A study on English learning strategies of university students in Hong Kong

ABSTRACT

This study attempted to analyze learning strategies used by Hong Kong university students for learning English. Results indicate that Cantonese native speakers mostly used cognitive strategies when learning English, while memory strategies were the least used. Besides, the use of memory strategies among males varied significantly, and little difference was observed in the use of metacognitive strategies by females. The use of cognitive strategies was significantly associated with grade level, with fourth-year students using cognitive strategies more often than fifth-year students. Finally, on correlating the daily study time with cognitive strategies, it was observed that students who studied more than 0.5 hours a day used cognitive strategies more frequently than those who studied less than 0.5 hours a day. This study not only provides new evidence that grade level and study time affect the use of English learning strategies in Hong Kong, but also yields some important pedagogical implications.

KEYWORDS:

• Strategy Inventory for Language Learning
• learning strategies
• Hong Kong university students
• second-language learning
• Cantonese native speakers

Introduction

Since 1997, the Hong Kong government has adopted the language policy of biliteracy and trilingualism, with the aim of helping the students master written Chinese and English while at the same time speak fluent Cantonese, Putonghua, and English. English has both instrumental and symbolic value in Hong Kong. Bilingualism in English and Cantonese is always viewed as integral to an individual coming from Hong Kong (Hansen Edwards, 2015). Previous studies found that teachers, civil servants, and clerks in Hong Kong use English for more than 66% of their total work time (Pierson, 1994). English is not only the main medium of instruction in the government-funded and private universities, but also the unmarked language of written communication in the workplace (Bacon-Shone, Bolton, & Luke, 2015; Evans, 2016; Kirkpatrick & Liddicoat, 2017). English is thus considered to be essential, not only for education but also for career advancements (Lau, 2020). Most of the Hong Kong people begin to learn English during kindergarten (Nunan, 2003). However, some Hong Kong university teachers pointed out that the overall English level of university students still needs to be improved. A common reason behind this phenomenon is that appropriate learning methods or models are not available to most Hong Kong university students for improvement of their learning efficiency (Tam, 2013). There is much evidence available which indicates that the use of appropriate learning strategies can improve the learners’ situation and help them to become more flexible in improving their proficiency (O’Malley & Chamot, 1990; Oxford, 1990; Wenden & Rubin, 1987).

Literature review

In the 1990s, learning strategies attracted the attention of researchers involved in studying the acquisition of a second language (Ellis, 1994; McDonough, 1999). Oxford (1990) proposed that a strategy system is composed of learning behaviors, and other scholars studied the learning strategies used in English learning (Huang & Naerssen, 1987; Liu & Huang, 2002; Wen & Wang, 2004). A learning strategy is an implicit learning system that can be regarded as an internal learning method. This method starts with the learners’ internal thinking and can improve learning efficiency, ultimately enhancing the learning achievement (Duffy, 1982; Mayer, 1987; Oxford, 1990). Effective learners can choose appropriate learning strategies based on their language learning process, whereas poorer learners find it difficult to understand the problems associated with their use of learning strategies (Carton, 1966; O’Malley & Chamot, 1990; Vann & Abraham, 1990). From the perspective of cognitive psychology, second-language acquisition requires information processing. During information processing, the use of learning strategies can help learners to realize the potential problems that they are likely to face, and thus can be motivated to improve their information processing process, which can ultimately lead to better learning achievement (Khodadad & Kaur, 2016; O’Malley & Chamot, 1990).

Definitions and classifications of learning strategies

Following the initial definition proposed by March and Simon (1958), Rigney (1978) defined learning strategies as the procedural steps to discover and solve problems during learning with the ultimate goal of improving learning outcomes. Later, Weinstein (1982) stated that a learning strategy implies a series of learning activities that should be based on the intrinsic nature of the students’ learning process (i.e. their implicit learning system). Other researchers suggested that a learning strategy is the process of using explicit methods and skills to solve the problems encountered by students during their internal learning process (Huang, 1990; Liu & Huang, 2002; Wen & Wang, 2004). From these definitions, it can be concluded that learning strategies refer to what learners do to achieve the internalization of external knowledge, including activities such as ‘acquiring’, ‘processing’, ‘storing’, and ‘retrieving’. These activities allow students to improve the effectiveness of their learning process.

