Data Analysis

Globally, multilingual schools are becoming more prevalent. As a result, the study will focus on the use of English as a foreign language in Malaysian high schools, and its conclusions drawn from interview data collected for a qualitative study and a quantitative study involving Malaysian EFL students. The study utilizes a mixed technique in the first phase of the quantitative component, which includes both surveys and interviews (Omidire & Ayob, 2020).. Participants in the study will be 20 EFL teachers, and data will be gathered via an online platform (Ng & Lee, 2019). The interview transcripts will be imported into the Nvivo12 program for data analysis, which will then establish statistical values and tests based on thematic analysis. Research questions,

I. What types of Translanguaging practices are used to teach English as a Foreign language in Malaysian High-schools?

II. What are the teachers’ perceptions about using Translanguaging?

III.How do these practices influence the teaching environment of the Malaysian EFL learners?

will be reviewed as a means to ultimately identify themes to write up any patterns in the research journal.The study will employ descriptive statistics to determine the proportions of each Likert-type element in the survey and interviews to analyze the data obtained from the questionnaire.  To equalize the levels of all elements in the surveys and interviews, two scales from the survey and interviews' 5-point Likert-type will be lowered to three. Based on a 3-point Likert-type scale, the analysis was conducted. Structural coding will be utilized to examine the qualitative data acquired from the open-ended questions, participant observations, and semi-structured interviews. Moreover, the data will be independently coded with the study's questions in mind(Ting & Jintang, 2020). The codes will then be looked at again and related to themes regarding how English was utilized in the observed classrooms.

Furthermore, independent factors like gender, education, educational background, and education will require the usage of a regression model. By doing this, a function that explains the relationship between the independent variables and the target variable will be produced (Ng & Lee, 2019). The function can then be used to comprehend potential data patterns (Yuvayapan, 2019). During the data analysis step, the research created codes to identify the goals of translanguaging activities that reflect multicultural viewpoints.

Semi-structured interviews were conducted to ascertain the causes of the discrepancies between their perceptions and actual usage of English. Assessments were also conducted to ascertain the purposes for that they employ the use of English in their instruction (Ting & Jintang, 2020). The survey's Likert-style items were subjected to quantitative descriptive statistical analysis, while the information acquired from open-ended questions was subjected to structural-coding analysis. This was done to demonstrate how EFL teachers see their own techniques (Yuvayapan, 2019). Although they are expected to have favorable opinions about translanguaging in some specific circumstances, they do not usually use this approach because of different expectations

References

Ng, L., & Lee, S. (2019). Translanguaging practices and identity construction of Multilingual Malaysian University Graduates in Digital Media. English Teaching &Amp; Learning, 43(1), 105-123. https://doi.org/10.1007/s42321-019-00021-6

Omidire, M., & Ayob, S. (2020). The utilisation of translanguaging for learning and teaching in multilingual primary classrooms. Multilingua, 41(1), 105-129. https://doi.org/10.1515/multi-2020-0072

Ting, S., & Jintang, L. (2020). Teacher and students’ translanguaging practices in a Malaysian preschool. International Journal Of Early Years Education, 30(2), 261-275. https://doi.org/10.1080/09669760.2020.1850429

Yuvayapan, F. (2019). Translanguaging in EFL classrooms: Teachers’ perceptions and practices. Dil Ve Dilbilimi Çalışmaları Dergisi, 15(2), 678-694. https://doi.org/10.17263/jlls.586811