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Abstract

This study investigates the relationship between depth of academic vocabulary knowledge and academic success among Saudi English-as-a-foreign-language university students. Fifty fourth-year university students majoring in English completed a vocabulary depth test, the Word Associates Test (WAT), based on the Academic Word List (AWL). Then, students’ grade point averages (GPAs) were obtained as a measure of academic success. Furthermore, a vocabulary learning strategy (VLS) questionnaire was administered to explore the students’ use of various VLSs. In addition, two focus group discussions were conducted to elicit participants’ views and experiences of English vocabulary learning. The scores on the WAT were positively correlated (r = .407, p < .01) with GPA. Results of the regression analysis show that the WAT scores accounted for 16.6% of the variance in GPA. Analysis of the data on VLSs reveals that the participants were medium-level VLS users who employed metacognitive strategies most frequently. Strategies that involve focused intentional vocabulary learning, such as learning from word cards and wordlists, were reported to be used the least. Results of the present depth study support previous findings of vocabulary breadth studies on the high predictive power of academic vocabulary knowledge in relation to academic success. Implications of the results for academic vocabulary teaching and learning are considered.

Keywords

vocabulary knowledge depth of vocabulary knowledge EFL academic success academic vocabulary vocabulary learning strategies

Introduction

Over the past 40 years or so, second language (L2) vocabulary has increasingly been recognized as a core component of L2 global competence that is central to language teaching and learning. Adequate L2 lexical knowledge is important for the mastery of L2 receptive and productive skills. As McCarthy (1990) put it, “no matter how well the student learns grammar, no matter how successfully the sounds of L2 are mastered, without words to express a wider range of meanings, communication in an L2 just cannot happen in any meaningful way” (p. viii). Research in the field of L2 vocabulary has focused on a wide range of areas including, but not limited to, various dimensions of L2 word knowledge (e.g., Nation, 2020), assessment of vocabulary knowledge (e.g., Read, 2000), the nature of vocabulary teaching and learning (e.g., Schmitt, 2000), vocabulary learning strategies (VLS) (e.g., Schmitt, 1997), and the relationship between vocabulary knowledge and L2 learners’ language proficiency (e.g., Qian & Lin, 2020).

Although a number of studies have explored the relationship between academic English vocabulary size and academic success of second language learners (e.g., Masrai & Milton, 2021), the literature on depth of academic vocabulary knowledge is relatively scarce. The present study, therefore, aims to extend previous research by examining the depth of academic vocabulary knowledge, use of VLSs, and the relationship between depth of academic vocabulary knowledge and academic success of Saudi English-as-a-foreign-language (EFL) university students. Specifically, the current study addresses the following three research questions:

RQ1: What VLSs do English-major Saudi university students report using? What are the most and least used VLSs?

RQ2: What is the academic vocabulary depth of Saudi university EFL students?

RQ3: Is there a relationship between depth of academic vocabulary knowledge and university academic success as measured by students’ GPAs?

Literature Review

This section begins by discussing different aspects of vocabulary knowledge, and then moves on to look specifically at issues pertaining to academic vocabulary. Then, this section considers the relationship of L2 learners’ vocabulary knowledge to university academic success. The last subsection briefly deals with VLSs.

Vocabulary Knowledge

It is widely recognized in the field of vocabulary acquisition that L2 learners’ lexical knowledge is not dichotomous. Rather, knowing a word can be seen on a continuum that ranges from an absence of knowledge to a native speaker-like control of L2 words (Nation, 2013, 2020; Qian & Lin, 2020; Read, 2000; Schmitt, 2000). Nation (2013, 2020) emphasized the complexity and multifaceted nature of vocabulary knowledge and argued that knowing a word involves a variety of nine aspects of knowledge pertinent to the word form (including spoken, written, and word parts), its meaning (including form and meaning, concept and referents, and associations), and its use (including grammatical functions, collocations, and constraints on use).