Since the learning strategies were proposed in the mid-twentieth century, cognitive psychologists have classified them into two types of general strategies and regulatory strategies (Resnick & Beck, 1976). Later, Dansereau (1985) further improved the classification of learning strategies and provided more clarity to the distinction between primary strategies and support strategies. Although this classification has influenced many studies on learning strategies, it does not reflect the interaction of learning methods with learning control. It also fails to throw light on appropriate learning methods for students, particularly for students having lower proficiency. The lack of suitable learning methods for students with lower proficiency may cause many problems in the learning process, thus bringing forward the question of how these students can improve their learning effectiveness through the use of appropriate strategies. Thereby, the classification of learning strategies needs further improvement (Huang, 1990). From a macro perspective, the ultimate goal of learning strategies should be to improve the efficiency of language learning and promotion of more active and enjoyable learning behavior (Oxford & Nyikos, 1989). Departing from the ‘dichotomy’ classification (Kirby, 1984; Resnick & Beck, 1976; Rigney, 1978) and the ‘trichotomy’ classification (O’Malley & Chamot, 1987, 1990), Oxford (1990) claimed that learning strategies include memory strategies, cognitive strategies, compensation strategies, metacognitive strategies, affective strategies, and social strategies. The first three are direct strategies, while the latter three are indirect strategies. The specific relationships among these strategies are depicted in Figure 1.

Figure 1. Interrelationships between direct and indirect strategies and among the six types of strategies (Oxford, 1990).

According to the different perspectives of researchers, learning strategies have been classified differently. Most of the subsequent studies on the classification of learning strategies have referred to Oxford (1990) and developed their own viewpoint (Bremner, 1999; Ghadessy, 1998; Liu, 1997; Tam, 2013). In spite of the different definitions and classifications, most studies have reached a consensus that learning strategies are a method or skill in language learning, which not only can improve learning efficiency but also can improve learning effectiveness. Therefore, this study was based on the Oxford (1990) classification.

Learning strategies and second-language learning

In the 1960s and 1970s, some scholars began to study coding strategies employed by children in learning. For example, Moely, Olson, Halwes, and Flavell (1969) found that children over 10 years of age employed higher-level coding strategies in comparison to those who were under 10 years of age. Subsequently, researchers tested university students, elementary school students, and kindergarten students, and found that the use of strategies varied significantly with age (Salatas & Flavell, 1976). Other studies indicated that fast learners pay more attention to learning strategies and use them more carefully than slow learners (Thorndyke & Stasz, 1980). Hence, the study of learning strategies has gradually developed from the initial investigation about the use of strategies to the discussion of the factors that influence their use.

Recent research demonstrated that learning strategies as a method for language learning bear direct influence on learners’ coding processes (Weinstein & Mayer, 1986). Huang and Naerssen (1987) argued that the research sample should not only include good learners, because there are also some studies available which suggest that testing good learners exclusively does not prove useful (Naiman, Fröhlich, Stern, & Todesco, 1978; Rubin, 1975). Moreover, some studies that have compared the use of learning strategies of high scorers and low scorers in second-language acquisition have highlighted possible factors that influence the use of learning strategies (O’Malley & Chamot, 1990). After proposing six learning strategies, Oxford (1990) found that the active use of consciousness, behavior, and emotions in strategies adopted by second-language learners can help them to deal with new information more easily and in a shorter period of time. Furthermore, learners use different learning strategies to improve their language communication skills, which also leads to a positive effect on second-language learning. Additionally, Chamot (2004) stated that by using these techniques and methods, learners aim to improve their learning efficiency and facilitate their recall of language forms and content. Both the early studies, which did not distinguish learning categories, and the recent research on second-language acquisition have focused on the characteristics of the learning strategies used by learners. However, the research on second-language acquisition focused on the more active and efficient learning process of learners who use variable learning strategies.

