Values of Quantitative Data Resulting in Qualitative Outcomes in Higher Education Institutions
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| Title: | Values of Quantitative Data Resulting in Qualitative Outcomes in Higher Education Institutions |
|---|---|
| Language: | English |
| Authors: | Mohammad Ghulam Ali (ORCID |
| Source: | Online Submission. 2025. |
| Peer Reviewed: | N |
| Page Count: | 17 |
| Publication Date: | 2025 |
| Document Type: | Reports - Evaluative |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Statistical Analysis, Educational Research, Research Methodology, Higher Education, Measurement, Outcomes of Education, Educational Quality, Reputation, Universities, Achievement Rating, Educational Indicators, Institutional Characteristics, Institutional Evaluation, Recognition (Achievement), Accreditation (Institutions) |
| Abstract: | In general, quantitative data (numerical and measurable) and qualitative data (descriptive and subjective) in higher education institutions represent quality and finally result in the quality of the higher education institutions. This research paper is focusing on the overall theory values of quantitative data in terms of qualitative outcomes. In most cases, quantitative data is the root of quality. However, qualitative data plays an independent role in reflecting quality in certain cases, such as peers' perceptions. We can also not deny that, even if qualitative reputation is high, weak quantitative data can pull down the final outcome. Strong performance in quantifiable areas boosts visibility in national/global rankings and attracts students, faculty, collaborations, and funding. Employers and collaborators prefer institutions with quantifiable excellence. In the ranking process, quantitative data acts as the measuring indicators, and in the results and outcomes, it acts as the determinant of final positions and institutional reputation, shaping perceptions, funding, and policy directions. Strong quantitative performance creates credibility, which leads to better qualitative recognition. Quantitative data acts as the engine powering qualitative outcomes in university rankings. Therefore, submission of correct and complete quantitative data with accuracy, consistency, reliability, and integrity to any university ranking or accrediting agencies can influence qualitative outcomes (transformation) in higher education institutions during performance assessment, quality assurance, and accreditation. Quantitative information will help institutions in making data-driven decisions and guide them in identifying areas where urgent strategic improvements are required based on the benchmark of ranking with the next top 10 and feedback given by the accreditation agencies on their identified parameters of evaluation. As a result, it will reflect and improve overall institutions' effectiveness in terms of academics, research, innovation, collaboration, graduate outcomes, employability, sustainability, and societal impact through various academic and research programs offered. We need to be aware of the values of completeness, correctness and sensitivity in quantitative data while submitting to any ranking or accredited agency. We have tried to illustrate the values of quantitative data needed by the institutions to participate in three different ranking frameworks that are QS WUR, THE WUR, and NIRF India Ranking and how all these ranking frameworks rely on institutional quantitative data. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | ED675726 |
| Database: | ERIC |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=ED675726 Name: ERIC Full Text Category: fullText Text: Full Text from ERIC |
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| Items | – Name: Title Label: Title Group: Ti Data: Values of Quantitative Data Resulting in Qualitative Outcomes in Higher Education Institutions – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mohammad+Ghulam+Ali%22">Mohammad Ghulam Ali</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-6012-6380">0000-0002-6012-6380</externalLink>) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Online+Submission%22"><i>Online Submission</i></searchLink>. 2025. – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: N – Name: Pages Label: Page Count Group: Src Data: 17 – Name: DatePubCY Label: Publication Date Group: Date Data: 2025 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Reports - Evaluative – Name: Audience Label: Education Level Group: Audnce Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink> – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Statistical+Analysis%22">Statistical Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Research%22">Educational Research</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Methodology%22">Research Methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement%22">Measurement</searchLink><br /><searchLink fieldCode="DE" term="%22Outcomes+of+Education%22">Outcomes of Education</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Quality%22">Educational Quality</searchLink><br /><searchLink fieldCode="DE" term="%22Reputation%22">Reputation</searchLink><br /><searchLink fieldCode="DE" term="%22Universities%22">Universities</searchLink><br /><searchLink fieldCode="DE" term="%22Achievement+Rating%22">Achievement Rating</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Indicators%22">Educational Indicators</searchLink><br /><searchLink fieldCode="DE" term="%22Institutional+Characteristics%22">Institutional Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Institutional+Evaluation%22">Institutional Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Recognition+%28Achievement%29%22">Recognition (Achievement)</searchLink><br /><searchLink fieldCode="DE" term="%22Accreditation+%28Institutions%29%22">Accreditation (Institutions)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In general, quantitative data (numerical and measurable) and qualitative data (descriptive and subjective) in higher education institutions represent quality and finally result in the quality of the higher education institutions. This research paper is focusing on the overall theory values of quantitative data in terms of qualitative outcomes. In most cases, quantitative data is the root of quality. However, qualitative data plays an independent role in reflecting quality in certain cases, such as peers' perceptions. We can also not deny that, even if qualitative reputation is high, weak quantitative data can pull down the final outcome. Strong performance in quantifiable areas boosts visibility in national/global rankings and attracts students, faculty, collaborations, and funding. Employers and collaborators prefer institutions with quantifiable excellence. In the ranking process, quantitative data acts as the measuring indicators, and in the results and outcomes, it acts as the determinant of final positions and institutional reputation, shaping perceptions, funding, and policy directions. Strong quantitative performance creates credibility, which leads to better qualitative recognition. Quantitative data acts as the engine powering qualitative outcomes in university rankings. Therefore, submission of correct and complete quantitative data with accuracy, consistency, reliability, and integrity to any university ranking or accrediting agencies can influence qualitative outcomes (transformation) in higher education institutions during performance assessment, quality assurance, and accreditation. Quantitative information will help institutions in making data-driven decisions and guide them in identifying areas where urgent strategic improvements are required based on the benchmark of ranking with the next top 10 and feedback given by the accreditation agencies on their identified parameters of evaluation. As a result, it will reflect and improve overall institutions' effectiveness in terms of academics, research, innovation, collaboration, graduate outcomes, employability, sustainability, and societal impact through various academic and research programs offered. We need to be aware of the values of completeness, correctness and sensitivity in quantitative data while submitting to any ranking or accredited agency. We have tried to illustrate the values of quantitative data needed by the institutions to participate in three different ranking frameworks that are QS WUR, THE WUR, and NIRF India Ranking and how all these ranking frameworks rely on institutional quantitative data. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2025 – Name: AN Label: Accession Number Group: ID Data: ED675726 |
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| RecordInfo | BibRecord: BibEntity: Languages: – Text: English PhysicalDescription: Pagination: PageCount: 17 Subjects: – SubjectFull: Statistical Analysis Type: general – SubjectFull: Educational Research Type: general – SubjectFull: Research Methodology Type: general – SubjectFull: Higher Education Type: general – SubjectFull: Measurement Type: general – SubjectFull: Outcomes of Education Type: general – SubjectFull: Educational Quality Type: general – SubjectFull: Reputation Type: general – SubjectFull: Universities Type: general – SubjectFull: Achievement Rating Type: general – SubjectFull: Educational Indicators Type: general – SubjectFull: Institutional Characteristics Type: general – SubjectFull: Institutional Evaluation Type: general – SubjectFull: Recognition (Achievement) Type: general – SubjectFull: Accreditation (Institutions) Type: general Titles: – TitleFull: Values of Quantitative Data Resulting in Qualitative Outcomes in Higher Education Institutions Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mohammad Ghulam Ali IsPartOfRelationships: – BibEntity: Dates: – D: 27 M: 09 Type: published Y: 2025 Titles: – TitleFull: Online Submission Type: main |
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