Vol. 20 / 2025 – International Conference on Virtual Learning
Model for rapid assessment of engagement in academic courses using genetic algorithms
Ion Alexandru POPESCU, Nicolae BOLD
This paper presents a model for rapid assessment of fundamental notions from an academic course and its implementation using the Python language. The model has two types of users: professor and student. The professor can enter test items along with answer options, and students must respond in a limited time to a test generated using genetic algorithms. The items are stored in a database to be used as a starting point for the test generator. To avoid the similarity of the tests, the items and answer options are permuted, thus obtaining results that correctly and impartially reflect the engagement in the course
Keywords:
modelling,
test,
algorithm,
interfaces,
database,
learning
CITE THIS PAPER AS:
Ion Alexandru POPESCU,
Nicolae BOLD,
"Model for rapid assessment of engagement in academic courses using genetic algorithms",
International Conference on Virtual Learning,
ISSN 2971-9291, ISSN-L 1844-8933,
vol. 20,
pp. 309-318,
2025.
https://doi.org/10.58503/icvl-v20y202526