Research on English learning strategies of Hong Kong students

Some researchers analyzed how Hong Kong students use learning strategies while learning English as a second language (Bremner, 1999; Ghadessy, 1998; Hu & Xu, 2003; Tam, 2013). In one of the studies, Ghadessy (1998) used the Strategy Inventory for Language Learning (SILL) and investigated the use of learning strategies of 602 students at Hong Kong Baptist University. However, this research did not provide details regarding the native language of the participants, which could have been English, Cantonese, or any other language. This is very crucial as different native languages may influence the use of language learning strategies differently (Jiang, 2000). In a later study, Bremner (1999) surveyed 114 Cantonese-speaking students using the SILL and found that, out of 50 questions, 11 questions were closely related to learning strategies and language proficiency. In this study, the 114 participants tested were undergraduate students at the City University of Hong Kong who had already been working as elementary school teachers, and their ages ranged from 20 to 50 years. Such a wide range of age is an important factor to consider, as other studies have shown that age may influence the use of learning strategies (Gu, Xin, & Li, 1998; Hu & Xu, 2003; Li, Yao, & Liu, 2011). In a more recent study, Tam (2013) examined the results of the Hong Kong Advanced Level Examination of 50 students between 19 and 21 years of age studying at The Hong Kong Polytechnic University, and found that social strategies are not only related to the participants’ knowledge level of the second language, but also closely relate to socioeconomic status. The sample size was too small as only 50 subjects were included in the study, which was likely to affect the result. Unlike these previous studies, here we strictly delimit our study by including only those students with Cantonese as their native language. Furthermore, the size of the sample was larger (101 students), and this increased the credibility of the results. Firstly, the overall use of the six learning strategies was analyzed, as proposed by Oxford (1990). Afterward, the factors affecting the use of learning strategies adopted by Hong Kong university students while learning English were explored. The roles of gender, grade level, and time devoted for learning in English language learning were also investigated.

This study addressed the following research questions:

1. What type of learning strategies do Hong Kong university students use to learn English?

2. How do factors (gender, grade level, and amount of time devoted to learning English language) influence the use of learning strategies by Hong Kong university students?

Methodology

Questionnaire

The SILL was suggested to be used to assess the use of learning strategies (Oxford, 1990). The items of this questionnaire relevant for Hong Kong university students were adapted from the SILL. The survey was conducted from 16 January to 17 February 2020. A total of 124 questionnaires were collected for final analysis. Among them, 101 questionnaires were valid, while the other 23 questionnaires were invalid. In 19 of the 23 invalid questionnaires, the native language reported was Mandarin, and in the remaining four the native languages reported were Chaoshan dialect, Wu dialect, and Korean.

The questionnaire consisted of two parts. The first part provided background information, including gender, grade level, English level, and time spent in English learning. Part two contained 50 items that were developed to probe the use of learning strategies by the students (see Table 1). The questionnaire was in the form of a Likert scale with responses, ranging from ‘1’ (never or almost never) to ‘5’ (always or almost always). Each participant was required to complete the questionnaire in 20–30 minutes.

Table 1. Learning strategies.

Items	Strategies
1–9	Memory strategies	Direct strategies	Enable learners to store verbal material and then retrieve it when needed for communication
10–23	Cognitive strategies		Enable learners to understand and produce new language in many different ways
24–29	Compensation strategies		Allow learners to use the language despite their large gaps in knowledge
30–38	Metacognitive strategies	Indirect strategies	Provide a way for learners to coordinate their own learning process
39–44	Affective strategies		Help to regulate emotions, motivations, and attitudes
45–50	Social strategies		Help learners to learn through interaction with others

Participants

A total of 101 students (31 male and 70 female) studying in The Education University of Hong Kong participated in the study. The native language of the participants was Cantonese. Detailed information of the participants with regard to their gender and grade level is presented in Table 2. The major in which the participants were enrolled was not considered during sampling as, according to Ghadessy (1998), students’ majors do not influence their choice of learning strategies.

Table 2. Participants.

Classification		Total number
Gender	Male	31
	Female	70
Grade level	Year 1	20
	Year 2	14
	Year 3	45
	Year 4	9
	Year 5	13

More than half of the participants (about 65.3%) had started studying English in kindergarten, and most participants (about 63.26%) had acquired formal English proficiency test certificates, such as the Hong Kong Diploma of Secondary Education, the Test of English as a Foreign Language, and the International English Language Testing System. A majority of participants with a percentage of 88.7% had been studying English for more than 11 years.