Two important dimensions from which vocabulary knowledge can be viewed are breadth (or size) and depth (or quality) of word knowledge (Anderson & Freebody, 1981; Nation, 2013; Qian, 2002; Yanagisawa & Webb, 2020). Breadth of vocabulary knowledge refers to the number of words that are known, whereas knowledge depth corresponds to the quality of word knowledge, which refers to how well a certain word is known (Qian, 2002). Accordingly, research studies on the assessment of vocabulary knowledge fall into two major types: studies on vocabulary breadth (e.g., Greidanus & Nienhuis, 2001; Nation, 1983; Schmitt et al., 2001; Webb et al., 2017) and those on vocabulary depth (e.g., Qian, 2002; Read, 1993, 1998; Wesche & Paribakht, 1996). The Vocabulary Level Test (Nation, 1983) and the Word Associates Test (WAT) (Read, 1993, 1998) are arguably the most frequently used tests for measuring breadth and depth of vocabulary knowledge, respectively (Read, 2020; Yanagisawa & Webb, 2020).

Yanagisawa and Webb (2020) pointed out that measuring depth of vocabulary knowledge is important for both educators and researchers alike, because L2 learners’ scores on depth tests facilitate useful feedback on the progress of learners’ vocabulary knowledge as well as on the nature of L2 lexical development. Based on the principle of network knowledge (i.e., relating a word to other words that are known), Read (1993, 1998) developed the WAT as a measure of depth of vocabulary knowledge. The format of the WAT is based on the concept of word associations and incorporates three main types of associations: paradigmatic (synonyms or near synonyms), syntagmatic (collocates), and analytic (representing one component of the meaning of the word). In the present study, the WAT was used to measure students’ depth of knowledge of English academic vocabulary.

Academic Vocabulary

Nation (2001) distinguished four different types of vocabulary: high-frequency words, academic words, technical words, and low-frequency words. In his review of research conducted within the field of L2 vocabulary, Read (2004) categorized research on specific purpose vocabulary beyond the high-frequency lexical items of around 2,000 word families into two major approaches. The first focuses on subtechnical (academic) words that occur frequently in a wide range of academic texts. The second approach is concerned with technical terms specific to a particular field of study.

In her recent review of research on academic vocabulary, Coxhead (2020) highlighted the importance of academic vocabulary and pointed out that academic vocabulary is common to a wide range of academic texts, covering between 10% and 14% of the total words (tokens) in academic texts. In other words, “one word in ten or one word in seven in a line of written academic text might be an academic word” (Coxhead, 2020, p. 97). Therefore, learning such words may be highly useful for students undertaking academic studies in English-medium institutions.

One of the first constructed lists of academic words is the University Word List (UWL) (Xue & Nation, 1984). The UWL consists of 836 word families and accounts for 8% of the words in an academic text. Another well-researched list of academic words is Coxhead’s (2000) Academic Word List (AWL). The AWL is a somewhat smaller list than the UWL, comprising 570 word families and based on a corpus of 3.5 million running words in a wide range of academic texts. The academic words in this list were selected according to three criteria: specialized occurrence, range, and frequency. The AWL is divided into 10 sublists of different frequency counts.

The AWL covers around 10% of the tokens in academic texts. A number of researchers (see, e.g., Coxhead, 2000, 2020; Nation, 2001; Read, 2000) correctly have argued for the importance of the AWL for learners who wish to undertake academic study in English. In this regard, Coxhead and Nation (2001, pp. 254–256) discussed a number of reasons highlighting the importance of the AWL for learners of English for academic purposes.

Academic vocabulary is common to a wide range of academic texts.

Academic vocabulary accounts for a substantial number of words in academic texts.

Academic vocabulary is generally not as well-known as technical terms.

Unlike technical vocabulary that differs from one subject to another, academic vocabulary is used across a wide range of academic disciplines.

Nation (2001) pointed out that learning the 2,000 high-frequency words and the AWL would provide a total coverage of around 90% of the running words in a variety of academic texts. Therefore, direct learning from the 10 sublists of the AWL as well as message-focused learning of this academic vocabulary would give learners “the opportunity to make this important vocabulary a part of their working knowledge of the language and thus help make their academic study more manageable” (Coxhead, 2000, p. 229). The present study uses the AWL, attempts to gauge the participants’ depth of knowledge of this list, and examines its relationship to their academic success.

Vocabulary Knowledge and Academic Success

The relationship between vocabulary knowledge and academic success is both multifaceted and dynamic. Undoubtedly, developing adequate lexical knowledge is essential for competent use of the L2, both receptively (listening and reading) and productively (speaking and writing). As noted by Qian and Lin (2020), due to the complexity of the construct of deep word knowledge, most studies have explored the impact of vocabulary size on academic success. In general, research has shown that vocabulary size is a powerful predictor of academic success (Loewen & Ellis, 2004; Masrai et al., 2021; Milton & Treffers-Daller, 2013; Roche & Harrington, 2013; Szabo et al., 2021). Roche and Harrington (2013), for example, explored the relationship between vocabulary size and academic achievement—with a sample of 70 Omani university EFL students enrolled in English-medium programs. Results of the study detected a positive correlation of 0.3 (p < .01) between vocabulary size as measured by a timed yes/no test (TYN) and students’ GPA. The results show that vocabulary size measure accounted for nearly 25% of the variance in GPA (R² = .234). Similarly, a recent study (Masrai & Milton, 2021) of 61 Saudi EFL university students enrolled in an English language program found that general vocabulary size, as measured by a yes/no test, accounted for 47% of variance in GPA, whereas knowledge of the AWL added a further 11.5% of variance in GPA. In an earlier study, Loewen and Ellis (2004) found that while their overall measure of vocabulary size of English for academic purposes students accounted for 14.8% of the variance in GPA, the UWL level test accounted for 15.8%. The studies reviewed above clearly underscore the importance of L2 academic vocabulary knowledge (as gauged by tests of vocabulary size) as a predictive measure of university academic success.

Nevertheless, it is remarkable that scarcely any studies have examined the relationship between depth of academic vocabulary knowledge and overall academic success. The current study, therefore, extends previous research on vocabulary breadth by examining depth of academic vocabulary knowledge and its relationship to university academic success as measured by students’ GPAs.

Vocabulary Learning Strategies

Language learning strategies (LLSs) refer to those “specific actions taken by the learner to make learning easier, faster, more enjoyable, more self-directed, more effective, and more transferable to new situations” (Oxford, 1990, p. 8). VLSs form a part of LLSs and represent an active area of research on vocabulary. Based on Oxford’s (1990) classical taxonomy of LLSs, Schmitt (1997) developed his well-known taxonomy, which classifies VLSs into five categories: determination, memory, social, cognitive, and metacognitive strategies. The totality of these VLSs comprises the L2 learner’s strategy repertoire employed to deal with new vocabulary learning tasks. Different learners have different VLS repertoires, preferences, and plans as to which and how these VLSs are to be used. Thus, expanding L2 vocabulary and dealing with its unknown words tend to be strategic in nature, involving a decision-making process cycle that requires the choice and use of appropriate VLSs as well as an evaluation of the effectiveness of employed strategies by the individual learner (Gu, 2020).

Research on VLS has shown the important role of individual differences in VLS preferences among L2 learners, because learners themselves exhibit different “cultural and educational backgrounds that perceive certain types of strategies more favorably than others” (Gu, 2020, p. 277). In this connection, Arabic-speaking learners of English tend to face particular issues and challenges when learning English vocabulary due to the wide range of differences (e.g., lexical, morphological, syntactic) between Arabic (L1) and English (L2). English is learned as a foreign language in Saudi Arabia where the EFL learning environment is influenced by a wide range of factors, including, but not limited to, lack of input and output opportunities, influence of the L1, culture, curriculum, and teaching methods. In Saudi Arabia, as one of the many countries within the expanding circle in which English has no official status (Kachru, 1985), English enjoys a special position as the sole foreign language taught in Saudi public schools. It is also widely used in such domains as academia, science, technology, medicine, and international business and commerce. Furthermore, English functions as a lingua franca for communication between Saudis and non-Arabic speakers.

Studies on the use VLSs among ESL students have revealed mixed results in terms of the most and least used VLSs, which appear to be influenced by learners’ background factors. In this connection, a number of studies have explored Saudi ESL learners’ use of VLSs (e.g., Al-Harbi & Ibrahim, 2018; Alqarni, 2018). Alqarni (2018) examined the use of VLSs among a group of 81 Saudi male English major first-year students and found that metacognitive strategies were the most frequently employed category while memory strategies were the least used category by the participants. Overall, the participants were found to be low strategy users (M = 1.63, based on a rating scale ranging from 0 = Never to 4 = Always).

Likewise, Al-Harbi and Ibrahim (2018) explored VLS use among 65 male and female first-year university students majoring in English and found that metacognitive and social strategies were the most used categories among the male participants. The results further indicated that the most frequently employed individual strategies were “I try to remember the word by repeating it several times” and “I try to guess the meaning of the word from the context,” while such strategies as “I ask my English instructor to check my flash cards or word list” and “I use a monolingual dictionary” were the least used ones. Using both a strategy questionnaire and focus group discussions, the current study aims to explore the participants’ EFL vocabulary learning experiences.

Method

Participants

The participants were fourth-year university students majoring in English at a public university in Saudi Arabia. Undergraduate studies at the English department where the participants enrolled follow a 4-year degree plan. Two undergraduate-level classes containing the majority of fourth-year students in the English department were visited during the first semester of 2020. A total of 58 students took the WAT to gauge their depth of knowledge of AWL. The participants were all male, Arabic-L1, Saudi nationals. The mean age of the students was 23.21 years and the students averaged over 10 years of English study (about 7 years at public schools and 3 years at university level). Eight participants were excluded for failing to complete all test and/or questionnaire items. Therefore, the final number of participants was 50.

Instruments

Measure of Vocabulary Learning Strategies

With the aim of capturing participants’ use of various VLSs, a self-reported questionnaire was used. The questionnaire was primarily based on Oxford’s (1990) questionnaire on LLSs and Schmitt’s (1997) questionnaire on VLSs. Adopted questionnaire comprises 30 items, and consists of five parts covering the following range of VLSs:

determination (e.g., use a dictionary),

social (e.g., ask teacher for an Arabic translation),

memory (e.g., connect new words to their synonyms and antonyms),

cognitive (e.g., study word lists), and

metacognitive (e.g., use English-language movies, songs, etc.)

Participants responded to each item by selecting one option on a 5-point Likert scale: “never or almost never true of me” (1 point), “usually not true of me” (2 points), “somewhat true of me” (3 points), “usually true of me” (4 points), or “always or almost always true of me” (5 points). Additionally, qualitative data were obtained from two focus group discussions to shed light on the quantitative data gathered through the strategy questionnaire.

Academic Vocabulary Depth Test

WAT: Depth of academic vocabulary was measured with Read’s WAT (also known as the Word Associates Format). The WAT used in this study was originally developed by Read (1993, 1998) to measure the quality aspect of word knowledge by examining knowledge of the network associations between a given word and other related words (including synonyms, antonyms, and collocations) in the language. The version of the WAT employed in this study was designed to test knowledge depth of the AWL (Morimoto, 2006). In this test, the target words were selected from different frequency counts of Coxhead’s AWL. Only adjectives were used as stimulus words in order to “allow for more consistency in the relationship between the target and the associates” (Read, 1995, p. 5). Accordingly, three adjectives were selected from each of the 10 AWL sublists, making a total of 30 stimulus words. Thus, the test comprised 30 items (30 stimulus words, 90 associates, and 90 distractors). The words were presented in two boxes with varied distributions of the three associates in the two boxes in order to counteract guessing. The participants were asked to choose and circle the three semantically related words for each target word. The total score of the test is 90. The following is an example of the WAT as used in this study (Source: Morimoto, 2006):

significant

In this example, the three associates of the stimulus word “significant” are “change” (a collocation) and “trivial” (an antonym) from the left side, and “important” (a synonym) from the right side. The other three words (honest, intelligent, and dominate) are used as distractors.

Measure of Academic Success

GPA: A student’s GPA indicates their academic success and represents the average result of all courses taken by the student over the course of their study program at a particular institution. At the participants’ university, GPAs are expressed on a 5-point scale (4.5–5.00 = excellent, 3.75–less than 4.5 = very good, 2.75–less than 3.75 = good, 2.00–less than 2.75 = satisfactory, and less than 2 = fail).

Procedure

The researcher visited two classes of fourth-year students to administer the test during the final 50 minutes of a lesson. Previously, students were informed about the aims of the study and were assured of the voluntary and anonymous nature of their participation and that their responses would not influence their course grades. No time limit was given to complete the WAT, and students were not allowed to consult dictionaries or work in pairs. It took them approximately 20 to 30 minutes to complete the test. Students who completed the test also agreed to allow access to their GPAs. After taking the test, participants filled out the VLS questionnaire. No time limit was given, and participants were allowed to ask the researcher for clarification. They spent approximately 15 to 20 minutes on the questionnaire. In the following week, group discussions were conducted. Each focus group included seven students and was led by the researcher. Questions asked centered on the participants’ views and experiences concerning English vocabulary learning. Each focus group lasted about 30 minutes and was recorded and later transcribed for analysis.

