Construction of mathematical models in language learning strategy and English proficiency of pre-university students

Johannah Jamalul Kiram (2016) Construction of mathematical models in language learning strategy and English proficiency of pre-university students. Masters thesis, Universiti Malaysia Sabah.

Construction of mathematical models.pdf

Download (14MB) | Preview


This study aims to construct the best mathematical model that describes the relationship between six Language Learning Strategies and English proficiency of the pre-university students of Universiti Malaysia Sabah. Two hundred and thirty pre-university students of Universiti Malaysia Sabah took part in this study by answering a background questionnaire and the Strategy Inventory for Language Learning self-report questionnaire. Also, these students sat for the Malaysian University English Test (MUET) and their results are taken as the student's proficiency in English as a second language. Three linear regression models was used as initial models, two of which went through stepwise variable selection method. However, in this study, we proposed two families of nonlinear models, which are the nonlinear Gompertz model, and a modified Gompertz model. Based on the five proposed models, the dependent variable, y, is the normalized English proficiency of the students and the independent variables, Xj , are the six different language learning strategies where j = 1,2,3, ... ,6. These six strategies are memory, cognitive, comprehensive, metacognitive, social and affective respectively. Goodness-of-fit tests and information criterion were used to assess these models, which are the root mean square error (RMSE), mean absolute error (MAE), residual standard error (RSE), the corrected Akaike information criterion (AlCe) and Bayesian information criterion (BIC). The results were then used to compare these models. The linear model showed good readings with its RMSE, MAE and RSE approaching zero indicating that the model is strong. However, the Gompertz model and the modified Gompertz model showed even better values of RMSE, MAE, RSE and AlCe. Especially for the modified Gompertz model, the values for the errors were even closer to zero. The goodness-of-fit tests and AlCc show that the modified Gompertz model's results were better than the nonlinear Gompertz model, and the linear regression model. Despite that, only the BIC calculated for the linear model M35 has the weightiest amount of information. In conclusion, four out of five metrics calculated suggested that the modified Gompertz model is the best amongst investigated models.

Item Type: Thesis (Masters)
Keyword: mathematical model, six Language Learning Strategies, English proficiency, pre-university students, MUET
Subjects: P Language and Literature > P Philology. Linguistics
Department: FACULTY > Faculty of Science and Natural Resources
Date Deposited: 27 Oct 2017 16:11
Last Modified: 27 Oct 2017 16:11

Actions (login required)

View Item View Item