Given the various differences between learners, teachers, and instructional methods in English Medium Instruction (EMI), a common purpose of EMI research involves investigating the potential variation between groups. The analysis of variance (ANOVA) test is a common technique used to address such a research aim, as it tests whether there are significant differences between the means of different groups. This chapter introduces the ANOVA test to readers by highlighting how it has been used in research within the field of EMI. To illustrate how different forms of the ANOVA test can be employed, the chapter then provides two case studies: (1) the use of a one-way between subjects ANOVA to examine the differences between three groups of students with respect to their perceptions of the role of English in their academic and career goals and comprehension level of EMI courses; and (2) the use of a mixed ANOVA in a quasi-experimental study that examined the differences in pre- and posttest writing performance and academic motivation of two groups provided with different types of feedback. Each of the case studies summarizes the assumptions required for the use of ANOVA, discusses potential problems that may face EMI researchers, and introduces alternative procedures.

To develop human capital in the globalized world, governments have implemented policies that require the teaching of some or all school subjects in English. However, the implementation of this policy has faced criticism and challenges in some countries where linguistic and cultural diversity is prevalent. These challenges include school segregation based on the medium of instruction, inadequate English proficiency of teachers and students and less interaction in English Medium of Instruction classrooms. Some researchers have investigated these challenges through international assessments such as the Programme for International Student Assessment and Trends in International Mathematics and Science Study. Others have examined EMI mathematics and science classrooms qualitatively through observations and interviews. These studies showed that teachers and students are more comfortable, and the classroom environment is more interactive when they use their mother tongue. In general, the findings favoured the mother tongue education for both cognitive and noncognitive variables. Researchers recommend either switching to EMI after achieving a certain level of English proficiency or providing language support for students who are already in EMI systems. Finally, a case study from Wales suggested that providing questions in both the mother tongue and English might mitigate unfair linguistic advantages in international assessments.

This chapter explores the design, development, and format of the Likert-type scales and response categories used in an online questionnaire for quantitative data collection for a recent empirical case study exploring attitudes, challenges, and perceptions of first-year undergraduate students at an English Medium Instruction (EMI) university in Hong Kong. Questionnaires are among the most widely used methods for research in the social sciences and can be an important and valuable source of data, which can be converted into measures of the numerous variables being examined. A variety of rating scale formats and designs with differing numbers of response categories and sequences are used in survey research. While researchers are typically confronted with a surplus of design and format choices, there is often little in terms of research, guidelines, or standards directing them toward which styles and formats to choose. Based on the survey design and development for this recent EMI-related study, and drawing from the literature, this chapter reviews how such choices and decisions were made, how the Likert-type scales were designed, and how these decisions may have influenced the overall success of the data collection and analysis. The case studies in Chapters 7, 8, and 11 of this book also adopt Likert-type scales in their questionnaire design, and these could be read together to supplement the understanding of the current chapter.

Questionnaire survey is among the main research instruments for data collection, where participants are required to respond by selecting from existing options or writing out answers. With the availability of easy-to-use online survey platforms that enhancing research efficiency in terms of time, cost, and access to participants, scholars have brought to bear a large number of questionnaire survey-based approaches to researching English Medium Instruction (EMI), putting stakeholders’ perspectives under the microscope. This chapter discusses how to plan and conduct a questionnaire survey study in EMI. Starting with the definition of questionnaire survey, this chapter centers on some key issues related to its use in EMI research, such as the selection of a sample frame, as well as design and distribution of questionnaire design. These issues are then exemplified in the subsequent case study of the acceptability and usefulness of collaborative writing activities in promoting university students’ online engagement.

The effect of English Medium Instruction (EMI) on language learning has been a classic and extensively discussed topic in EMI research, with various methods used to address it. One reliable method is corpus-based analysis, which provides quantitative evidence about the development of learners’ linguistic competence within an EMI context. This paper chapter aims to introduce the application of corpus-based analysis in EMI research through three tasks. Firstly, it summarizes relevant literature exploring the effects of EMI on English learning. Secondly, it elaborates on how to use corpus-based analysis to conduct relevant studies, including corpus construction, linguistic analysis instruments, and statistical analyses. Lastly, it presents an example study that demonstrates the value of corpus-based analysis in EMI research. The study examines learners’ longitudinal development of phraseological competences within an EMI course and explores the effect of textbook input on language learning. The data for the study consisted of learners’ written productions at three data collection times in the course. Learners’ phraseological competence was measured by eight measures targeting bi-grams’ and tri-grams’ complexity. The study found noticeable growth in learners’ phraseological competence with EMI education’s progression and similarities between high-frequency bi-grams and tri-grams in textbook input and learners’ written productions, proving the effect of the input on language learning.

