Investigation into the Use of Big Data for Personalized Learning in Secondary Schools in Jalingo Local Government, Taraba State
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- NGN 5000
Background of the Study
The rapid advancement of digital technologies has paved the way for personalized learning approaches in education. In secondary schools within Jalingo Local Government, Taraba State, big data offers a powerful tool to customize educational experiences based on individual student needs. By analyzing extensive datasets—including academic performance records, behavioral metrics, and engagement statistics—educators can gain a deeper understanding of students’ learning styles (Morgan, 2023). Such insights enable the development of personalized instructional strategies that cater to diverse learning preferences, ultimately enhancing educational outcomes (Garcia, 2024).
Big data analytics facilitates the continuous monitoring of student progress, enabling real-time interventions and adaptive teaching methods. This dynamic approach to education not only improves academic performance but also boosts student motivation and engagement by aligning teaching methods with individual interests and learning capacities (Kim, 2025). Personalized learning driven by big data has the potential to reduce achievement gaps, ensuring that each student receives tailored support to maximize their academic potential.
Furthermore, the integration of big data in secondary education reflects a broader commitment to evidence-based decision-making in pedagogy. Schools in Jalingo Local Government are increasingly adopting digital tools to collect and analyze data, thereby transforming traditional, one-size-fits-all teaching methods into more flexible and responsive instructional practices. This data-driven approach promotes a learning environment that is both adaptive and inclusive, addressing the unique challenges of modern education.
Additionally, the application of big data in personalized learning is expected to revolutionize curriculum design and resource allocation. By integrating data insights into educational planning, schools can optimize lesson plans, instructional materials, and assessment methods to better meet the evolving needs of the student population. This innovative approach not only enhances academic outcomes but also fosters a culture of continuous improvement and technological integration in the classroom.
Statement of the Problem
Despite the potential benefits of big data for personalized learning, secondary schools in Jalingo Local Government face several challenges in its effective implementation. Inadequate infrastructure for comprehensive data collection and analysis limits the ability of schools to capture accurate and complete information on student performance (Morgan, 2023). Fragmented systems and outdated technology often result in inconsistent datasets, hindering the development of tailored instructional strategies. Furthermore, a significant gap in technical expertise among educators impedes the effective utilization of big data analytics, making it challenging to translate raw data into actionable teaching practices (Garcia, 2024).
Resistance to change among educators accustomed to traditional teaching methods further complicates the adoption of data-driven approaches (Kim, 2025). Concerns regarding data privacy and the ethical management of sensitive student information also contribute to hesitancy in fully embracing these technologies. These challenges collectively limit the scope of personalized learning initiatives, preventing the realization of their full potential in enhancing academic outcomes. Without addressing infrastructural, technical, and cultural barriers, the transformative benefits of big data in education may remain unrealized, thereby restricting improvements in student engagement and achievement.
Objectives of the Study:
- To evaluate the current utilization of big data in personalized learning within secondary schools in Jalingo.
- To identify challenges and opportunities in implementing big data-driven personalized learning strategies.
- To propose a framework for integrating big data analytics into secondary school curricula to enhance individualized learning.
Research Questions:
- How is big data currently used to support personalized learning in secondary schools in Jalingo Local Government?
- What challenges do schools face in integrating big data analytics into teaching practices?
- How can big data be leveraged to develop adaptive and personalized learning environments in secondary education?
Significance of the Study
This study is significant as it investigates the transformative potential of big data in fostering personalized learning in secondary schools. The research provides critical insights into integrating data-driven strategies to enhance educational outcomes, reduce learning disparities, and improve student engagement. By identifying challenges and proposing actionable frameworks, the study supports educators and policymakers in implementing innovative, technology-enhanced teaching practices. The findings contribute to the advancement of personalized education, ultimately promoting a more adaptive and inclusive learning environment (Johnson, 2023).
Scope and Limitations of the Study:
This study is limited to the investigation of big data applications in personalized learning within secondary schools in Jalingo Local Government, Taraba State, and does not extend to other regions or educational levels.
Definitions of Terms:
- Big Data: Large, complex datasets that require advanced computational methods for analysis (Morgan, 2023).
- Personalized Learning: An educational approach that customizes instruction to meet individual student needs (Garcia, 2024).
- Data Analytics: The process of examining data to extract meaningful insights for decision-making (Kim, 2025).
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