Optimization of Language Learning with TOPSIS
محورهای موضوعی : Numerical Analysis
1 - دانشگاه کبک در مونترال
کلید واژه: fuzzy logic, Optimization, TOPSIS, language learning, automated decision-making,
چکیده مقاله :
The present study focuses on the application of fuzzy sets in the optimization of language learning with TOPSIS. The appropriate consideration of the candidates’ characteristics is an important issue which can affect their language learning. Motivation, learner strategies, perseverance and age are the factors that affect language learning. The hypothesis in this paper was that the difference in the consideration of these factors can affect the individuals’ language learning. In this study, for the first time, the analysis of the candidates’ characteristics of two age categories was performed for the investigation of their impact on language learning. The purpose of this work was to analyze the candidates’ characteristics on the individuals’ language learning. The analysis with a decision making algorithm, TOPSIS, revealed the efficiency of this method. One of the advantages of this study was that the effect of different characteristics of the category members on the categories confusion has made the prediction for the optimization of language learning possible. Another advantage was that the modification of the TOPSIS method with the application of fuzzy disjunction has been efficient to provide an automated decision-making tool for this analysis. The results presented in this paper could be used for the development of algorithms and linguistic tools for the optimization of language learning with artificial intelligence.
The present study focuses on the application of fuzzy sets in the optimization of language learning with TOPSIS. The appropriate consideration of the candidates’ characteristics is an important issue which can affect their language learning. Motivation, learner strategies, perseverance and age are the factors that affect language learning. The hypothesis in this paper was that the difference in the consideration of these factors can affect the individuals’ language learning. In this study, for the first time, the analysis of the candidates’ characteristics of two age categories was performed for the investigation of their impact on language learning. The purpose of this work was to analyze the candidates’ characteristics on the individuals’ language learning. The analysis with a decision making algorithm, TOPSIS, revealed the efficiency of this method. One of the advantages of this study was that the effect of different characteristics of the category members on the categories confusion has made the prediction for the optimization of language learning possible. Another advantage was that the modification of the TOPSIS method with the application of fuzzy disjunction has been efficient to provide an automated decision-making tool for this analysis. The results presented in this paper could be used for the development of algorithms and linguistic tools for the optimization of language learning with artificial intelligence.