Findings and discussion

Reliability and validity

The main role of reliability analysis is to test the consistency and stability of results, which can then be used to judge whether the results are credible. If reliability is high, the results are considered to be credible. Cronbach’s α is the standard measure of reliability. Cronbach’s α for the 50 items in the questionnaire was 0.966, which indicated that the questionnaire was highly reliable.

The basic purpose of validity analysis of the tool (questionnaire) is to test whether the questionnaire can accurately measure the degree of the desired characteristics (Mehrens & Lehmann, 1978). In this study, the data obtained were analyzed using the Kaiser–Meyer–Oklin test to measure sampling adequacy and the Bartlett test for sphericity (Kaiser, 1974). A high Kaiser–Meyer–Oklin value (close to 1.0) indicates that the items of the questionnaire represent different factors and thus the data are suitable for factor analysis. Besides, the Bartlett test is used to check the correlation between variables. If the test value is smaller than 0.05, the correlation is deemed significant. On the contrary, if the test value is larger than 0.05, then the correlation is not significant. The Kaiser–Meyer–Oklin value obtained was 0.842, demonstrating that the data were suitable for factor analysis. The result of the Bartlett test was less than 0.01, indicating that the correlation between variables was significant. Therefore, the reliability and validity tests revealed that the data could be used for further analysis.

Overall English learning strategies used by university students in Hong Kong

This section presents a detailed analysis of the overall strategies employed by Hong Kong students for English language learning, and the analysis is based on the ranking of standard deviation and mean values (see Table 3).

Table 3. Overall English learning strategies.

Strategies	Mean value	Standard deviation
Memory strategies	2.8272	1.003
Cognitive strategies	3.2298	1.0066
Compensation strategies	3.3151	0.9591
Metacognitive strategies	3.077	0.9294
Affective strategies	2.9653	0.9901
Social strategies	3.0297	1.0633

As presented in Table 3, the maximum and minimum standard deviations were 1.0633 and 0.9294 respectively, and the difference between them was 0.1339 (<0.14). In terms of the mean value, the maximum value of compensation strategies was 3.3151 and the minimum value of memory strategies was 2.8272. The difference between them was 0.4879, which was quite less and reflected that the overall use of learning strategies by the participants was at a high level. Although memory strategies ranked the lowest in mean value, their standard deviation ranked third, which indicated that the participants were more stable regarding the use of memory strategies than the other five strategies. In addition, compensation strategies ranked the highest in mean value, and their standard deviation (0.9591) was quite large. This indicates that there existed a diversity among different participants in terms of the use of compensation strategies. However, the largest value for standard deviation was found in the case of social strategies, which reflected that the English learning of participants was influenced by the external language environment and other factors.

Since the mean value of the use of affective strategies (0.9901) was small, it can be inferred that Hong Kong students appeared to be poorly adjusted and lacked control over negative emotions while learning English. That is, they were susceptible to emotional factors during the process of learning English and lacked the ability to adequately adjust their negative emotions, which was more likely to affect their interest in learning English. A similar result was obtained for memory strategies. In the process of receiving the image information presented by the teacher, English learners only accepted it passively. They were thus unable to take appropriate actions to obtain the learning information transmitted by the teacher, which ultimately leaded to the decline of their ability to retrieve information. Therefore, in the process of teaching English, teachers can reduce the teaching of traditional knowledge in an appropriate way and direct students’ interest in learning through a variety of teaching activities. This is likely to improve the learning mood of the students and hence enhance the efficiency of their English learning.

Factors affecting the use of learning strategies in learning English

Gender differences

Studies conducted in the past had reported contradictory findings for the relationship between gender and learning strategies. Some of them suggested that there is a significant correlation between gender and learning strategies (Chen, 2014; Green & Oxford, 1995; Oxford & Nyikos, 1989; Tam, 2013) or a weak correlation (Ghadessy, 1998; Gu et al., 1998), whereas others maintained that there is no correlation (Jiang, 2000; Jiang & Zhao, 2001; Li et al., 2011; Liu & Huang, 2002; Zhang, Gao, & Liu, 2002). In light of the mixed findings from the previously conducted studies, the study attempted to investigate whether the use of English learning strategies among Hong Kong university students was affected by gender (see Table 4).

Table 4. Gender and learning strategies.