Analysis

The WAT was marked with 1 point awarded for each correct answer, with a total of 90 points for the entire test. The questionnaire data were analyzed with the use of descriptive statistics including means and frequencies. Vocabulary test scores were correlated with the GPAs using Pearson product moment. SPSS 21 was used for all statistical analyses in this study. Focus group data were qualitatively analyzed (see, e.g., Miles & Huberman, 1994) to code and categorize the main themes pertinent to students’ vocabulary learning.

Results

Reported Use of Vocabulary Learning Strategies

The results of the VLS questionnaire are shown in Table 1. As the table indicates, metacognitive strategies are reported as the most frequently used VLS category (M = 3.55), followed by memory strategies (M = 3.44), determination strategies (M = 2.79), social strategies (M = 2.90), and cognitive strategies (M = 2.77). According to Oxford’s (1990) strategy use scoring system, the category of metacognitive strategies is the only category that falls into the high level of usage while the other four categories of VLSs were reported to be employed at a medium level. The results further revealed that the three most frequently used individual VLSs were using English-language media, such as movies and songs (M = 4.70), saying new words several times (M = 4.30), and guessing from textual context (M = 4.26). Meanwhile, using flashcards (M = 1.46), studying wordlists (M = 2.14), and keeping a vocabulary notebook (M = 2.22) were reported to be used least commonly.

Table 1.

Results of the Vocabulary Learning Strategies Questionnaire.

Strategy type	N	M	SD	Degree of strategy use	Rank of order of usage
MET	50	3.55	0.68	High	1
MEM	50	3.44	0.79	Medium	2
DET	50	2.97	0.49	Medium	3
SOC	50	2.90	0.91	Medium	4
COG	50	2.77	0.76	Medium	5

Note. MET = metacognitive strategies; MEM = memory strategies; DET = determination strategies; SOC = social strategies; COG = cognitive strategies.

Analysis of the focus group data revealed that participants exhibited the same strategies. All participants emphasized the importance of learning English vocabulary. For example, Ahmad (all student names are pseudonyms) said, “I think vocabulary is really important for learning any language. You cannot really speak or write if you do not have words in your mind. It is like bricks, and one cannot build a house or even a small wall without bricks.” Many of the participants reported that they watch English movies and play video games online, which provide access to authentic meaning-focused vocabulary learning input. They indicated that they learn vocabulary and useful phrases from watching English movies online with and without Arabic/English subtitles. For example, Hassan pointed out that he has learned English vocabulary “from watching English movies; like I watch a movie first with subtitles then I watch again without subtitles so that I can check my understanding.” Another student, Talal, added “I think it is better to watch the movie like two times: one episode with Arabic subtitle and in the second time I switch the subtitles to English.”

Similarly, some participants emphasized the positive role of playing online multiplayer games in enhancing their vocabulary. As noted by Abdullah, “since my childhood I have played video games a lot. Most of these games are narrative-driven games, which include a lot of dialogues and chat and also puzzles …so I have learned a lot of new words.” Khalid added, “when I play online, I meet people from other non-Arabic countries, so we use English as a common language to chat and play. We often use Discord [a free voice, video, and text chat app] and I think many people use it as well.” Another student, Badr, reported that following some English YouTube channels has improved his English vocabulary.

Only one student, Umar, reported using flash cards, “I use flash cards. I put the word on one side and the meaning on the other side and sometimes I write a word with a similar meaning, sometimes I use a picture to associate the word with an image.” None of the participants reported using word lists or a vocabulary notebook.

With regard to their strategies to deal with unknown words, using dictionaries (both monolingual and bilingual) and guessing from context were two strategies commonly reported by the students. For example, Nabeel, said,

I have both paper and electronic dictionaries, but I found that it is easier to use online dictionaries like Merriam Webster’s or Oxford Dictionary. I find about the meaning of the new word and listen to its pronunciation and repeat the word many times until I feel that I become able to pronounce it correctly.

Some students reported using Google Translate to look up their unknown words while others indicated their preference for online English-English dictionaries. I this connection, Talal shared his own experience by stating that,

When I first meet a new word, I use my phone to google that word. I look for its Arabic translation. But I realize that this way is not really effective as I almost immediately forget the meaning of the word. So, I think the best method for learning a new word is first to translate into the language itself by using English-English dictionary so you can read a definition of the word along with its synonyms and also you find information about how it is used and some example sentences.

