1. bookVolume 115 (2018): Issue 4 (April 2018)
Journal Details
License
Format
Journal
eISSN
2353-737X
First Published
20 May 2020
Publication timeframe
1 time per year
Languages
English
access type Open Access

The Use of Genetic Algorithm to Optimize Quantitative Learner’s Motivation Model

Published Online: 21 May 2020
Volume & Issue: Volume 115 (2018) - Issue 4 (April 2018)
Page range: 189 - 194
Received: 09 Mar 2018
Journal Details
License
Format
Journal
eISSN
2353-737X
First Published
20 May 2020
Publication timeframe
1 time per year
Languages
English
Abstract

The paper presents a method of optimizing Quantitative Learner’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 student’s learning motivation.

Keywords

[1] Nobuta Y., Masui F., Ptaszynski M, Modeling Learning Motivation of Students Based on Analysis of Class Evaluation Questionnaire, Technical Transactions, 2-M/2015, 193–201.Search in Google Scholar

[2] Ekbal, A., Saha, S., Simultaneous feature and parameter selection using multiobjective optimization: application to named entity recognition International Journal of Machine Learning and Cybernetics, Volume 7, Issue 4, 2016, 597–611.10.1007/s13042-014-0268-7Search in Google Scholar

[3] Calkin S. Montereo, Araki K., Unsupervised language independent genetic algorithm approach to trivial dialogue phrase generation and evaluation. Lecture Notes in Computer Science, Springer, Berlin, Heidelberg, Vol. 4592, 2007, 388–394.Search in Google Scholar

[4] Manurung R., Ritchie G., Thompson H., Using Genetic Algorithms to Create Meaningful Poetic Text, Journal of Experimental & Theoretical Artificial Intelligence, Vol. 24, Issue 1, 2012, 43–64.10.1080/0952813X.2010.539029Search in Google Scholar

[5] Manurung H.M., An evolutionary algorithm approach to poetry generation, Doctoral Thesis, Institute for Communicating and Collaborative Systems, School of Informatics University of Edinburgh, 2003.Search in Google Scholar

[6] Araki K., Kuroda M., Generality of Spoken Dialogue System using SeGA-IL for Different Languages, Systems and Computers in Japan, Vol. 35, No. 12, 2004.Search in Google Scholar

[7] McIntyre N., Lapata M., Plot Induction and Evolutionary Search for Story Generation, Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, Stroudsburg, 2010, 1562–1572.Search in Google Scholar

[8] Goldberg D.E., Holland J.H.., Genetic algorithms and machine learning, Machine learning 3(2), 1988, 95–99.10.1023/A:1022602019183Search in Google Scholar

[9] Langdon WB, Poli R. Foundations of genetic programming, Springer, 2002.10.1007/978-3-662-04726-2Search in Google Scholar

[10] Melanie M. An introduction to genetic algorithms, Cambridge, Massachusetts London, England, Fifth printing 1999.Search in Google Scholar

[11] Ladd SR. Genetic algorithms in C++, Hungry Minds, Incorporated, 1995.Search in Google Scholar

[12] Deslauriers W.A., Asexual Versus Sexual Reproduction in Genetic Algorithms, Carleton University.Search in Google Scholar

[13] Wu Ch. H., Tzeng G.H., Goo Y.J., Fang W.C., A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy, Expert Systems with Applications, 2007, Vol. 32, Issue 2, 397–408.10.1016/j.eswa.2005.12.008Search in Google Scholar

[14] Keller J.M., Kopp T., Application of the ARCS model of motivational design, M. Reigluth (Ed.), Instructional theories in action: Lessons illustrating selected theories and models, Lawrence Erlbaum Associates, USA 1987.Search in Google Scholar

[15] Keller J.M., Suzuki K., Use of the ARCS motivation model in courseware design (Chapter 16), [in:] D.H. Jonnasen (Ed.), Instructional designs for microcomputer courseware, Lawrence Erlbaum Associates, USA 1988.Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo