Enhancing English Pronunciation Learning in Primary Education through Natural Language Processing: A Quantitative Study

Authors

  • Mishalini Chandran Faculty of Computing and Meta-Technology (FKMT), Sultan Idris Education University, Perak, Malaysia.
  • Shir Li Wang Faculty of Computing and Meta-Technology (FKMT), Sultan Idris Education University, Perak, Malaysia.
  • Sumayyah Dzulkifly Faculty of Computing and Meta-Technology (FKMT), Sultan Idris Education University, Perak, Malaysia.
  • Theam Foo Ng Centre for Global Sustainability Studies (CGSS), Universiti Sains Malaysia, Penang, Malaysia.
  • Amr S. Ghoneim Faculty of Computers and Artificial Intelligence, Helwan University, Helwan, Egypt.

DOI:

https://doi.org/10.37134/jictie.vol11.2.1.2024

Keywords:

natural language processing, English pronunciation learning, primary education, educational technology, randomised controlled trials

Abstract

Learning English pronunciation is crucial for primary school pupils to enhance their communication skills, yet many struggle. This study evaluates the effectiveness of a natural language processing (NLP) tool in improving English pronunciation among primary school pupils by measuring motivation, confidence, and performance. Conducted in a primary school in Johor, the research used a randomised controlled trial (RCT) design with 30 Year 3 pupils, divided into two groups of 15 each: control and treatment. The English teacher assessed motivation, confidence, and performance using a rubric-based evaluation, with a Cronbach’s Alpha value of 0.932, indicating high reliability. Paired t-tests were conducted to determine if the differences in motivation, confidence, and performance between the two groups were statistically significant. For motivation, t-values ranged from -1.871 to -1.468 for the traditional method and -6.548 to -13.229 for the NLP method. For confidence, t-values ranged from -1.871 to -1.468 for the traditional method and -11.500 to -7.135 for the NLP method. For performance, t-values ranged from -1.871 to -1.000 for the traditional method and -6.548 to -13.229 for the NLP method. With α = 0.05, the mean differences in motivation, confidence, and performance were significantly different for the NLP method (all p-values < 0.05) but not for the traditional method (all p-values > 0.05). High partial η² values, ranging from 0.474 to 0.827, suggest that the teaching methods account for a significant proportion of variance in the dependent variables. With α = 0.10, multivariate analysis of variance (MANOVA) assessed the effectiveness of the teaching methods. The combined dependent variables significantly differed based on teaching methods, Pillai Trace = 0.95, F(24, 5) = 3.72, p < 0.074, partial η² = 0.95. In conclusion, the study demonstrates that the NLP tool enhances English pronunciation learning by significantly improving motivation, confidence, and performance among Year 3 pupils.

Downloads

Download data is not yet available.

References

Abdullah, A. A., Awang, M. D., Kadir, M. N. A., Fadzil, A. F. M., & Hamzani, D. H. (2021). Ethics and civilization in Malaysian multiracial society. International Journal of Academic Research in Business and Social Sciences, 11(12). https://doi.org/10.6007/ijarbss/v11-i12/11940

Aithal, A., & Aithal, P. S. (2020). Development and validation of survey questionnaire and experimental data: A systematic review-based statistical approach. International Journal of Management, Technology, and Social Science, 5(2), 233–251.

Alhawiti, K. M. (2014). Natural language processing and its use in education. International Journal of Advanced Computer Science and Applications, 5(12). https://doi.org/10.14569/ijacsa.2014.051210

Andrade, C. (2021). The inconvenient truth about convenience and purposive samples. Indian Journal of Psychological Medicine, 43(1), 86–88.

Annamalai, N., Eltahir, M. E., Zyoud, S. H., Soundrarajan, D., Zakarneh, B., & Salhi, N. R. A. (2023). Exploring English language learning via Chabot: A case study from a self-determination theory perspective. Computers and Education Artificial Intelligence, 5, 100148. https://doi.org/10.1016/j.caeai.2023.100148

Azman, N. S., Rahmatullah, B., Tamrin, K. F., & Qahtan, Y. M. (2024). A preliminary study on tech-based health advisory online system: The case study of UPSI computing students. AIP Conference Proceedings, 2750, 040006. https://doi.org/10.1063/5.0148931

Bozkurt, A., & Ataizi, M. (2015). English 2.0: Learning and acquisition of English in the networked globe with a connectivist approach. Contemporary Educational Technology, 6(2), 155–168.

Devi, B., Khandelwal, B., & Das, M. (2017). Application of Bandura’s social cognitive theory in the technology-enhanced, blended learning environment. International Journal of Applied Research, 3(1), 721–724.

Dincer, A., & Yesilyurt, S. (2017). Motivation to speak English: A self-determination theory perspective. PASAA: Journal of Language Teaching and Learning in Thailand, 53, 1–25.

Gegenfurtner, A., & Ebner, C. (2019). Webinars in higher education and professional training: A meta-analysis and systematic review of randomized controlled trials. Educational Research Review, 28, 100293.

Goldie, J. G. S. (2016). Connectivism: A knowledge learning theory for the digital age. Medical Teacher, 38(10), 1064–1069.

Hasbullah, N. H., Rahmatullah, B., Mohamad Rasli, R., Khairudin, M., & Downing, K. (2022). Google Meet usage for continuity and sustainability of online education during pandemic. Journal of ICT in Education, 9(2), 46–60. https://doi.org/10.37134/jictie.vol9.2.4.2022

Liu, X., Xu, M., Li, M., Han, M., Chen, Z., Mo, Y., & Liu, M. (2019). Improving English pronunciation via automatic speech recognition technology. International Journal of Innovation and Learning, 25(2), 126. https://doi.org/10.1504/ijil.2019.097674

Manjarres-Posada, N., Onofre-Rodríguez, D. J., & Benavides-Torres, R. A. (2020). Social cognitive theory and health care: Analysis and evaluation. International Journal of Social Science Studies, 8, 132.

McNamara, D. S., Allen, L., Crossley, S., Dascalu, M., & Perret, C. A. (2017). Natural language processing and learning analytics. In C. Lang, G. Siemens, A. F. Wise, & D. Gasevic (Eds.), Handbook of learning analytics (pp. 93–104). Society for Learning Analytics Research.

Myles, F. (2017). Learning foreign languages in primary schools: Is younger better? Languages, Society & Policy. https://doi.org/10.17863/CAM.9784

Nasir, A. (2014). An analysis of relationship between English language anxiety, English language interest and English language achievement. Journal of Language and Linguistic Studies, 5(2), 78–90.

Nor, K. M., Razali, M. M., Talib, N., Ahmad, N., Sakarji, S. R., Saferdin, W. A. A. W., & Nor, A. M. (2019). Pupils’ problem in learning English as a second language among MDAB pupils at UITM Malacca. International Journal of Humanities, Philosophy, and Language, 2(7), 01–12.

Odom, S. L. (2021). Education of pupils with disabilities, science, and randomized controlled trials. Research and Practice for Persons with Severe Disabilities, 46(3), 132–145.

Pan, X. (2020). Technology acceptance, technological self-efficacy, and attitude toward technology-based self-directed learning: Learning motivation as a mediator. Frontiers in Psychology, 11, 564294.

Queirós, A., Faria, D., & Almeida, F. (2017). Strengths and limitations of qualitative and quantitative research methods. European Journal of Education Studies, 3(9), 369–387.

Radar, L., & Meunier, F. (2020). Text-to-speech and Dys Vocal tools: How can they enhance the reading skills of dyslexic pupils in L2? System, 91, 102264. https://doi.org/10.1016/j.system.2020.102264

Rahberdi, R., & Yusupovich, I. V. (2022). Problems in learning English in different classes in secondary schools. Thematics Journal of English Language Teaching, 6(1), 15–22.

Rahman, M. S. (2020). The advantages and disadvantages of using qualitative and quantitative approaches and methods in language “testing and assessment” research: A literature review. Journal of Education and Practice, 11(4), 110–119.

Ghafar, N. A., Rahmatullah, B., Razak, N. A., Muttallib, F. H. A., Adnan, M. H. M., & Sarah, L. L. (2023). Systematic literature review on digital courseware usage in Geography subjects for secondary school students. Journal of ICT in Education, 10(1), 26-39. https://doi.org/10.37134/jictie.vol10.1.3.2023

Reswari, G. P. A. (2018). English learning difficulties for multilingual pupils: A case study of an Indonesian pupil in learning English. Culturalistics: Journal of Cultural, Literary, and Linguistic Studies, 2(3), 56–65.

Rogers, J., & Revesz, A. (2020). Experimental and quasi-experimental designs. In Routledge Handbook of Research Methods in Applied Linguistics (pp. 164–176). Routledge.

Sa-ih, R. (2017). The problems faced by Thai pupils at University of Muhammadiyah Malang in learning speaking [Doctoral dissertation, University of Muhammadiyah Malang]. Universitas Muhammadiyah Malang Library. https://onesearch.id/Record/IOS4109.35797?widget=1&institution_id=136

Samuri, S.M., Abdul Ghani, H., Rahmatullah, B., & Ab Aziz, N. S. (2016). Sistem sokongan keputusan untuk menilai dan memantau prestasi guru: Kajian rintis di SMK Bachok, Kelantan. Journal of ICT in Education, 3, 55–72.

Santosa, J., Figueiredo, A. S., & Vieira, M. (2019). Innovative pedagogical practices in higher education: An integrative literature review. Nurse Education Today, 72, 12–17. https://doi.org/10.1016/j.nedt.2018.10.003

Supena, I., Darmuki, A., & Hariyadi, A. (2021). The influence of 4C (constructive, critical, creativity, collaborative) learning model on pupils' learning outcomes. International Journal of Instruction, 14(3), 873–892.

Taherdoost, H. (2016). Sampling methods in research methodology: How to choose a sampling technique for research. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3205035

Tyagi, G., & Singh, R. (2019, March). Implementing CALL system using natural language processing tools. In Proceedings of 2nd International Conference on Advanced Computing and Software Engineering (ICACSE).

Yuliani, S., Khulaifiyah, K., & Idayani, A. (2023). Investigating pupils’ motivation on the use of Rosetta Stone in learning English pronunciation. AL-ISHLAH Jurnal Pendidikan, 15(2), 2433–2440. https://doi.org/10.35445/alishlah.v15i2.3160

Zhang, A., Olelewe, C. J., Orji, C. T., Ibezim, N. E., Sunday, N. H., Obichukwu, P. U., & Okanazu, O. O. (2020). Effects of innovative and traditional teaching methods on technical college pupils’ achievement in computer craft practices. SAGE Open, 10(4), 2158244020982986.

Zhou, Y. (2020). The influence of family on children’s second language learning. Journal of Language Teaching and Research, 11(4), 599–605. https://doi.org/10.17507/jltr.1104.06

Zolkipli, N. Z., Rahmatullah, B., Samuri, S. M., Árva, V., & Pranoto, Y. K. S. (2023). ‘Leave no one behind’: A systematic literature review on game-based learning courseware for preschool children with learning disabilities. Southeast Asia Early Childhood Journal, 12(1), 79–97. https://doi.org/10.37134/saecj.vol12.1.7.2023

Downloads

Published

2024-10-15

How to Cite

Chandran, M., Wang, S. L., Dzulkifly, S., Ng, T. F., & Ghoneim, A. S. (2024). Enhancing English Pronunciation Learning in Primary Education through Natural Language Processing: A Quantitative Study. Journal of ICT in Education, 11(2), 1–17. https://doi.org/10.37134/jictie.vol11.2.1.2024