Questionnaires have been widely used to tap into fine-grained themes of educational studies (see also Chapters 3, 8, and 11 of the this book). Unfitted use of parametric methods, however, would result in mistakenly interpreting ordinal scales as equal intervals, or difficulties in resolving issues such as missing raw data. Rasch measurement, as one of several item response theoretic models, is strongly suggested for application prior to the conduction of parametric statistical tests (Boone, Staver, & Yale, 2014).

This chapter starts with introducing basic facts about Rasch modelling, and discusses three study cases that applied Rasch modeling for scale development and validation.

In addition, this chapter features a step-by-step analysis procedure for data collected from a questionnaire, which is administered among 102 undergraduate students enrolled in a university located in Shanghai, China. All of the students have registered for at least one course instructed in English, which is related to their major area of study. The questionnaire was adapted from the Japanese English Medium of Instruction Attitude Scale (JEMIAS) (Curle, 2018). Multi-facet Rasch Measurement (MFRM) analysis was conducted to investigate the possible influence of students’ academic major on their attitude toward EMI, as well as the functioning of individual items on the scale. Analysis results show that students’ disciplinary background has limited influence on their attitudes. Items demonstrating different logit scales, however, provide practical implications for designing EMI courses in Chinese higher education institutions.

English Medium Instruction (EMI) researchers have called for studies that extend our understanding of EMI classroom discourse and the role of language in EMI in general (Dalton-Puffer & Smit, 2013; McKinley & Rose, 2022; Macaro, 2019). Corpus-based analytical frameworks are well-suited to analyze large amounts of naturally occurring language data and thus to provide reliable and verifiable findings about situationally defined language use such as language use in EMI contexts (see also Chapter 9, Author, this volume).

The primary goal of this chapter is to introduce the principles and practices of carrying out an additive multi-dimensional (MD) analysis (Biber, 1988; Berber Sardina et al., 2019) affording an empirically driven comprehensive linguistic analysis of variation in a register that could be applied to an EMI context. Our case study showcases the methodology using 500,000 words of text from the Singapore EMI corpus (SEMIC). Relying on the results of the MD analysis, this chapter also demonstrates how to identify text types via cluster analysis, which could provide additional information about classroom discourse. It will demonstrate show how these advanced quantitative analytical frameworks can be applied to analyze EMI classroom discourse. The chapter will also highlight practical aspects of MD analysis.

This chapter elaborates on ways of carrying out a comprehensive review based on searching the research literature systematically in the context of English Medium Instruction (EMI). Teaching content subjects in English is now a growing phenomenon around the world. Many researchers, teacher educators and teachers want to read and understand the latest findings of studies on EMI. A systematic review, which ‘systematically’ locates all relevant studies, evaluates these studies’ findings and synthesizes the findings that have implications for teaching and learning in EMI, can provide numerous benefits to researchers and writers. First, it draws readers’ attention to different findings about the same issues in the literature, such as the use of native languages (L1) in EMI classrooms, translanguaging pedagogy (i.e. refer to a pedagogical process of utilizing more than one language in a classroom) and learning in EMI. It can also indicate whether a consensus exists on effective ways of teaching and learning in EMI classrooms. A well-structured systematic review in which writers follow existing review protocols reduces the potential bias inherent in synthesizing research. For example, some of the standard procedures that are agreed on in the research community (e.g., PRISMA guidelines) include review teams having diversified research expertise, inter-rater reliability checking, rigorous screening procedures, data extraction, and assessment of the quality of studies. These procedures can largely eliminate bias and offer the EMI research community authoritative information about gaps in the research that need to be filled. By examining the evidence in the research, they can highlight conflicting views on the same teaching issues in the context of EMI. In this chapter, we use a case study that explores the teaching and learning issues encountered by teachers and students in EMI science classrooms, introducing different approaches to carrying out research reviews, particularly reviews that use quantitative approaches, such as systematic quantitative reviews and meta-analyses. We outline the key steps when conducting a systematic review: (1) formulating the topic; (2) locating and screening the literature; (3) evaluating the data; (4) extracting the data and assessing the study quality; (5) analyzing the data; (6) interpreting the results; (7) presenting the results; and (8) writing up the review. The implications and limitations of writing a systematic review in the EMI context are discussed.