On 19 September 2024, at the 35th Conference on Information and Intelligent Systems, organized by the University of Zagreb's Faculty of Organization and Informatics in Varaždin, members of the LA Lab presented two research papers. The papers were part of the section on Learning Analytics, AI and Technologies in Education.

The paper entitled Prioritizing Learning Outcomes in Different Learning Design Contexts by Blaženka Divjak, Barbi Svetec, Bart Rienties, Paul Astles, Catriona Matthews, Alexander Tillmann, Michael Eichhorn, Julia Schmitt explores possible approaches to the prioritization of learning outcomes, while considering the complexity of different learning contexts and the influence of learning programs on learning paths. The paper is available here: https://archive.ceciis.foi.hr/public/conferences/2024/Proceedings/S7/S7P6.pdf

The paper entitled Predicting the Outcomes of PBL: Comparison of Two Methods by Barbi Svetec, Blaženka Divjak, Damir Horvat, Katarina Pažur compares Random Forest and Decision Trees algorithms in the development of predictive learning analytics models for problem- and project-based learning (PBL) and can be found here: https://archive.ceciis.foi.hr/app/public/conferences/2024/Proceedings/S7/S7P5.pdf 

The research was done with the support of internationally-oriented projects, namely, Erasmus+ project Innovating Learning Design in Higher Education (iLed) and the Croatian Science Foundation project Trustworthy Learning Analytics and Artificial Intelligence for Sound Learning Design (TRUELA).