Revolutionising Higher Education: A Big Data‐Driven Approach to Intelligent Supervision Platforms in Universities.
Background: The creation of Intelligent Supervision Platforms in universities leverages Big Data for robust monitoring and decision‐making, which significantly enhances overall efficiency and adaptability in educational environments. Objectives: This research focuses on evaluating how Big Data‐drive...
| Publicado en: | Journal of Computer Assisted Learning Vol. 41; no. 5; pp. 1 - 17 |
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| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Oct2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188234196&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188234196 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Oct2025 vid: 41 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 188234196 188234196 188234196 10.1111/jcal.70084 188234196 ppf: 1 ppct: 16 formats: tig: atl: Revolutionising Higher Education: A Big Data‐Driven Approach to Intelligent Supervision Platforms in Universities. aug: au: Chen, Jing Chen, Tianhui affil: School of Marxism, Hohai University, Jiangsu, , China sug: subj: Colleges and Universities Education, Masters Educational Technology Academic Performance Data Analytics Automation Human Male Female Adolescence Adult Descriptive Statistics Data Analysis Software Coefficient alpha Linear Regression Learning Methods Funding Source Digital Technology Structured Questionnaires Adolescent: 13-18 years Adult: 19-44 years Male Female ab: Background: The creation of Intelligent Supervision Platforms in universities leverages Big Data for robust monitoring and decision‐making, which significantly enhances overall efficiency and adaptability in educational environments. Objectives: This research focuses on evaluating how Big Data‐driven Intelligent Supervision Platforms in universities influence core institutional outcomes, namely, perceived academic performance, student retention, faculty productivity, and data‐informed decision‐making. The study prioritises these key variables to demonstrate the strategic role of Intelligent Supervision Platforms in enhancing higher education performance. Methods: Data were gathered from 420 students and 118 teachers using a questionnaire method, and the quantitative data were analysed with Statistical Package for the Social Sciences (SPSS) software. The novelty of this study lies in its focus on the development of intelligent supervision platforms tailored specifically for the unique needs and dynamics of university settings. Results: The findings show that the implementation of intelligent supervision platforms, driven by Big Data analytics, positively affects students' perceived academic performance. Conclusions: The integration of Big Data analytics into intelligent supervision platforms can significantly enhance decision‐making processes and support personalised learning experiences; such platforms improve faculty and staff productivity, streamline administrative operations, and optimise resource allocation within universities, ultimately contributing to a more efficient and effective educational environment. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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