Application of Academic Analytical Models in Education Management
DOI:
https://doi.org/10.36941/jesr-2024-0171Keywords:
Learning Analytics, Machine Learning, Natural Language Processing, Education Data MiningAbstract
Objective: The primary objective of the current study is to provide an analytical systematic review on the application of academic analytical models in educational management and how the related techniques can be used to enhance quality outcomes and learning processes. Methodology: The study adopted the methodological framework outlined by the Joanna Briggs Institute (2015) and was informed by Arksey and O’Malley’s (2005) approach of summary and dissemination of research findings and, in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Findings: Learning analytics has emerged as the most relevant educational concept with the potential of collecting, analyzing and reporting data on learners, educators and administrators for efficient educational management processes. Analytics in education enhances the capabilities of the educators of determining the learners’ performances and identification of areas for improvement to make data-driven learning decisions. Conclusions: The application of analytical models in educational management is based on different domains such as customized learning, intelligent tutoring systems, predictive modelling, automated grading and assessments, and natural language processing.
Received: 26 July 2024 / Accepted: 25 October 2024 / Published: 05 November 2024
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.