Success factors for English as a second language university students’ attainment in academic English language proficiency: exploring the roles of secondary school medium-of-instruction, motivation and language learning strategies

2.1 The impact of medium-of-instruction in secondary education on university students’ academic English proficiency

Recent research has expressed the concerns that students from secondary schools which adopt mother tongue medium-of-instruction have lower academic English language proficiency than those from EMI schools (e.g. Evans and Morrison 2018; Lin and Morrison 2010). This has important implications for university EMI education since research studies have found that students’ secondary school background is one of the substantial sources of difficulty for students in learning content subjects and developing academic English proficiency in EMI university settings (Aizawa and Rose 2020). Lin and Morrison (2010) examine the impact of medium-of-instruction in secondary school education on university students’ size of academic vocabulary. Seven hundred and sixty two undergraduates at the HK Polytechnic University take a vocabulary levels test for measuring their receptive vocabulary size. Four hundred and thirteen of them write an argumentative essay after the tests for evaluating their productive vocabulary knowledge. The findings indicate that first-year undergraduates from EMI secondary schools in HK have significantly larger receptive and productive vocabularies than those from Chinese-Medium-Instruction (CMI) schools. It is suggested that EMI secondary schools offer students more exposure to English academic vocabulary which allows them to employ more academic words in the written work and produce quality academic texts for their tertiary assessments.

Evans and Morrison (2018) conduct a follow-up study and they compare the university experiences of first-year undergraduates who graduated from HK’s CMI and EMI secondary schools when adjusting to the academic and linguistic demands of EMI education at the university level. The authors carry out a large-scale questionnaire (n = 828) and the findings reveal that undergraduates from CMI schools enrol into university with lower academic English proficiency in comparison to the undergraduates who graduated from EMI schools. During the semi-structured interviews, some of the EMI graduates mention that they adjust to the language demand of university study fairly easy as they have been studying academic subjects in English since year 7. The authors argue that the secondary school medium-of-instruction plays an important role in determining the students’ speed and ease of adjustment to EMI university study. Nevertheless, the findings of the study rely on students’ self-assessment of academic skills, which include academic reading, writing, speaking and listening. To date, there are limited research studies (Aizawa and Rose 2020; Evans and Morrison 2018; Lin and Morrison 2010) which investigate the influence of school background on students’ English language ability at university. Hence, one of the aims of the current study is to explore whether the impact of secondary school medium-of-instruction is a crucial factor in predicting the undergraduates’ academic English language performance at the university level.

2.2 The impact of university’s EMI policy on English language learning

Most of the studies in the field of EMI conceptualise success in EMI through investigating students’ mastery of academic knowledge. Researchers (e.g. Airey 2012; Li 2018; Rose et al. 2019; Thompson et al. 2022) typically use students’ academic results in the EMI courses in order to evaluate the learner’s success in EMI. A small number of studies have investigated the effects of EMI instruction in university settings on students’ English L2 proficiency (e.g. Hu et al. 2014; Rogier 2012; Yang 2015). Yang (2015) examines 29 Taiwanese learners’ English proficiency in an EMI tourism classroom at a Taiwanese university longitudinally over two years. These learners’ English proficiency levels are measured by conducting pre-tests immediately after entering the programme and post-tests after two years. The tests were developed based on the national General English Proficiency Test, a locally-developed English proficiency test in Taiwan. The results show that after two years of studying the EMI programme, the learners make significant improvements in their reading and listening skills in the post-tests. Nevertheless, since Yang only evaluates learners’ productive skills during the post-tests but not the pre-tests, Yang is not able to evaluate the effectiveness of the EMI programme in improving learners’ productive skills. Moreover, as Yang’s study does not have a control group that received non-EMI education, this study is not able to establish a relationship between EMI education and the development of learners’ English proficiency.

On the other hand, Lei and Hu (2014) investigate whether the EMI programme at a Chinese university has an effect on Chinese undergraduate students’ English proficiency. The authors conduct a direct comparison group in China and the authors use two national tests: the National Matriculation English Test and the College English Test. The authors have found similar English proficiency gains on two proficiency tests amongst EMI students and those studying in a CMI programme while taking general English language classes. Additionally, the student’s perceptions of EMI programmes and prior English proficiency have significant effects on the outcome measures. The authors argue that there is a lack of evidence which suggests that EMI can lead to better English language learning. Nevertheless, the authors also point out that it is possible the university’s EMI programme has suffered from several issues, including a mismatch between the programme goals and actual pedagogical practice and inadequate command of English as the language of instruction for teaching and learning. Moreover, the outcome measure is evaluated by general English proficiency tests which do not evaluate subject-specific English skills that students have acquired in the EMI programme.

