EXPLORING THE IMPACT OF DATA MINING IN EDUCATION THROUGH A QUALITATIVE STUDY OF LEARNING PATTERNS

This qualitative research study delves into the transformative impact of data mining on educational practices and the identification of learning patterns within diverse educational contexts. As educational institutions increasingly integrate data mining techniques, it is essential to understand how these practices influence teaching methodologies, student engagement, and overall educational outcomes. This study employs a multiple case study design, utilizing semi-structured interviews, document analysis, and observational data from various educational institutions that have adopted educational data mining (EDM) systems. The research reveals several key themes regarding the integration of data mining into educational settings. First, educators reported significant enhancements in their teaching practices, facilitated by insights drawn from data analysis. These insights allow for the customization of instruction tailored to individual student needs, fostering a more personalized learning experience that enhances student engagement and retention. Additionally, the identification of learning patterns through data mining provides educators with a comprehensive understanding of student behaviors, enabling them to track progress, pinpoint at-risk students, and implement targeted interventions effectively. Another important finding of this study is the shift towards data-driven decision-making within educational institutions. Administrators leverage data mining to inform policy decisions, resource allocation, and curriculum design, leading to improved operational efficiency and accountability. However, the research also identifies several challenges and ethical considerations associated with the use of data mining in education. Concerns regarding data privacy, the potential for biased outcomes, and the complexity of data interpretation highlight the need for a careful and responsible approach to data mining practices. The study underscores the importance of ongoing professional development initiatives to equip educators with the necessary skills to interpret and utilize data insights effectively. Additionally, fostering a collaborative culture among educators, administrators, and data specialists is crucial for maximizing the benefits of data mining in educational settings. By contributing to the growing body of literature on educational data mining, this research provides valuable insights that can inform future policy and practice, ultimately enhancing the educational experience for students and educators alike.

Authors

Publication Details

Journal
Acta Electronica Malaysia
Published
2024-10-02
DOI
https://doi.org/10.26480/aem.02.2024.68.73
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

EXPLORING THE IMPACT OF DATA MINING IN EDUCATION THROUGH A QUALITATIVE STUDY OF LEARNING PATTERNS

Mubashshir Bin Mahbub
Acta Electronica Malaysia
Online Learning and Analytics
article

EXPLORING THE IMPACT OF DATA MINING IN EDUCATION THROUGH A QUALITATIVE STUDY OF LEARNING PATTERNS

Mubashshir Bin Mahbub
article en

Abstract

This qualitative research study delves into the transformative impact of data mining on educational practices and the identification of learning patterns within diverse educational contexts. As educational institutions increasingly integrate data mining techniques, it is essential to understand how these practices influence teaching methodologies, student engagement, and overall educational outcomes. This study employs a multiple case study design, utilizing semi-structured interviews, document analysis, and observational data from various educational institutions that have adopted educational data mining (EDM) systems. The research reveals several key themes regarding the integration of data mining into educational settings. First, educators reported significant enhancements in their teaching practices, facilitated by insights drawn from data analysis. These insights allow for the customization of instruction tailored to individual student needs, fostering a more personalized learning experience that enhances student engagement and retention. Additionally, the identification of learning patterns through data mining provides educators with a comprehensive understanding of student behaviors, enabling them to track progress, pinpoint at-risk students, and implement targeted interventions effectively. Another important finding of this study is the shift towards data-driven decision-making within educational institutions. Administrators leverage data mining to inform policy decisions, resource allocation, and curriculum design, leading to improved operational efficiency and accountability. However, the research also identifies several challenges and ethical considerations associated with the use of data mining in education. Concerns regarding data privacy, the potential for biased outcomes, and the complexity of data interpretation highlight the need for a careful and responsible approach to data mining practices. The study underscores the importance of ongoing professional development initiatives to equip educators with the necessary skills to interpret and utilize data insights effectively. Additionally, fostering a collaborative culture among educators, administrators, and data specialists is crucial for maximizing the benefits of data mining in educational settings. By contributing to the growing body of literature on educational data mining, this research provides valuable insights that can inform future policy and practice, ultimately enhancing the educational experience for students and educators alike.

Acta Electronica MalaysiaVol. 8(2)
Openalex Percentile: Top 71%
Online Learning and Analytics
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