	Female		Male
Strategies	Standard deviation	Mean value	Standard deviation	Mean value
Memory strategies	0.6389	2.8551	0.7165	2.7634
Cognitive strategies	0.6457	3.2286	0.8453	3.2327
Compensation strategies	0.6461	3.2643	0.5786	3.4301
Metacognitive strategies	0.6604	3.1016	0.84	3.0215
Affective strategies	0.6509	2.9619	0.7877	2.9731
Social strategies	0.7374	2.9762	0.9333	3.1505

As presented in Table 4, the difference between the mean values of gender among the six learning strategies was small, which demonstrated that the overall strategies used by the participants are quite similar. The analysis of variance indicates that there was no significant correlation between the gender and the use of any of the six learning strategies (P > 0.05). That is, males and females did not differ significantly with respect to the use of learning strategies.

Furthermore, in terms of the mean value ranking, compensation strategies and cognitive strategies were used to a maximum extent while the use of memory strategies was minimal (lowest) and was regardless of gender. This was consistent with the ranking of general learning strategies. Regarding standard deviation, social strategies showed the largest value, which was indicative that they were the most unstable. This also implies that the use of social strategies differed largely with respect to gender. Although cognitive strategies ranked second in the overall use, the standard deviation in gender was relatively large. This reflects the phenomenon of polarization between males and females in the use of cognitive strategies. Moreover, the values for standard deviations of compensation strategies and metacognitive strategies were relatively small. In light of the previous analysis, it can be concluded that compensation strategies were widely used by Hong Kong university students while learning English. Besides, there were no obvious differences between genders.

Regarding females, their use of direct strategies, which included memory strategies, cognitive strategies, and compensation strategies, was higher than that of indirect strategies. This is consistent with the results of Li et al. (2011). In addition, the standard deviation of the use of social strategies was too large (0.7374), indicating that there were great differences among females in terms of the ability to process and retrieve information while communicating with others. Due to the lack of their ability, some females might find difficulty in retrieving existing knowledge information in the subsequent learning process, which affected their normal communication and learning process. Some females showed higher levels of the use of social strategies, but other females might prove to be incompetent in the process of information exchange, which affected the normal interpersonal skills during English learning. With respect to employment of memory strategies, males exhibited lower-level performance in comparison to females. This indicates that females were better than males in storing and processing knowledge. The reason for this may be that they did not realize the importance of memory methods, or did not understand various methods that can help to improve memory.

With respect to the use of indirect strategies, including metacognitive strategies, emotional strategies, and social strategies, females used social and emotional strategies at a higher level compared to males. This finding is in consonance with the findings of Politzer (1983), Tannen (1990), Green and Oxford (1995), and Kato (2005). This effect also reflects that females were more proficient in communication than males and emotional factors played a major role in their language learning, while males were found to be more concerned about the practicality of language learning compared to females. Males were better at using the logical abilities while considering the practical value of listening, speaking, reading, and writing in language learning, from a long-term perspective.

Grade level

In this study, the grade level of 101 participants ranged from year 1 (Y1) to year 5 (Y5). The comparison between the mean value and standard deviation with respect to the use of the six learning strategies among different grade levels is presented in Table 5.

Table 5. Grade level.

Grade level	Memory strategies	Cognitive strategies	Compensation strategies	Metacognitive strategies	Affective strategies	Social strategies
Y1 (N = 20)	2.93 (0.52)	3.15 (0.61)	3.19 (0.53)	3.05 (0.6)	2.97 (0.66)	3.07 (0.61)
Y2 (N = 14)	2.82 (0.72)	3.49 (0.64)	3.36 (0.55)	3.34 (0.64)	2.9 (0.57)	3.11 (0.81)
Y3 (N = 45)	2.79 (0.63)	3.17 (0.67)	3.3 (0.74)	3.07 (0.65)	3.02 (0.66)	3.01 (0.82)
Y4 (N = 9)	3.12 (0.73)	3.81 (0.31)	3.69 (0.24)	3.38 (0.77)	3.2 (0.59)	3.37 (0.85)
Y5 (N = 13)	2.58 (0.86)	2.89 (1.2)	3.23 (1.08)	3.63 (1.08)	2.65 (1.13)	2.71 (1.17)

Note: Standard deviation in parentheses. N = number.

