Madjid SADALLAH

Ph.D., Researcher - Engineer

Description

The Learning Data Lab (LDL) stands as an innovative initiative committed to revolutionizing educational experiences through the strategic use of learning analytics. Our dynamic team is dedicated to constructing a robust infrastructure capable of collecting, processing, and analyzing data from diverse sources, including MOOC platforms and institutional learning management systems. This initiative is driven by the goal of delivering actionable insights to educators and students, thereby enhancing the overall quality of learning outcomes.

Integration of ELK and Grafana for Comprehensive Data Visualization

As part of our commitment to cutting-edge analytics, the LDL project seamlessly integrates Elasticsearch, Logstash, and Kibana (ELK) stack, along with Grafana, to facilitate a comprehensive approach to data visualization. This amalgamation allows for a holistic view of educational data, which is sourced not only from ELK but also from MySQL and MongoDB databases. The data extraction process includes repositories from both FUN and edX, ensuring a diverse and comprehensive dataset.

Key Highlights of Data Visualization:

  • Kibana for Real-time Insights: Kibana plays a pivotal role in providing real-time insights into ELK-sourced data, enabling instantaneous identification of trends and patterns crucial for informed decision-making.

  • Grafana Dashboards for Enhanced Visualization: The utilization of Grafana enhances our visualization capabilities by creating dynamic and interactive dashboards. These dashboards provide stakeholders with a user-friendly interface to explore data from ELK, MySQL, and MongoDB seamlessly.

Data Extraction and Storage

The LDL project employs a sophisticated data extraction mechanism to pull relevant information from FUN and edX repositories. This data is then stored not only in ELK but also in MySQL and MongoDB databases, ensuring a comprehensive and accessible repository for analysis.

Predictive Learning Analytics (PLA) with ELK

The LDL project’s research component focuses on Predictive Learning Analytics (PLA), utilizing machine learning algorithms. ELK’s real-time search and analytics capabilities play a crucial role in enhancing our PLA efforts, providing deeper insights into student performance patterns.

In summary, the LDL project is at the forefront of leveraging ELK, Grafana, MySQL, and MongoDB to create a powerful analytics ecosystem. This approach ensures that educators and administrators have access to a rich set of tools for making informed decisions, implementing targeted interventions, and driving student success to new heights.