A study which measures EMI students’ academic English proficiency by using a standardised English test (International English Language Testing Service, IELTS) is conducted by Rogier (2012). Rogier aims to investigate the extent to which undergraduates’ academic English proficiency will improve after studying for a four-year undergraduate degree through EMI. The findings demonstrate that there is a statistically significant score gain in all English language skills areas (i.e. reading, writing, listening and speaking). Particularly, students’ largest gains are in the area of speaking, followed by reading. Rogier’s study does not have a direct comparison group, but she compares the results with studies of general English programmes (e.g. Elder and O’Loughlin 2003). Rogier justifies that EMI students can move up to one-half of an IELTS band in four years. However, such a finding shows that EMI instruction may not enable students to achieve a huge improvement in their academic English proficiency.

Based on the small body of studies that have assessed measured academic English language gains in EMI university settings, it is shown that the evidence is not positive (Macaro et al. 2018). This means that there are potentially other variables that may influence students’ English language proficiency. This study aims to address the research gap by investigating whether a university’s medium-of-instruction policy (Chinese Medium Instruction and English Medium Instruction policies) can predict students’ success in English L2 learning at a Hong Kong bilingual university. In the following sections, we will explore how students’ motivation and their use of language learning strategies can predict successful English learning.

2.3 Language learning motivation

Success in English language learning can be influenced by student motivation. Motivation research has a strong history in the field of applied linguistics, and it has been conceptualised within different frameworks over the past decades (e.g. Deci and Ryan 2002; Dörnyei and Ryan 2015) with Deci and Ryan’s self-determination theory being one of the prevailing frameworks. Self-determination theory hypothesises that individuals have an ability to self-regulate their behaviour and engage in intellectual growth with others. The theory conceptualises motivation as intrinsic and extrinsic (Deci and Ryan 2002; Ryan and Deci 2000, 2002). Extrinsic motivation represents the practical benefits of L2 proficiency. The perceived usefulness of L2 proficiency provides the driving force (Csizér and Dörnyei 2005), such as job prospects, good salaries, immigration and travelling. On the other hand, intrinsic motivation triggers ‘internally rewarding consequences’, including the ‘feeling of competence and self-determination’ (Deci 1975: 23). When individuals are intrinsically motivated, they may engage in activities because of the challenge, enjoyment, interest, personal enrichment and self-determination needs, rather than money, recognition and competition (Amabile et al. 1994). As Deci and Ryan (2002) argue, the three psychological needs (i.e. the need for autonomy, competence and relatedness) are necessary for a person’s motivation and well-being. Research studies in L2 acquisition and EMI have employed self-determining theory to understand the development of and decline in student’s motivation in L2 English learning as well as learning content subjects through English as an L2 (e.g. Hiromori 2003; Kojima 2021; Kojima and Yashima 2017). This implies that Deci and Ryan’s theory can be a useful framework for exploring students’ language learning motivation.

In order to maintain learners’ language learning motivation, ‘motivation must emanate from the learners rather than be externally regulated by teachers’, and ‘learners must see themselves as agents of the processes that shape their motivation’ (Ushioda 2008: 30). In a questionnaire survey of 524 first-year students at the HK Polytechnic University, Lin and Detaramani (1998) find that intrinsic motivation is positively related to higher English attainment. However, the result shows that extrinsic motivation is not positively related to high English attainment. In Gan’s (2003) case study, all successful EFL university students report having a fondness for English since secondary school. Unlike less successful students, none of them feels that they are forced to learn English. In the light of this finding, it is suggested that intrinsic motivation is a powerful factor contributing to a higher level of English proficiency. It is suggested that students with higher extrinsic motivation tend to attach higher priority to working experience rather than English attainment.

Recent studies have demonstrated that students enrol in EMI courses at the university level for various reasons. One of the most common goals is to enhance their English proficiency levels (e.g. Jiang et al. 2019; Kojima and Yashima 2017) and simultaneously learn the relevant academic subject knowledge (Rose et al. 2019). Other motivators include enhancing future job opportunities (e.g. Iwaniec and Wang 2021; Macaro and Akincioglu 2018), opportunities for contact with the international community (e.g. Macaro and Akincioglu 2018) and the prestige related to learning English as a global language (e.g. Uçar and Soruç 2018). These findings have revealed that students’ motivations are diverse and there is a need for research studies to consider different factors that shape the influence of EMI on students’ language learning motivation.

