Custom Reporting Framework for Moodle LMS Based E-Learning

Authors

  • B. Suraj Aravind Department of Computer Science and Engineering, GITAM Deemed to be University, Andhra Pradesh, India
  • Ankitha Vandana Department of Computer Science and Engineering, GITAM Deemed to be University, Andhra Pradesh, India
  • R. Bharath Kumar Reddy Department of Computer Science and Engineering, GITAM Deemed to be University, Andhra Pradesh, India
  • Sohan Patchigolla Department of Computer Science and Engineering, GITAM Deemed to be University, Andhra Pradesh, India
  • G. Harshitha Department of Computer Science and Engineering, GITAM Deemed to be University, Andhra Pradesh, India

DOI:

https://doi.org/10.51983/ajcst-2023.12.1.3521

Keywords:

Learning Management System, E-Learning, Analytics

Abstract

This paper aims to provide moodle LMS based instructors with real-time insights into their learner data. The project involves requirements analysis, design, data integration, user testing, deployment and evaluation, considering factors such as ease of use, data accuracy, and scalability. The framework is integrated with Moodle’s data sources to ensure that the reports generated are accurate and up to date. The framework will be tested with a sample group of moodle users to ensure it meets their reporting needs and requirements. Upon successful testing, the framework will be deployed on the moodle platform for all instructors to access. The framework is maintained to ensure it continues to work correctly and meets the evolving needs of moodle instructors. The framework’s effectiveness is evaluated, and any necessary improvements are made based on feedback from moodle instructors. This paper aims to provide moodle instructors with real-time insights into their data, making it easier for them to make informed decisions and monitor the progress of their e-learning courses.

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Published

03-04-2023

How to Cite

Suraj Aravind, B., Vandana, A., Bharath Kumar Reddy, R., Patchigolla, S., & Harshitha, G. (2023). Custom Reporting Framework for Moodle LMS Based E-Learning. Asian Journal of Computer Science and Technology, 12(1), 7–10. https://doi.org/10.51983/ajcst-2023.12.1.3521

Issue

Vol. 12 No. 1 (2023): January-June 2023

Section

Articles

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