To deal with this problem of L2 vocabulary learning and forgetting, some students reported that learning new words in phrases (i.e., chunking) leads to improved retention. Hassan, for example, shared his own experience by stating that “I find it easier and more effective to learn new words in phrases because I feel that I learn better in context. It becomes easier for me to remember the phrase than just the individual word.” Another problem articulated by some of the participants is related to lack of output opportunities for practicing their learned words and phrases. As indicated by Umar, such opportunities are relatively scarce in the Saudi EFL context,

The problem we face is that we do not have many chances where we can practice using the words that we have learned. I can maximize my listening and reading but finding ways to practice using these words are limited here. I mean you do not find yourself in a context where you have to use these words. I can say that most of the time I am more of a listener than of a speaker.

Measure of Depth of Academic Vocabulary Knowledge (WAT Scores)

Table 2 reports the descriptive statistics of the scores of the WAT. It shows that the mean score is 61.8 (68.7%). Whereas the maximum score is 82, the minimum score is much lower at 42.

Table 2.

Vocabulary Test Scores.

	N	Minimum	Maximum	M	SD
WAT	50	42	82	61.82	9.718

Measure of Academic Success (GPA Scores)

Table 3 presents the average GPA scores of the participants. GPAs range from 2.52 to 4.74 with a mean score of 3.79 (75.8), which is the equivalent of a C+.

Table 3.

Grade Point Averages.

	N	Minimum	Maximum	M	SD
GPA	50	2.52	4.74	3.79	0.62

Relationship Between Vocabulary Test Scores and GPA

Correlations were computed between the WAT scores and GPAs (Table 4). The scores on the WAT are moderately positively correlated (r = .407, p < .01) with GPA. The regression analysis results show that 16.6% of the variability in GPA can be accounted for by knowledge depth of the AWL as measured by the WAT (R² = .166).

Table 4.

Regression Analysis of WAT Scores and GPA.

Predictor	R	R ²	Adjusted R²	SE of the estimate
WAT	.407^a	.166	.149	0.57043

Discussion

The first research question addresses the types of VLSs employed by the participants. They reported using a variety of VLSs to different degrees (Table 1). The mean value of the overall reported use of VLSs in this study is 3.13, which indicates that the students are medium-level strategy users. On the one hand, this result is contrary to those obtained in Alqarni’s (2018) study on Saudi EFL learners’ use of VLSs, where students’ overall use of VLSs was at a low level. The difference may be attributable to sample: unlike the participants in the current study who were in their final year, Alqarni’s (2018) participants were all first-year students at the beginning of their first semester in their English department and thus, they might have lacked awareness of VLSs and their usefulness as learning tools. On the other hand, the result is in line with some previous studies on EFL university students (e.g., Alqarni, 2018; Ansarin et al., 2012) in that, among all five categories of VLSs, metacognitive strategies were reported to be used most frequently. Among different individual strategies, “watching English-speaking movies” was reported as the most used of all VLSs by the participants in this study and also in Alqarni (2018).

On the other hand, strategies that involve intentional vocabulary learning, such as learning from word cards and wordlists, were reported to be used the least. This is in accordance with the findings of Al-Harbi and Ibrahim (2018), who reported the use of flash cards and wordlists by their Saudi student participants to be among the least employed strategies; this could be attributed to the lack of popularity of such direct VLSs among the students. There are other possible reasons for reported low usage of strategies that involve direct study of words, such as learning from word cards and wordlists. There may be a lack of awareness and classroom guidance on the important role of such strategies in increasing vocabulary size. Another potential possibility for this is related to the fact that many teachers tend to consider direct learning of vocabulary ineffective and not useful vocabulary learning activity (Nation, 2001). However, as argued by Nation (2001), direct learning of vocabulary provides an important complementary kind of learning to other incidental vocabulary learning techniques. It should be noted though that effective use of such explicit VLSs requires training students in their use.

The second research question concerns the level of academic vocabulary depth knowledge among the sample of students. The test used in this study measured learners’ knowledge depth of the AWL. The results show that these students achieved an average score of 61.8 (68.7%; Table 2). Apparently, these students’ academic vocabulary level was not high, which could have been related to the relatively overall low academic performance of the students whose mean score of GPAs was 3.79 (75.8%; Table 3). There is, however, another possible explanation for such a relatively low average score. The results on vocabulary learning strategies show that direct vocabulary learning strategies were reported as the least frequently used strategies by the participants. For example, the mean for employing such a direct strategy as using word cards was the lowest at 1.46. Besides message-focused learning of the academic words, deliberate word learning from word cards and wordlists represents an effective route to academic vocabulary acquisition (Nation, 2001). This finding has important implications for academic vocabulary teaching and learning, as discussed in the next section.