2.4 Language learning strategies

L2 Learning strategies are techniques that students apply to enhance the effectiveness of their learning (Dörnyei 2001; Zhou and Rose 2021). Students make use of resources and materials to take responsibility for their own language learning. Following a series of empirical studies on strategy use by L2 students, O’Malley and Chamot (1990) classify strategies into three groups: cognitive, metacognitive and social-affective. They state that cognitive strategies “operate directly on incoming information, manipulating it in ways that enhance learning” (O’Malley and Chamot 1990: 44). They are therefore related closely to the processing of language, for example, inferencing, deductive reasoning and translation strategies. Metacognitive strategies, on the other hand, “involve thinking about the learning process, planning for learning, monitoring of comprehension or production while it is taking place, and self-evaluation after the learning activity has been completed” (O’Malley and Chamot 1990: 8). Students can be aware of the content to be learned, and awareness of one’s motives, what the task requires and whether they can meet those requirements (Biggs 1984). The final category described by O’Malley and Chamot (1990), is that of social-affective strategies which are defined as “either interaction with another person or ideational control over affect” (p. 45). The affective strategies are linked with motivation and attitudes, whereas the social strategies could take the form of questioning for clarification, cooperation with others, or creating opportunities for practice by seeking out native speakers.

A contemporary taxonomy of language learning strategies is developed by Oxford (1990). Oxford (1990) compiles a list of 62 language learning strategies which are divided into two main groups: direct and indirect strategies. The direct strategies involve direct manipulation of the target language and are further divided into mnemonic, cognitive and compensatory strategies. The second main group is that of indirect strategies, which are further sub-divided into metacognitive, affective and social. A lot of the examples of metacognitive strategies coincide with those of O’Malley and Chamot, focusing on organisation, planning and evaluation of learning. This study adopts Oxford’s taxonomy (1990) for classifying the students’ use of L2 learning strategies that are reported in the questionnaire and student interview data. Such a taxonomy has been used in much research on L2 learning strategies (e.g. Oxford and Burry-Stock 1995; Peacock 2001; Peacock and Ho 2003). Although the Strategy Inventory for Language Learning (SILL), developed by Oxford (1990), has been much criticised for its parametric measure issue, it can be argued that SILL still remains a useful instrument in L2 learning strategy research. Amerstorfer’s review of the literature (2018) reiterates that ‘the utility and reliability of SILL are both high’ (p. 504). Moreover, it is indicated that SILL has high content validity, high predictive validity and high concurrent validity (see Amerstorfer 2018 for further details).

3.1 Setting

The study was carried out at The Chinese University of Hong Kong (CUHK), a government-funded university in HK. Founded in 1963, the university is unique in that the use of Chinese as the principal language of instruction is conceived in the university’s ordinance. It was established to provide education to Chinese middle school leavers for post-secondary education, particularly those who were arrivals from mainland China seeking refuge in HK in the late 1950s. The university has now evolved into a comprehensive university which offers a variety of disciplinary and interdisciplinary undergraduate and postgraduate degree programmes. The university is the only university in HK which adopts a bilingual policy, which allows academic departments to decide the medium-of-instruction for their courses. The courses are either taught in English and/or Chinese. According to the report produced by the university’s committee on bilingualism (2007), the report recommends that ‘depending on the nature of the academic subject, the language used at lectures should be set by the boards of various departments’ (clause 14). The academic departments have the flexibility to decide on the medium-of-instruction for lectures and they need to take into account other factors including ‘the language habits, the linguistic competence and the cultural background of the students and teachers, and have consulted the teachers concerned’ (clause 15).

All undergraduates are required to achieve an IELTS equivalent score of 6.0 as the minimum English language required for admission. Undergraduates at the university are required to fulfil the English language requirements by taking the courses offered by the English language teaching unit in order to graduate from their respective degree programmes. The 1,000-level course was a foundation English course for year 1 students, and it was designed to provide a comprehensive English language foundation to new undergraduate students for equipping them for university studies and developing their understanding of the common features of academic English. The 1,000-level course included topics, such as the L2 writing process, L2 listening and reading and features of L2 spoken English. The 2,000-level course was an advanced course for year 2 students, or above which focused on advanced academic English skills. The 2,000-level course entailed topics, including using academic writing skills for composing specific academic genres, critically evaluating the academic language use in research papers and developing students’ oral presentation skills for persuasion.

