GTM in new era: A reflection on its development and integration with other teaching methods

Issue 55, 2024

Wenyi Guan, Dan Hong, Lihua Zhao, Bermet Ibraeva, Bermet Ryskulova

Received 14.08.2023, Revised 05.11.2023, Accepted 24.01.2024

https://doi.org/10.54919/physics/55.2024.277ud7

Abstract

Relevance. The rapid development of information technologies and the changing educational needs of society require continuous improvement of teaching methods, making the examination of the grammar-translation method (GTM) and its integration with other approaches relevant. This allows identifying the strengths of this method and ways to optimise it in accordance with current challenges.

Purpose. The purpose of the study is to explore ways to integrate GTM with other teaching methods, such as the direct method, the audio-lingual method, and the Suggestopedia, to create more effective and comprehensive educational strategies.

Methodology. Conceptual modelling, synthesis, and comparison methods were used in the study.

Results. The results indicate the prospects of integrating various teaching methods, including GTM, with other approaches such as the direct method, the audio-lingual method, and the Suggestopedia. The study discovered that integrated teaching methods also contribute to actively engaging students in the learning process by stimulating them to work independently, conduct research, and exchange knowledge, thus creating a more dynamic and stimulating learning environment that promotes the development of not only knowledge but also the skills necessary for successful adaptation in modern information society. However, the study also demonstrated that for maximum effectiveness of such programmes, it is important to consider the individual characteristics and needs of each student, which will make the educational process more flexible and efficient, providing students with optimal conditions for learning and development.

Conclusions. The results of the study can be used to develop and improve educational programmes, adapt teaching methods to student needs, and optimise the learning process as a whole.

Keywords: live communication; grammar-translation method; online platforms; Suggestopedia; effective educational strategies

Suggested citation

Guan W, Hong D, Zhao L, Ibraeva B, Ryskulova B. GTM in new era: A reflection on its development and integration with other teaching methods. Sci Herald Uzhhorod Univ Ser Phys. 2024;(55):2777-2785. DOI: 10.54919/physics/55.2024.277ud7

