Description: The Learning Dashboard (LD) is a tool used in some software engineering courses at the Universitat Politècnica de Catalunya (UPC), where students develop projects in teams applying agile development practices. The LD supports both instructors and students by monitoring the development process of these projects by integrating data from multiple sources, such as Taiga, GitHub or Google Sheets, to compute and visualize metrics, factors, and indicators that provide insights into team performance, collaboration, and progress.

The goal of this Final Degree Project (TFG) is to refactor the data layer of the Learning Dashboard in order to increase its robustness and improve its maintainability. The project involves redesigning the data layer and the components who access them following software engineering best practices ensuring the consistency and reliability of the system.

Degree: GEI

Forms of collaboration: TFG

Contact: Marc Oriol

e-mail: marc.oriol@upc.edu

Description: The Learning Dashboard (LD) is a tool used in some software engineering courses at the Universitat Politècnica de Catalunya (UPC), where students develop projects in teams applying agile development practices. The LD supports both instructors and students by monitoring the development process of these projects by integrating data from multiple sources, such as Taiga, GitHub or Google Sheets, to compute and visualize metrics, factors, and indicators that provide insights into team performance, collaboration, and progress.

The goal of this project is to identify the most relevant metrics and indicators in agile software development according to the literature. This includes a comprehensive review of the literature and the implementation of the selected metrics within the Learning Dashboard, enabling more meaningful analysis and continuous improvement in agile project development.

Degree: MEI

Forms of collaboration: Master Thesis, I2R

Contact: Marc Oriol

e-mail: marc.oriol@upc.edu

Description: The Learning Dashboard (LD) is an analytics platform used in software engineering courses at the Universitat Politècnica de Catalunya (UPC) to monitor team-based development projects. LD integrates data from tools such as Taiga and GitHub and computes metrics that reflect team activity, collaboration patterns, and project progress. A customized version of Taiga—named LD@Taiga—has recently been developed to embed LD visualizations directly into the Taiga interface. This integration allows students to access project metrics from both GitHub and Taiga without leaving the project management environment. The current deployment focuses on the student view and supports project-level monitoring from a team perspective.

The goal is to design and implement the instructor-oriented version of LD@Taiga. This extended version should allow teachers to:

• Administer and configure the tool for their courses.

• Access consolidated dashboards with metrics for all the teams they supervise.

• Inspect project activity at different levels of granularity (course, team, and individual student).

• Manage permissions and control access to dashboards and data.

The student undertaking this project will analyze the current LD@Taiga implementation, identify the architectural and functional requirements for the instructor view, and implement the necessary backend and frontend extensions in accordance with software engineering best practices. The expected result is a robust, maintainable, and deployable extension of LD@Taiga that supports course-level oversight and simplifies instructional monitoring.

Degree: GEI

Forms of collaboration: TFG

Contact: Carles Farré

e-mail: carles.farre@upc.edu

Description: The Learning Dashboard (LD) is a platform that analyzes project data and provides metrics on activity, collaboration, and progress. Although it was created for educational use, its analytics are equally relevant in professional development environments. This TFG focuses on extending LD to work directly inside Jira, allowing developers to access project metrics without leaving their main project-management tool.

The goal is to design and implement a Jira-integrated version of LD, specifically targeting professional software teams. The student will:

• Adapt the current LD components to a Jira-based workflow.

• Integrate LD using Jira’s APIs or plugin framework.

• Provide developer-focused dashboards showing issue activity, workload patterns, and code metrics.

The expected outcome is a functional prototype that brings LD analytics into Jira in a usable, maintainable form.

Degree: GEI, MEI

Forms of collaboration: TFG, Master Thesis

Contact: Carles Farré

e-mail: carles.farre@upc.edu