This OptLearn algorithm is an improved and advanced version of the UMA implementation, which integrates a recommender system using the Surprise module. This version allows loading and consolidating data from various sources, such as a file with the details of the questions clustering (provided by IPB in this case), into structured DataFrames, and the generation of a rating dataset for analysis and recommendation, with a focus on optimizing the learning experience through personalized question recommendations, while also keeping extensibility in mind. The code has been improved and the main recommender system algorithms have been upgraded to improve performance.

Fuster-López, A. and Nowak, I. "iMath Project - Optlearn Algorithm (HAW Hamburg)", 2024. Available at https://github.com/aipereira/iMath_Public/tree/main/Algorithms_and_reports/HAMBURG

Alejandro Fuster López

University of Malaga