3.2 Data collection

The current study includes two research instruments: a questionnaire and follow-up semi-structured interviews with individual students from different faculties.

The comprehensive questionnaire is organised into two sections. The first section of the questionnaire asked the participants to indicate their faculty, their year of study, their gender, their secondary school’s medium-of-instruction, the types of secondary schools that they attended (e.g. government school and international school), the medium-of-instruction that is used in their lectures and tutorials, their English proficiency grades prior to enrolling at the university (i.e. IELTS scores or equivalent English language test results) and their use of language(s) at home. The second part of the questionnaire consists of 36 Likert-type statements related to the students’ frequency of using English for academic purposes, frequency of using English outside class, intrinsic and extrinsic motivation in learning English and English language learning strategies (see Section 3.5 for further details). Cronbach’s alpha for the different sections ranged from 0.857 to 0.896, which suggests that the internal consistency reliability of the questionnaire was high (Dörnyei 2007).

Additionally, follow-up individual semi-structured interviews were carried out with students of various levels of English attainment in order to gain more in-depth accounts of their previous and current language experiences (within and outside campus) and English language learning strategies.

3.3 Participants

A total of 349 undergraduate students completed the questionnaire, who were drawn in roughly equal distributions from each of the university’s faculties. A convenience sampling strategy was employed in order to recruit student participants in completing the questionnaire. 7.7% of the students were from the Faculty of Arts, 15.1% of the students were from the Faculty of Business, 20% of the students were from the Faculty of Engineering, 9% of them were from the Faculty of Medicine, 23% of them were from the Faculty of Science and 25% of the students were from the Faculty of Social Sciences. All questionnaire participants were L2 English speakers and they all have scored the minimum English language entrance requirement (i.e. IELTS overall band 6 or equivalent) for enrolling on their respective degree programmes. 81.7% of the participants were HK local students, 12% of the participants were from Mainland China and 6.3% of the participants were classified as international students who come from overseas countries. 4% of the students were year one undergraduates, 6.6% were year two undergraduates, 37.1% of them were year three undergraduates and 52.3% of them were year 4 or above. Note that the duration of most of the degree programmes is four years. Some of the degree programmes, such as education and medicine, demand five years of study.

Additionally, the individual semi-structured interviews were held with six students who came from a range of academic fields, and this was largely achieved, with one student in the Faculty of Arts, one from the Faculty of Social Sciences, one from the Faculty of Engineering, one from the Faculty of Medicine and two from the Faculty of Science. All participating students achieved an A grade (i.e. 4.0 Grade Point Average) in both 1,000- and 2,000-level academic English language courses and based on the questionnaire data, these students are all highly motivated to learn English (both intrinsically and extrinsically). These high-performing students are chosen to participate in the interviews since their accounts can enable us to understand the potential success factors for high English attainment, particularly the student’s language learning motivation and their use of language learning strategies. Although the conclusions that can be drawn from these interviews are limited due to the low number of students who volunteered to participate in the interviews, these students come from different academic disciplines and graduated from different secondary schools, ranging from adopting different medium-of-instruction, from local schools to overseas high school. Hence, the interview data can offer some insight into the students’ perceptions of success in English language learning. The interviews were audio-recorded and conducted in the participant’s first language which allows them to offer adequate detail in their responses.

3.4 Key measures

3.5 Data analysis

RQ one explores the secondary school-level influence on students’ academic English language performance in university (i.e. 1,000- and 2,000-level academic English course grades). Thus, this question is answered by two simultaneous linear regressions controlling for students’ sociodemographic backgrounds, academic English ability at the entry to university, the primary medium of instruction in secondary school, student’s faculty, and medium-of-instruction at university. In addition to these variables in RQ one, RQ two further examines the role of learner-level variables, including intrinsic and extrinsic motivation, cognitive/metacognitive and social/affective strategies in predicting both 1,000- and 2,000-level academic English course grades. Thus, in order to answer RQ two, we conducted two hierarchical regressions on top of the two regression analyses in RQ one.

To investigate RQ three, content analysis is used to analyse the interview transcripts. The first stage of the analysis entails an iterative process of reading and annotating the transcripts with comments and codes. These initial codes are then categorised into different themes that capture the recurring patterns in the interview data. The focus of the analysis is on the students’ comments on their own English language experiences and their learning strategies for enhancing their own general and academic English proficiency.

