A Low-Code Approach for Developing Customizable Teacher Performance Analysis Dashboards for Moodle

Document Type : Research Article

Authors

Department of Software Engineering, University of Isfahan, Isfahan, Iran.

10.22108/jcs.2025.144824.1164

Abstract

Nowadays, analyzing teacher performance is crucial to improving instruction quality. Evaluating teachers can be effective in designing and delivering a course, managing the class, managing time, and supporting learners. Continuous teacher evaluation helps maintain high educational standards by ensuring that only qualified educators are recruited. In the current educational landscape, learning management systems (LMS) provide an environment for interaction and quality enhancement. Dashboards designed to analyze teacher performance in educational institutions can significantly aid in generating supervisory reports on course quality and improving teaching effectiveness. Additionally, various evaluation criteria—which may differ across institutions—can support these assessments. However, developing performance analysis dashboards for teachers is complex, requiring substantial time and financial investment. Existing research on such dashboards does not fully address the need for diverse dashboard types, highlighting the demand for a new solution.
This study employs a low-code development approach to create a customizable platform for teacher performance analysis dashboards in Moodle LMS, tailored to specific evaluation criteria. The platform categorizes teacher performance indicators using a feature model, streamlining dashboard development and reducing time and cost. Its modular architecture enables rapid assembly of dashboard components, while the feature model allows dynamic selection and configuration of relevant metrics. The study was evaluated in two phases. First, three case studies across different subjects were analyzed. Then, usability testing was conducted via an online workshop and questionnaire completed by school administrators and LMS experts. Results demonstrate faster dashboard development and high user satisfaction, confirming the platform’s effectiveness.

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Main Subjects

References

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Journal of Computing and Security
Volume 12, Issue 2 - Serial Number 2
September 2025
Pages 1-23

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History

  • Receive Date: 04 April 2025
  • Revise Date: 05 July 2025
  • Accept Date: 19 July 2025

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