A Neural Network Model of Students’ English Abilities Based on Their Affective Factors in   Learning

Fitra A. Bachtiar; Katsuari Kamei; Eric W. Cooper

doi:10.20965/jaciii.2012.p0375

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JACIII Vol.16 No.3 pp. 375-380

doi: 10.20965/jaciii.2012.p0375

(2012)

Paper:

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A Neural Network Model of Students’ English Abilities Based on Their Affective Factors in Learning

Fitra A. Bachtiar^*, Katsuari Kamei^, and Eric W. Cooper^

^*Graduate School of Science and Engineering, Ritsumeikan University, 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577, Japan

^**College of Information Science and Engineering, Ritsumeikan University, 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577, Japan

Received:

September 15, 2011

Accepted:

November 15, 2011

Published:

May 20, 2012

Keywords:

neural network, affective factors, English ability, estimation model

Abstract

The gap between teaching perspectives and students’ differences may impact negatively on teaching and learning effectiveness, indicating the need for a new approach for bridging this gap. The potentials of artificial neural networks for approximating extremely complex problems encouraged us to develop an estimation model of student English ability. The model was trained using a back propagation algorithm and tested using 154 samples from two universities. The model estimation rate related to student English ability demonstrated a high level of estimation by 93.34% for listening, 94.38% for reading, 94.90% for speaking, and 93.58% for writing.

Cite this article as:

F. Bachtiar, K. Kamei, and E. Cooper, “A Neural Network Model of Students’ English Abilities Based on Their Affective Factors in Learning,” J. Adv. Comput. Intell. Intell. Inform., Vol.16 No.3, pp. 375-380, 2012.

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References

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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

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[9] [9] M. Wei, “The Interrelatedness of Affective Factors in EFL Learning: An Examination of Motivational Patterns in Relation to Anxiety in China,” TESL-EJ, Vol.11, No.1, 2007.

[10] [10] C. Halpern, “An Investigation of Linguistic, Cognitive, and Affective Factors That Impact English Language Learners’ Performance on A State Standardized Reading Achievement Test,” Ph.D. thesis, College of Education at the University of Central Florida, 2009.

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[14] [14] R. Lippman, “An Introduction to Computing with Neural Nets,” Vol.4, IEEE Trans. ASSP Magazine, 1987.

[15] [15] B. Bloom, M. Engelhart, J. Edward, and H.W. D. Krathwohl, “Taxonomy of Educational Objectives, Handbook I: The Cognitive Domain,” Longmans, Green and Co. Ltd., London, 1956.

[16] [16] E. Horwitz, M. Horwitz, and J. Cope, “Foreign Classroom Anxiety,” The Modern Language Journal, Vol.70, No.2, 1986.

[17] [17] C. Bishop, “Neural Network for Pattern Recognition,” Oxford University Press, 1995.

[18] [18] D. George and P. Mallery, “SPSS for Windows step by step: a simple guide and reference 4th edition,” Allyn and Beacon, 2003.

[19] [19] D. Rumelhart, J. McClelland, and P. D. P Research Group, “Parallel Distributed Processing: Explorations in the Microstructure of Cognition,” Vols.1 and 2, MIT Press, 1986.

A Neural Network Model of Students’ English Abilities Based on Their Affective Factors in Learning

Fitra A. Bachtiar*, Katsuari Kamei**, and Eric W. Cooper**

Fitra A. Bachtiar^*, Katsuari Kamei^, and Eric W. Cooper^