4.1 Descriptive statistics

Table 2 demonstrates participants’ background information at both secondary-school level and university level. In terms of medium-of-instruction used in secondary schools, the majority of participants received EMI (64.8%), followed by CMI (33.2%). Regarding participants’ faculties, the majority of them came from Social Sciences (24.9%), followed by Natural Sciences (22.9%), Engineering (20.3%), Business (15.1%), Medicine (9.1%) and Arts (7.7%). Among these participants, 66% of them received EMI in lectures and 63.7% of them received EMI in tutorials in CUHK.

4.2 The influence of medium-of-instruction in both secondary schools and university on students’ academic English proficiency

In order to answer the first RQ, we have controlled for both secondary-school-level and university-level information. Table 3 demonstrates the standardised results generated by linear regression analyses on predicting both 1,000-level (i.e. model 1) and 2,000-level grades (i.e. model 2). We have conducted post-estimation tests, which ensured that our analyses satisfied the assumptions of linearity, normality, no-multicollinearity, no-autocorrelation and homoscedasticity.

Model 1 explained 12.02% variances in 1,000-level grade, with F (12,336) = 4.97, p < 0.001. In terms of medium-of-instruction in secondary school, students who received Chinese as medium-of-instruction did not obtain a significantly different 1,000-level grade in comparison to those who received English as medium-of-instruction (β = −0.007, p = 0.889). Regarding medium-of-instruction in university, English predominantly used in university lectures (β = 0.105, p = 0.132) and tutorials (β = 0.0098, p = 0.888) were not significant predictors of 1,000-level grade.

Model 2 explained 10.77% variances in 2,000-level grade, with F (12,336) = 4.5, p < 0.001. In terms of medium-of-instruction in secondary school, students who received Chinese as medium-of-instruction did not obtain a significantly different 2,000-level grade in comparison to those who received English as medium-of-instruction (β = 0.037, p = 0.479). Similarly to model 1, students’ 2,000-level grade was not significantly predicted by the tutorial’s medium-of-instruction (β = −0.02, p = 0.773). However, participants who received predominantly EMI in university lectures were more likely to receive a higher 2,000-level grade (i.e. β = 0.213 and p = 0.002).

4.3 Students’ motivation and L2 learning strategies predicting academic English proficiency

Table 4 demonstrates the results after adding in learner-level factors, where model 3 predicts 1,000-level grade and model 4 predicts 2,000-level grade. Model 3 explained 19.7% of total variances in 1,000-level grade, with F (16,332) = 6.34. Compared to model 1, the addition of learner-level variables resulted in 7.67% change in R ², with F (4, 332) = 9.02, p < 0.001. Model 4 explained 19.8% of total variances in 2,000-level grade, F (16,332) = 6.37. Compared to model 2, the addition of learner-level variables resulted in 9.03% change in R ², with F (4, 332) = 10.46, p < 0.001.

Similarly to model 1, as shown in model 3, there were no significant differences in 1,000-level grade between participants who received EMI in secondary school and those who received CMI in secondary school. Receiving predominantly EMI in university lectures (β = 0.056 and p = 0.41) or in university tutorials (β = 0.02 and p = 0.765) did not make a significant difference in 1,000-level grade.

However, in model 3, students who adopted more cognitive and metacognitive learning strategies with English learning in university were more likely to score higher on 1,000-level grade, i.e. β = 0.197 and p = 0.012. Moreover, the 1,000-level grade was not significantly predicted by university students’ intrinsic (β = 0.034 and p = 0.41), extrinsic motivation (β = −0.056 and p = 0.408), and social affective strategies (β = 0.136 and p = 0.059) with L2 English learning.

Similarly to model 2, as shown in model 4, medium-of-instruction used in secondary school did not make significant differences regarding their influences on 2,000-level grade but using English predominantly in university lectures predicted higher 2,000-level grade, i.e. β = 0.144 and p = 0.034. In contrast, using English predominantly in university tutorials did not hold a significant impact on 2,000-level grade.

However, in model 4, among all the learner-level factors, social and affective learning strategies (i.e. β = 0.166 and p = 0.022) and extrinsic motivation (i.e. β = 0.133 and p = 0.05) significantly and positively predicted 2,000-level grade. In contrast, cognitive and metacognitive learning strategies and intrinsic motivation were not significant predictors of 2,000-level grade.

