UTILIZING DATA MINING TECHNIQUES TO IMPROVE THE QUALITY OF EDUCATION IN MALAWIAN UNIVERSITIES

UTILIZING DATA MINING TECHNIQUES TO IMPROVE THE QUALITY OF EDUCATION IN MALAWIAN UNIVERSITIES

Registration ID: IJNRD_213400

Published ID: IJNRD2402073

DOI: Click Here to Get

Crusade Chiwalo

Data mining, student performance, instructional efficacy, resource allocation, Malawian universities, personalised learning, productive learning environment, data-driven, at-risk students, quality of education

By offering insightful information about student performance, instructional efficacy, and resource allocation, data mining tools have the potential to dramatically raise the standard of education in Malawian universities. Malawian universities may develop a more personalized, productive, and data-driven learning environment for all students by properly applying data mining. By offering insightful information about student performance, instructional efficacy, and resource allocation, data mining tools have the potential to dramatically raise the standard of education in Malawian universities. Malawian universities may develop a more personalized, productive, and data-driven learning environment for all students by properly applying data mining. A data mining framework for improving the quality of education in Malawian universities is proposed, consisting of data collection, data preprocessing, exploratory data analysis, feature engineering, model selection, model training, model evaluation, and deployment. Data that can be used for data mining in Malawian universities includes student demographic data, academic data, learning behavior data, assessment data, instructor data, and institutional data. Examples of data mining applications in Malawian universities include identifying at-risk students, personalizing learning experiences, predicting student performance, evaluating teaching effectiveness, and improving resource allocation. Data mining techniques have the potential to make a significant contribution to the improvement of the quality of education in Malawian universities. By effectively utilizing data mining, Malawian universities can create a more personalized, effective, and data-driven learning environment for all students.

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"UTILIZING DATA MINING TECHNIQUES TO IMPROVE THE QUALITY OF EDUCATION IN MALAWIAN UNIVERSITIES", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 2, page no.a647-a657, February-2024, Available :https://ijnrd.org/papers/IJNRD2402073.pdf

Volume 9 Issue 2, February-2024

Pages : a647-a657

Paper Reg. ID: IJNRD_213400

Published Paper Id: IJNRD2402073

Downloads: 000121193

Research Area: Computer Science & Technology 

Country: Mangochi, Malawi, Malawi

Published Paper PDF: https://ijnrd.org/papers/IJNRD2402073.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2402073

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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