Abstract
The success of new learning systems depends highly on their ability to adapt to the characteristics and needs of each student. QUESTOURnament is a competitive e-learning tool, which is being re-designed in order to turn it into an adaptive e-learning system, managing different contests adapted to the progress of the students. In this adaptation process, the first step is to design a mechanism that objectively estimates the difficulty level of the challenges proposed in this environment. The present paper describes the designed method, which uses a genetic algorithm in order to discover the characteristics of the answers to the questions corresponding to the different difficulty levels. The fitness function, which evaluates the quality of the different potential solutions, as well as other operators of the genetic algorithm are described. Finally, an experiment with a real data set is presented in order to show the performance of this approach.
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Verdú, E., Regueras, L.M., Verdú, M.J., de Castro, J.P. (2010). Estimating the Difficulty Level of the Challenges Proposed in a Competitive e-Learning Environment. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds) Trends in Applied Intelligent Systems. IEA/AIE 2010. Lecture Notes in Computer Science(), vol 6096. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13022-9_23
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