@article{oai:kitami-it.repo.nii.ac.jp:00008889,
author = {Lempa, Pawel and Ptaszynski, Michal and Masui, Fumito},
journal = {Czasopismo Techniczne, Technical Transactions},
month = {},
note = {The paper presents a method of optimizing Quantitative Learnerâ€™s Motivation Model with the use of genetic algorithm. It is focused on optimizing the formula for prediction of learning motivation by means of different weights for three values: interest, usefulness in the future and satisfaction. For the purpose of this optimization, we developed a C++ library that implements a genetic algorithm and an application in C# which uses that library with data acquired from questionnaires enquiring about those three elements. The results of the experiment showed improvement in the estimation of studentâ€™s learning motivation.},
pages = {189--194},
title = {The use of genetic algorithm to optimize quantitative learner's motivation model},
volume = {4},
year = {2018}
}