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References

  1. Kinzheevа BS, Doroonova LN, Duishenova GE, Ailchieva AJ. Teaching students of a russian – Speaking audience to read and translate mass media materials. Bull Int Univ Kyrgyz Rep. 2021;43(2):218–23.
  2. Nurullaev HH. Psychology of teaching foreign languages in higher education: Modern approaches and guidelines. Central Asian Res J Interdiscip Stud. 2022;1:238–40.
  3. Mukanova ET. Pedagogical meaning of the concept of “multicultural competence” in teaching a foreign language at a university. Bull Osh State Univ. 2023;1:77-86. DOI: 10.52754/16948610_2023_1_10.
  4. Zharmatova EK. Issues of motivation of students to learning activities in higher school. Bull Osh State Univ. 2022;2:171–7. DOI: 10.52754/16947452_2022_2_171.
  5. Khalilova S. Importance of applying the Suggestopedia method to teach language to young learners. Mod Sci Res. 2024;3(1):1–3.
  6. Norton B, Toohey K. Identity, language learning, and social change. Lang Teach. 2011;44(4):412–46. DOI: 10.1017/S0261444811000309.
  7. Darvin R, Norton B. Investment and motivation in language learning: What’s the difference? Lang Teach. 2023;56(1):29–40. DOI: 10.1017/S0261444821000057.
  8. Akramy SA, Habibzada SA, Hashemi A. Afghan EFL teachers’ perceptions towards grammar-translation method (GTM). Cogent Educ. 2022;9(1):2125636. DOI: 10.1080/2331186X.2022.2127503.
  9. Akhunzhanova Zh. Formation of key competencies of college students on the English language lessons with the Kyrgyz language of study. Bull Kyrgyz Rep. 2020;2:9–17.
  10. Shopokova KSh. Theory and methods of teaching foreign languages. Bull Kyrgyz State Univ I Arabaev. 2019;1(S-2):177–80.
  11. Spahiu I, Kryeziu N. A contrastive study of grammar translation method and direct method in teaching of English language to primary school pupils. Linguist Cult Rev. 2021;5(S2):1022–9. DOI: 10.21744/lingcure.v5nS2.1663.
  12. Saidin S. A study of direct strategies of speaking learning used. J Appl Linguist Transl Lit. 2021;1(1):28–34. DOI: 10.33292/jalintrali.v1i1.56.
  13. Sidabutar U. The effect of the audio lingual method on students’ speaking achievement. Educ Light J. 2021;9(1):56–65. DOI: 10.36655/jsp.v9i1.537.
  14. Wullur A, Liando NVF, Rorimpandey R. Improving students’ motivation in studying English using audio-lingual method. J Engl Lang Lit Teach. 2023;5(1):19–30. DOI: 10.53682/jellt.v5i1.6832.
  15. Syarifuddin M, Muhlisin M, Thinh VT. Suggestopedia-based language learning to enhance students’ speaking skills viewed from teachers’ educational background. J Lang Lit Stud. 2022;2(1):12–22. DOI: 10.36312/jolls.v2i1.709.
  16. Talley PC, Tu H. A relative comparison made of two teaching methodologies: The examples of ‘Suggestopedia’ vs. total physical response. Int J Humanit Soc Sci. 2016;6(4):40–6.
  17. Cook V. Second language learning and language teaching. New York: Routledge; 2016. 344 p. DOI: 10.4324/9781315883113.
  18. Nunan D. Teaching English to speakers of other languages: An introduction. New York: Routledge; 2015. DOI: 10.4324/9781315740553.
  19. Ayu, M., Pratiwi ZF. The implementation of online learning in English language teaching during pandemic: The teachers voice. J Res Lang Educ. 2021;2(2):93–9. DOI: 10.33365/jorle.v2i2.1316.
  20. Mart CT. The audio-lingual method: An easy way of achieving speech. Int J Acad Res Bus Soc Sci. 2013;3(12):63–5. DOI: 10.6007/IJARBSS/v3-i12/412.
  21. Rotshtein AP, Rakytyanska HB. Diagnosis problem solving using fuzzy relations. IEEE Transact Fuzzy Syst. 2008;16(3):664–75. DOI: 10.1109/TFUZZ.2007.905908.
  22. Kvyetnyy RN, Romanyuk ON, Titarchuk EO, Gromaszek K, Mussabekov N. Usage of the hybrid encryption in a cloud instant messages exchange system. Proceed SPIE - Int Soc Optic Engin. 2016;10031:100314S. DOI: 10.1117/12.2249190.
  23. Rotshtein AP, Posner M, Rakytyanska HB. Cause and effect analysis by fuzzy relational equations and a genetic algorithm. Reliab Engin Syst Safety. 2006;91(9):1095–101. DOI: 10.1016/j.ress.2005.11.041.
  24. Yerzhanova AE, Kerimkhulle SY, Abdikerimova GB, Makhanov M, Beglerova ST, Taszhurekova ZK. Atmospheric correction of landsat-8 / Oli data using the flaash algorithm: Obtaining information about agricultural crops. J Theor Appl Inform Technol. 2021;99(13):3110–9.
  25. Kadirbayeva G, Chezhimbayeva K, Khizirova M, Wójcik W. Application of the method of measuring deformation parameters under mechanical action on concrete beams using a fiber bragg grating. East-Eur J Enterp Technol. 2023;4(7(124)):54–62. DOI: 10.15587/1729-4061.2023.285800.
  26. Zhetpisbayeva A, Khizirova M, Dostiyarova A, Zilgaraeva A, Kussambaeva N. Research of the simulated brillouin scattering in the single-mode fiber at wavelengths of 1, 31μm and 1, 55 μm for different modulation frequencies for different lengths of the optical fiber. Int J Appl Engin Res. 2016;11(3):1590–4.
  27. Kvyetnyy R, Bunyak Y, Sofina O, Kotyra A, Romaniuk RS, Tuleshova A. Blur recognition using second fundamental form of image surface. Proceed SPIE - Int Soc Optic Engin. 2015;9816:98161A. DOI: 10.1117/12.2229103.
  28. Kerimkhulle S, Saliyeva A, Makhazhanova U, Kerimkulov Z, Adalbek A, Taberkhan R. The input-output analysis for the wholesale and retail trade industry of the Kazakhstan statistics. E3S Web Conf. 2023;376:05023. DOI: 10.1051/e3sconf/202337605023.
  29. Kerimkhulle S, Baizakov N, Slanbekova A, Alimova Z, Azieva G, Koishybayeva M. The Kazakhstan Republic Economy Three Sectoral Model Inter-sectoral Linkages Resource Assessment. Lect Notes Networks Syst. 2022;502 LNNS:542–50.
  30. Rotshtein A. Design and tuning of fuzzy rule-based systems for medical diagnosis. In: Fuzzy and Neuro-Fuzzy Systems in Medicine (pp. 243–89). Boca Raton: CRC Press; 2017. DOI: 10.1201/9780203713419.
  31. Krasilenko VG, Nikolsky AI, Zaitsev AV, Voloshin VV. Optical pattern recognition algorithms on neural-logic equivalental models and demonstration of their prospectiveness and possible implementations. Proceed SPIE – Int Soc Optic Engin. 2001;4387:247–60. DOI: 10.1117/12.421146.
  32. Kerimkhulle S, Azieva G, Saliyeva A, Mukhanova A. Estimation of the volume of production of turbine vapor of a fuel boiler with stochastic exogenous factors. E3S Web Conf. 2022;339:02006. DOI: 10.1051/e3sconf/202233902006.
  33. Ushenko YA, Dubolazov AV, Karachevtcev AO, Zabolotna NI. A fractal and statistic analysis of Mueller-matrix images of phase inhomogeneous layers. Proceed SPIE - Int Soc Optic Engin. 2011;8134:81340P. DOI: 10.1117/12.891812.
  34. Faure E, Shcherba A, Lavdanskyi A, Makhynko M, Khizirova M. Three-Pass Protocol on Permutations: Implementation Example and Security. CEUR Workshop Proceed. 2024;3654:110–25.
  35. Khizirova MA, Chezhimbayeva KS, Mukhamejanova AD, Manbetova ZD, Ongar B. Using of virtual private network technology for signal transmission in corporate networks. News Nat Acad Sci Rep Kazakhstan, Ser Geol Techn Sci. 2021;3(447):100–3. DOI: 10.32014/2021.2518-170X.69.
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