The third research question addresses whether there is any relationship between the students’ academic vocabulary level and academic success. The results show that the GPA correlates significantly with the vocabulary depth test (r = .407). The WAT scores account for 16.6% of the variance in GPA. This finding is unsurprisingly consistent with previous predictive studies on the relationship between academic vocabulary size and academic success, since tests of vocabulary size and depth tend to correlate significantly with each other (Yanagisawa & Webb, 2020). For example, Loewen and Ellis (2004) used the UWL and found that their vocabulary size test accounted for 15.8% of the variance in GPA. Masrai and Milton (2021) used the AWL and reported a percentage of 11.5%. The current study considers depth of knowledge of the AWL and reported a higher percentage (16.6%). Thus, this depth study confirms previous findings on the high predictive power of vocabulary knowledge in relation to academic success.

Conclusion

This study explored the relationship between depth of academic vocabulary knowledge and academic success of EFL university students in Saudi Arabia. The results demonstrate the importance of academic vocabulary knowledge for EFL university students. The depth of an EFL student’s academic vocabulary knowledge functions as a reasonably effective predictor of academic success. In the current study, depth test scores of the AWL accounted for 16.6% of the variance in academic success as measured by GPA. Academic vocabulary knowledge is essential for university undergraduates, English-major students in particular, as it could facilitate understanding of academic texts and lectures. Results of the WAT show that the average score on the AWL was not high, at 61.8 (68.7%). This suggests these students might have experienced difficulty in reading university-level texts.

The results of this study further illustrate that VLSs that involve direct study of words, such as using wordlists and flashcards, are among the least employed strategies. Teachers, therefore, should raise students’ awareness, particularly first-year students, of the important complementary nature of such deliberate VLSs to enhance their knowledge of academic words and consequently their academic performance. Teachers can provide training in these VLSs and also help students discover their preferred strategies and develop them in order to extend their repertoire of VLSs, thereby becoming more autonomous learners who take both responsibility for and control over their vocabulary learning process. This issue becomes even more essential if English is learned in an EFL context.

Obviously, a VLS such as watching English movies, the most used strategy to learn vocabulary reported by the students, is unlikely to provide exposure to academic vocabulary, as the AWL, which comprises specialized subtechnical vocabulary, are outside the first 2,000 most frequently occurring words in English and are unlikely to be used much in movies. These results, therefore, provide support for research outlining the importance of deliberate learning of the AWL due to the value of focused intentional vocabulary learning (Nation, 2001). As Gu (2020, p. 247) pointed out, learning the AWL is “strategically useful” for university students who would benefit from intentional list-learning of these academic words, followed by learning from meaning-focused input through listening and reading activities.

Finally, as noted previously, the depth measure used in the present study (Read’s WAT) employs the lexical network approach to assess the quality of academic vocabulary knowledge. One limitation of the WAT as used in the current study is related to the fact that the test focuses on the knowledge depth of a vocabulary item without context, addressing the network type of deep word knowledge. While it is almost impossible to provide a comprehensive measure of vocabulary depth due to the complexity in conceptualizing such a construct, it remains for future research to consider other developmental and component approaches (see, Yanagisawa & Webb, 2020) to assess EFL learners’ depth of academic vocabulary knowledge, and examine its relationship to their academic success.

Footnotes

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The author received no financial support for the research,authorship,and/or publication of this article.

ORCID iD

Morad Alsahafi

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The Relationship Between Depth of Academic English Vocabulary Knowledge and Academic Success of Second Language University Students

Abstract

Keywords

Introduction

Literature Review

Vocabulary Knowledge

Academic Vocabulary

Vocabulary Knowledge and Academic Success

Vocabulary Learning Strategies

Method

Participants

Instruments

Measure of Vocabulary Learning Strategies

Academic Vocabulary Depth Test

Measure of Academic Success

Procedure

Analysis

Results

Reported Use of Vocabulary Learning Strategies

Measure of Depth of Academic Vocabulary Knowledge (WAT Scores)

Measure of Academic Success (GPA Scores)

Relationship Between Vocabulary Test Scores and GPA

Discussion

Conclusion

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iD

References