ISILA dataset
The data collected in the scope of the ISILA project has been curated and released as an open dataset on Zenodo so it can be reused by the learning analytics community. This dataset brings together learning activity data from multiple Learning Management Systems (LMSs)—including Canvas, Moodle, and LAMS—with complementary data collected through surveys and other […]
Presenting our paper at Koli Calling 2025
This week, ISILA team members Sonsoles López-Pernas and Mohammed Saqr participated in the Koli Calling 2025, celebrated every year in Koli National Park (Finland). We presented our research contribution titled “The dynamics of the self-regulation process in student-AI interactions: The case of problem-solving in programming education”. We modeled student-AI interaction when completing a web programming […]
Retrieving students’ ChatGPT interactions
The overarching goal of the ISILA project is improving teaching practices through innovative tools that provide real-time insights into student learning and engagement. With the rise of conversational AI tools like ChatGPT, educators now have access to powerful resources that can enrich the learning experience. However, effectively utilizing these tools requires efficient methods for collecting […]
Generating xAPI logs from tabular data: The csv2xAPI tool
Our solution to combine data from multiple sources in the scope of the ISILA project consists of a tool to convert from pretty much any CSV file (or other tabular format) to xAPI JSON logs that can be sent to a Learning Record Store. The tool that we have developed for this purpose is called […]
Data sources
The main goal of the ISILA project is to combine data from multiple sources to provide teachers with relevant information on their students, so they can make timely interventions to improve their learning. In the first stage of the project, each partner investigates which data sources are relevant to their own teaching implementations. Our first […]