Analyzing the Impact of Big Data on Curriculum Design and Student Performance in Secondary Education

Bigchanges are happening in the Education Sector particularly with Big Data Analytics in the digital era. The first Big Data study that investigates how big data influences curriculum development and performance of students in the context of secondary level education, and explores the significance of data-driven approaches in revolutionizing the pedagogical practices and performance of learners. Big data - a huge amount of structured and unstructured information - reveals insights about student behaviors, learning patterns, educational success, and social-emotional growth. When appropriately leveraged, this data enables educators and policymakers alike to develop adaptable curricula that supports diverse learners, and encourages personalized and equitable learning experiences. It delves in to the data drawn from myriad sources - digital learning platforms, student information systems, attendance data, assessments, social media, behavioral tracking tools. With predictive analytics and machine learning algorithms, educators can identify student strengths, weaknesses, and learning gaps in real time. This allows for timely interventions, differentiated instruction, and personalized learning experiences, leading to improved academic performance and greater engagement. The constant collection of data also enables a feedback loop dynamic, in which the contents of the curriculum can be revised and better adapted to fit both the subjects that are a mesh of future job market skills, as well as the skills laid out by the Casper Libero students. In addition to sizing up big data, the paper explores how it supports evidence-informed decision making in curriculum design. If used in the right way, educational institutes would have been using AI to collect historical and real-time data and search for the best teaching approaches/content delivery models for different cohorts of students. It provides perspective on how to transition toward a non-customized approach to curriculum that is adaptable, dynamic, and cultivates critical thinking, creativity, and problem-solving skills in students. And some also include how data analytics has uncovered trends that may have been previously unrecognized around dropout rates and absenteeism and even student mental health, allowing schools to take proactive steps to foster the overall well-being and retention of students. Although the implementation of Big Data in secondary education brings many advantages, this article critically assesses some potential downsides and ethical dilemmas.

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Published
2025-03-27
DOI
https://doi.org/10.1109/icfts62006.2025.11032025
Primary Topic
Technology and Data Analysis
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article
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article

Analyzing the Impact of Big Data on Curriculum Design and Student Performance in Secondary Education

Yousef Jaber Alawneh, Abdel Khaleq Issa
Technology and Data Analysis
article

Analyzing the Impact of Big Data on Curriculum Design and Student Performance in Secondary Education

Yousef Jaber Alawneh, Abdel Khaleq Issa
article en

Abstract

Bigchanges are happening in the Education Sector particularly with Big Data Analytics in the digital era. The first Big Data study that investigates how big data influences curriculum development and performance of students in the context of secondary level education, and explores the significance of data-driven approaches in revolutionizing the pedagogical practices and performance of learners. Big data - a huge amount of structured and unstructured information - reveals insights about student behaviors, learning patterns, educational success, and social-emotional growth. When appropriately leveraged, this data enables educators and policymakers alike to develop adaptable curricula that supports diverse learners, and encourages personalized and equitable learning experiences. It delves in to the data drawn from myriad sources - digital learning platforms, student information systems, attendance data, assessments, social media, behavioral tracking tools. With predictive analytics and machine learning algorithms, educators can identify student strengths, weaknesses, and learning gaps in real time. This allows for timely interventions, differentiated instruction, and personalized learning experiences, leading to improved academic performance and greater engagement. The constant collection of data also enables a feedback loop dynamic, in which the contents of the curriculum can be revised and better adapted to fit both the subjects that are a mesh of future job market skills, as well as the skills laid out by the Casper Libero students. In addition to sizing up big data, the paper explores how it supports evidence-informed decision making in curriculum design. If used in the right way, educational institutes would have been using AI to collect historical and real-time data and search for the best teaching approaches/content delivery models for different cohorts of students. It provides perspective on how to transition toward a non-customized approach to curriculum that is adaptable, dynamic, and cultivates critical thinking, creativity, and problem-solving skills in students. And some also include how data analytics has uncovered trends that may have been previously unrecognized around dropout rates and absenteeism and even student mental health, allowing schools to take proactive steps to foster the overall well-being and retention of students. Although the implementation of Big Data in secondary education brings many advantages, this article critically assesses some potential downsides and ethical dilemmas.

An-Najah National University (PS)
Quality Education
Openalex Percentile: Top 80%
Technology and Data Analysis
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