4.4 Qualitative analysis

In the quantitative analysis, the results indicate that the medium-of-instruction of students’ secondary schools does not play a role in determining their academic English proficiency at university. Moreover, students’ cognitive and metacognitive strategy use, alongside social and affective strategy use, students’ extrinsic motivation and attending EMI lectures contribute to the success of students’ English language learning. In this section, we will be discussing the potential success factors that are identified from the interviews with high-performing students, which include L2 strategy use and motivation.

4.4.1 L2 strategy use: use of cognitive and metacognitive strategies

Reading English books and articles and watching TV movies are the most common metacognitive strategies that many students have mentioned. Student A is a year 4 law student, and she previously attended a British secondary school before joining the university. In the following excerpt, she explains how reading English books and watching English TV programmes enhance her general English proficiency:

Student A recounts her prior English learning experience which involves using metacognitive strategies, such as ‘doing past papers’ and adopting ‘a very academic way’ of learning English. As she commenced her tertiary education, she employed different kinds of metacognitive strategies, including reading English books in different genres and watching English TV programmes via Netflix and YouTube. She believes that engaging in these activities regularly allows her to learn English in a stress-free manner.

Similar to student A, student B, who is a year 4 Anthropology student, expresses similar ways of learning English:

Student B attended a CMI secondary school in HK and prior to studying at the university, she achieved an IELTS band 7 which classifies her as a proficient English user. Student B relates her success in English learning to the employment of cognitive strategies, including watching movies and drama and listening to podcasts in English in order to observe how English is being used in different social contexts. By doing so, it enables her to develop an interest in learning the western culture and enhance her language awareness in terms of the ways of communicating ideas through different modes of communication (English writing and speaking in this case).

4.4.2 L2 strategy use: social and affective strategy

Some students attribute their success in English learning to their effort in speaking English outside the classroom. This is achieved through communicating with international students or academic staff at the university.

In the interview, student A explains that participating in intercultural communication with people who come from different linguistic and cultural backgrounds creates opportunities for student A to immerse in an English-speaking environment. She describes that these events make her ‘felt natural because I just came back from the UK’. In this extract, it is noticeable that student A has displayed an understanding of using diverse communicative resources (verbal English utterances and gestures in this case) to include different people in the community. Such a practice is often referred to as translanguaging, which involves using available linguistic and multimodal resources for promoting social inclusion and participation (Tai 2022, forthcoming; Tai and Li 2020, 2021a, 2021b, 2021c). It can be argued that student A is adopting a social strategy in order to engage in social interaction with other international students in order to improve language learning and cultural understanding (Oxford 1990).

Although the questionnaire data illustrates that social and affective strategies play a more important role in contributing to students’ success in English learning, the interview data shows that the high achieving students mostly refer to both their use of cognitive strategies and social strategies for facilitating their English learning. This may be the result of selection bias, that is of motivated students who volunteered to take part in the semi-structured interviews. Nevertheless, it is noted that all of the six students explain how they enjoy learning English through doing English-related leisure activities, such as listening to English songs and movies and reading English books.

4.4.3 L2 motivation

Extrinsic motivation is the most common form of motivation for successful students attributed to when they learn English. This is evidenced in some of the students’ responses as they explain their reasons for motivating them to acquire a high level of academic English proficiency.

It is evidenced that student A’s family values the importance of education and her family was keen to financially support her overseas study plan in order to enable her to receive the best secondary education in the UK. Hence, student A’s family influence and her self-determination for honouring her family’s expectations are the extrinsic motives which encourage her to improve her academic English proficiency. It is also noticeable that student A also states her goal to be a successful lawyer and acquiring a strong English proficiency is a prerequisite for becoming an ‘elite’ in the law profession.

However, apart from extrinsic motives, some successful learners also attribute high importance to intrinsic motives. This is evidenced in student C’s account:

Student C is a year 4 Biomedical Science student, and he previously attended a CMI local school in HK. Before joining the university, he achieved an IELTS band 8 score, which classifies him as a proficient English user. In the interview, student C explains how he transitions from attending to extrinsic motivation to intrinsic motivation. When he was a secondary school student, he only focused on achieving good grades in his English language public examination. As he received more opportunities to engage in more English activities at the university, he gradually developed an interest in learning English through reading English texts and engaging in English-related activities.

Overall, in the student interviews, students display a genuine interest in learning English, and they explore different ways for enhancing their English proficiency. It is observed that undergraduates with high academic English proficiency levels tend to relate their success in learning English with their L2 strategy use (particularly the use of cognitive and social strategies) and intrinsic and extrinsic motivation.