medicine is generally costly and time consuming. The records at Indian Patent Office were searched (Controller General of Patents Design and Trademark website) and information was collated on granted patents and filed intellectual Property (IP) by searching the institute’s name as it appears in any of the following fields: Name of Grantee, Applicant and Inventors address. As compared to Medical institutes, data and information for Pharmacy institutes on intellectual property (both granted and filed as well as IP earnings) was found to be more organized and uniform on the NIRF official platform which is officially submitted by medical institutes. Thus, for Pharmacy institutions, IP impact was also used as an evaluation parameter. Employing a threshold criterion, we chose to rank India’s 100 outstanding medical schools – 70 in public and 30 in private sector separately. Four key parameters were identified, as seen in the given figure with their weighted scores. Normalization was carried out for uniformity and scores were arrived at using max-min formula for some parameters.

India has close to 2200+law institutes approved by the Bar Council of India (BCI) for all levels of programmes being offered in law education. Careers360 Ranking is an attempt to assess the best law institutes among them on the basis of objective parameters that matter the most to students and helps the institutes to know where they exactly stand among their peers.

The process

The first step was to create a list of all the institutes that impart law programme(s) at the undergraduate level such as 5-year integrated BA/BBA/B.Com/BSc with LLB and also 3-year LLB. A short list was then made of those institutes assessed through cut-off scores (wherever available), and popularity on Careers360 portal and also figured in ranking/ rating of top law schools conducted by reputed magazines/ agencies in the last three years. This exercise gave us 445 such institutes. This included those that participated in the Careers360 ranking survey advertised in November 2018.

The second step involved a comprehensive exercise of populating the rank sheet with critical details like student enrolment, diversity, faculty members, educational qualification, infrastructure, residential facility, average salary of the recent passing out batch, research output, and the list was further pruned at looking at the publication count (2016-2018), average citations, productivity and h-index. This was done from the world’s two leading citation databases (Web of Science of Clarivate Analytics and Scopus of Elsevier science). However, to include more institutes, Google Scholar was also searched for the total number of institutions and it was restricted to 179 for final evaluation on all parameters

Research methodology

To map the research performance of Law schools, scholarly publication records were searched, including year-wise literature publication count from 2016, 2017 and 2018; total citation; average citation per paper and h-index. Publication records from the Web of Science (WoS) database were searched using the respective law university or institute and its department or school’s name in the address field. For this search, the WoS’s standard abbreviation was used in the search field. For example, “uni” is used for Universities and “Sch” is used for School and so on. Similarly, Scopus records were searched using the respective university or institute or school’s name in the “Affiliation” search field and retrieved results set. Records from Google Scholar were searched using the Google search advance search field.

The assessment parameters are as follows:

Intellectual Property Search

The universities’ intellectual property records (dominated by patent publications) were collected from two prominent databases -- the Indian Patent Office records (http:// ipindiaservices.gov.in/PublicSearch/) and from the World Intellectual Property Organization (WIPO) Patentscope database (https://patentscope.wipo.int/search/en/ advancedSearch.jsf) as under the publicly accessible norms. The Patentscope has lately started acquiring Indian patent records in its database coverage and according to Patentscope statistics; it has a collection of 74 million patent documents, including 3.5 million published international patent applications (PCT).

From the database, 500,763 patent records from Indian Patent Office were recorded. These records were searched putting the universities name in the abbreviated field (ANA: “respective universities’ name”).

For intellectual property, granted and filed applications of institutions were searched from the Indian Patent Advance Search System by putting the respective universities name in the Applicants’ Name or Applicant’s address search box using “Inventor’s Address” search field. For both filed and granted records, all the IPRs till 31.12.2018 were considered. Participating institutions in the announced survey were also asked about IP data.

Arriving at the Top 100 Universities

Employing a threshold criterion (say minimum publication count), we restricted to rank only the best – India’s Hundred Outstanding Universities – more in the public sector. The scores were arrived at using max-min formula for some parameters. The exercise involved a comprehensive search for all the degree awarding institutions, barring those that have come into existence in the last three years. The ranking is done separately for Public and Private universities.

The Rating Process

A cumulative rating was generated for all the institutes that occupy the same output pool using the above. We used the natural gaps that exist in any normal distribution to identify and delineate clusters.

The robustness of data enabled us to find discriminate amongst universities in different domains such as multidisciplinary (MDU), specific domains like agriculture, medicine, engineering and even specialized ones in the following category