Fuzzy Logic Based Teaching/Learning of a Foreign Language in Multilingual Situations
The concept of Fuzzy Logic (FL) has gained momentum in areas of artificial intelligence and allied researches because of its absolute ability to present efficient solutions to real life problems. Contrary to the paradigmatic approach to the solutions of being either absolutely true or false [0 or 1] the fuzzy sets provide a range of possible outputs with error prone inputs which are vague and inaccurate using linguistic objects instead of mere mathematical numbers. A multilingual situation poses a similar challenge for a language teacher/learner where languages exist in continuum. Learners with heavy mother tongue influence tend to use their natural languages instinctively in a way that can create their own fuzzy rules to encounter the situation of being taught an entirely new language. A typical Indian language classroom is highly multilingual where scope of errors is numerous though they are ignored. This leads to stress both for the teachers as well as the learners making the classroom ambience more mechanistic than human. To combat such situations FL based Three-Phase Model of language teaching has been proposed which derives its basis on the presumption that the language instructor is aware of general rules of linguistics. An empirical longitudinal study on 150 undergraduate technical students designed on the proposed framework has been conducted to establish the efficiency and the success of the model. Observing language pedagogy through the lens of fuzzy logic and fuzzy thinking will not only make the classroom more real-like but it will also tap the pre-existing linguistic knowledge of the learners. Language interference will be more of a resource than a challenge.
Brown, H. D. (2001). Teaching by principles: An interactive approach to language pedagogy. Beijing: Foreign language Teaching and Research Press.
Challa, K. A. (2015). Fuzzy logic based approach for Computer Assisted English Learning in International Journal of Modern Engineering, 5(12), 66-70.
Davies, M., Hirschberg, J., Lye, J., Johnston, C., & McDonald, I. (2007). Systematic Influences on Teaching Evaluation: The Case for Caution. Australian Economic Papers, 46(1).
Fergusson, G. (1956). On transfer and the abilities of man. Canadian Journal of Psychology, 10, 121- 131.
Garcia-Honrado, I. (2013). Reflections on the teaching of Fuzzy Logic. 8th Conference of the European Society for Fuzzy Logic and Technology, 683-690.
Mamdani, E. (1974). Application of fuzzy algorithms for control of a simple dynamic plant. Proc. IEEE, 12, 1585-1588.
O'Grady, W., Dobrovolsky, M., & Aronoff, M. (1989). Contemporary linguistics: An introduction. New York: St. Martin's Press.
Piaget, J. (1962). The Psychology of the Child. New York: Basic Books.
Sinha, S. (2016). Differential approach to technology aided English language teaching: a case study in a multilingual setting. 18th International Conference on Applied Linguistics and Foreign language teaching. Hong Kong.
Sobrino, A. (2013). Fuzzy Logic and Education: Teaching the Basics of Fuzzy logic through an Example (by Way of Cycling). Education Sciences, 3(2), 75-97.
Spagnolo, F. (2003). Fuzzy logic, fuzzy thinking and the teaching/learning of mathematics in multicultural situations. Proceedings International Conference on Mathematics Education into the 21st Century (MEC21), (pp. 17-28). Brno.
Sugeno, M. & Murofushi, T. (1991). Helicopter flight control based on fuzzy logic. Proc. 1st International Fuzzy Engineering Symposium, (pp. 1120-1121). Yokohama, Japan.
Trillas, E., & Guadarrama, S. (2010). Fuzzy representations need careful design. International Journal of General Systems, 39(3), 329-346.
Voskoglou, M. (2011). Fuzzy Logic and Uncertainty in Mathematics Education. International Journal of Applications of Fuzzy Sets, 13, 45-64.
Voss, J. F. (1987). Learning and transfer in subject learning: a problem solving model. International Journal of Educational Research, 11, 607-622.
Zadeh, L. A. (1965). Fuzzy Sets. Information and Control (8), 338-353.
Zadeh, L. A. (1974). Fuzzy Logic and its Application to Approximate Reasoning. IFIP Congress (pp. 591-594). Atockhol, Sweden.
Copyright (c) 2017 Sweta Sinha
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors are confirming that they are the authors of the submitting article, which will be published online in journal Acta Linguistica Asiatica by Ljubljana University Press, Faculty of Arts (University of Ljubljana, Faculty of Arts, Aškerčeva 2, 1000 Ljubljana, Slovenia). Author’s name will be evident in the article in journal. All decisions regarding layout and distribution of the work are in hands of the publisher.
- Authors guarantee that the work is their own original creation and does not infringe any statutory or common-law copyright or any proprietary right of any third party. In case of claims by third parties, authors commit their self to defend the interests of the publisher, and shall cover any potential costs.
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.