As shown in Table 5, although the mean value of cognitive strategies was high among different grade levels, the standard deviation was larger, which indicated that there was considerable difference in the use of cognitive strategies. The mean values of social and affective strategies were the lowest, which demonstrated that most students used these two strategies less often. However, the standard deviations were relatively stable, reflecting that the differences among the few students who used social and affective strategies were relatively small and stable. One-way analysis of variance indicated that students of different grade levels exhibited significant difference in the use of cognitive strategies (F = 3.123, P = 0.018), whereas there was no significant difference in the case of the other five strategies (see Figure 2).

Figure 2. Grade level.

As shown in Figure 2, the lowest mean value for the Y5 students was 2.89, and for Y4 students it was 3.81, which was the highest. Compared to other strategies, the difference between these two was highly significant (0.92). Students of the five grades were compared in pairs (i.e. Y1 and year 2 [Y2], Y1 and year 3 [Y3], Y1 and year 4 [Y4], etc.) to see which grade levels differed significantly in the use of cognitive strategies. According to the results of multiple comparisons, significant differences were observed among Y5, Y2, and Y4 students: the former (Y5 and Y2 students) was P = 0.024, while the latter (Y5 and Y4 students) was P = 0.002. Besides, there were also significant differences between Y4 and Y3 students (P = 0.011). These results reflect that Y4 students made most frequent use of cognitive strategies, and Y5 students used such strategies less frequently, in comparison to other grade levels. One-way analysis of variance revealed that students of different grade levels used cognitive strategies frequently (P = 0.018 < 0.05). Furthermore, the pairwise comparisons of the students from all five grades indicated that there was a large difference in the creation of the information input and output models for students of each grade level. This demonstrates an upward trend from Y1 to Y2 and from Y3 to Y4, while the students of other grade levels showed a downward trend, in which the decline from Y4 to Y5 was the most obvious. Y4 students showed the highest level in the use of cognitive strategies whereas Y5 students showed the lowest. However, the maximum standard deviation was observed in Y5 students, which indicated that the use of learning strategies by Y5 students was the most unstable. Compared to students in other grade levels, Y5 students experienced a significant decline in their ability to analyze and reason information during English learning. The main reason may be that the students in Y5 are about to graduate, and some students are busy applying for jobs or postgraduate studies, which accounts for a large difference in the use of cognitive strategies between them. While planning English learning activities, teachers can tailor the activities according to the needs and characteristics of their students studying in different grade levels.

Among the 101 participants, there were 45 Y3 participants. The mean value obtained with respect to the use of memory strategies was small, and the standard deviation was the lowest. This reflects that, in comparison to students in other grade levels, Y3 students were at a disadvantage when dealing with images, information storage, and information retrieval. Similar observation was made in use of memory strategies by Y4 and Y5 students, indicating that students at higher grade levels faced difficulty in storing teacher-provided image and sound information accurately.

Daily English study time

The daily English study time mainly refers to the time spent on English homework, text review, oral practice, and so on. For the purpose of discussing the relationship between learning strategies and daily study time (T), the study time was divided into four groups: Group 1, T ≤ 0.5 (N = 57); Group 2, 0.5 < T ≤ 1 (N = 29); Group 3, 1 < T ≤ 1.5 (N = 3); and Group 4, T > 1.5 (N = 12). The relationships between the mean value and standard deviation of the six learning strategies and different daily study time are presented in Table 6.

Table 6. Daily study time.

Daily study time	Memory strategies	Cognitive strategies	Compensation strategies	Metacognitive strategies	Affective strategies	Social strategies
T ≤ 0.5 (N = 57)	2.65 (0.74)	3.02 (0.77)	3.28 (0.66)	3.02 (0.79)	2.91 (0.73)	3.02 (0.83)
0.5 < T ≤ 1 (N = 29)	2.74 (0.75)	3.41 (0.61)	3.49 (0.87)	3.09 (0.59)	2.95 (0.7)	3 (0.83)
1 < T ≤ 1.5 (N = 3)	3.48 (0.56)	3.52 (0.65)	3.33 (0.58)	3.22 (0.5)	3.33 (0.93)	3.22 (0.62)
T > 1.5 (N = 12)	3.13 (0.76)	3.74 (0.82)	3.39 (0.83)	3.5 (0.7)	3.29 (0.84)	3.03 (1.06)

Note: Standard deviation in parentheses. N = number.

