An extension to previous studies, the model comparison of all five models whereby the consideration of nonlinear models, specifically Gompertz model and Modified Gompertz model, were fit into the social data of Language Learning Strategies (LLS) as its independent variables and its dependent variable, Language Proficiency. A self-report questionnaire called the Strategy inventory for language learning (SILL) was administered to two hundred and thirty pre-university students of Universiti Malaysia Sabah, and their language proficiency was measured using the Malaysian University English Test (MUET). A comparison analysis was done between the three best linear models and the two nonlinear models using these goodness of fit tests and information criterions; root mean square error (RMSE), mean absolute error (MAE), residual standard error (RSE), corrected Akaike’s information criterion (AICC) and Bayesian Information Criterion (BIC).
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4 December 2019
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICAL SCIENCES AND TECHNOLOGY 2018 (MATHTECH2018): Innovative Technologies for Mathematics & Mathematics for Technological Innovation
10–12 December 2018
Penang, Malaysia
Research Article|
December 04 2019
Comparison analysis between linear and nonlinear models to predict language proficiency in proportion to language learning strategy
J. J. Kiram;
J. J. Kiram
a)
1
Preparatory Centre for Science and Technology, Universiti Malaysia Sabah
, 88400 Kota Kinabalu, Sabah, Malaysia
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J. Sulaiman;
J. Sulaiman
b)
2
Faculty of Science and Natural Resources, Universiti Malaysia Sabah
, 88400 Kota Kinabalu, Sabah, Malaysia
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S. Swanto;
S. Swanto
c)
3
Faculty of Psychology and Education, Universiti Malaysia Sabah
, 88400 Kota Kinabalu, Sabah, Malaysia
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AIP Conf. Proc. 2184, 050003 (2019)
Citation
J. J. Kiram, J. Sulaiman, S. Swanto, W. A. Din; Comparison analysis between linear and nonlinear models to predict language proficiency in proportion to language learning strategy. AIP Conf. Proc. 4 December 2019; 2184 (1): 050003. https://doi.org/10.1063/1.5136391
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