All of the 101 participants spent a fixed amount of time each day studying English, but there were differences in the amount of time spent. Participants’ use of learning strategies depended upon the amount of time spent studying. It was observed that the daily study time influenced their use of learning strategies. According to Table 6, participants whose daily study time was 0.5 < T ≤ 1 obtained the largest value for standard deviation in the use of compensation strategies, which indicated that there was a large difference among these participants in terms of their speaking and writing ability. Furthermore, some participants showed insufficient literacy skills. Among the 101 participants, 57 participants studied English for 0.5 hours (or less) per day (T ≤ 0.5). The mean value of their use of metacognitive strategies was high, and the standard deviation was also too large. This means that these 57 participants had a high ability for coordinating and planning their study time as well as for assessing the effectiveness of their learning activities. However, high-level polarization was observed in these 57 participants. Some students had an outstanding ability to learn English, whereas others lacked confidence in studying English and had difficulties in clarifying and summarizing valuable information during their learning activities. In light of these findings, teachers can plan and execute appropriate learning activities and give assignments to students with variable study time and assist them to improve their speaking and writing skills through the use of cognitive strategies.

Conclusion and implications

In this study, 101 participants showed a medium level for the use of language learning strategies, which is consistent with the results reported by many scholars who had investigated students in Asian countries, including Wharton (2000) in Singapore, Park (2005) in Korea, Zhou (2010) in mainland China, and Domakani, Roohani, and Akbari (2012) in Iran. The results of this study indicated that, during the process of English learning, Hong Kong university students used learning strategies either consciously or unconsciously. The memory strategy was the least used strategy, which is different from some previous studies (Kohn, 1992; Campbell & Zhao, 1993). It was found that the ‘memorization-oriented’ teaching of Hong Kong university students did not contribute to improve their proficiency in English language. As some earlier researchers had found that students’ language proficiency is related to their use of language learning strategies (Gu, Hu, & Zhang, 2005), it is important that the teachers dealing with the Hong Kong students should make sincere efforts for reinforcing suitable strategies, in order to help the students to improve their proficiency in English language.

Variables including gender, grade level and study time can affect their English learning strategies. The teachers should give due consideration to these factors while designing appropriate teaching-learning activities and tailor their strategies accordingly, in order to improve their students’ proficiency in the language. Teachers should also keep the gender differences in mind. The study revealed that females paid more attention to the retrieval and storage of knowledge, and hence their use of memory strategies was the most stable. However, females differed significantly with respect to the ability to retrieve information. In order to help those females with poor memory, classroom-reading training can be provided. On the other hand, teachers should ensure successful completion of the reading tasks for females with good memory and help them to become more proficient in English learning. Males were more aware of the practical nature of the language and viewed its significance from a long-term perspective. The standard deviation of use of social strategies by males was too large and showed polarization in the process of communication. Therefore, it can be inferred that males can be provided with more opportunities for organizing and planning the learning activities. Teachers should make them participate in some classroom learning activities and extracurricular training. Males should be assigned the responsibility to plan, organize, and evaluate the language learning activities to ensure higher degree of engagement. Secondly, there was a significant correlation between cognitive strategies and factors such as grade level and daily study time devoted to learning English, indicating that these factors tend to influence the process of creating the structure of information input and output. Teachers should also understand the significance of the amount of time available to the students and give them adequate time for learning. They should also understand that the needs of students are not the same and hence should be flexible with respect to time. They can allow the weak students extra time, in order to increase their learning competence. For example, students who have been studying English for less than five years should get more time for their study. The teachers should also make sure that they have clarity on the basic concepts. The students having more than five years of English learning experience should be guided so that they become more proficient in the language.

The findings of the study yield some important implications to guide Hong Kong teachers in understanding the English learning strategies adopted by Hong Kong university students and also in designing appropriate EFL teaching-learning activities, planning, and implementing the curriculum. Some questions remain to be answered; for example, in addition to gender, study time, and grade, what are the other factors that affect the use of learning strategies? This calls for future research in this area, with respect to differences in the use of learning strategies by students with different native languages. Further exploration is required to find out whether the native language of the EFL students affects the choice of learning strategies or has any kind of influence on their proficiency in English language.

Disclosure statement

No potential conflict of interest was reported by the authors.