Usefulness of Textbook Vocabulary for Reading Academic Texts: A Corpus-Based Case Study

(Mark) Feng Teng, Hong Kong Baptist University

(Mark) Feng TENG is a language teacher educator with extensive experience in China. He is now studying for a PhD degree at Hong Kong Baptist University. He is interested in doing research on vocabulary studies, metacognition and autonomy. His recent publications appeared in Innovation in Language Learning and Teaching and TESL-EJ. E-mail: tengfeng@uni.canberra.edu.au

Menu

Abstract
Introduction
Literature review
Method
Findings
Discussion
Conclusion
Limitations and future research
References

Abstract

Textbooks, which supposedly represent high-frequency words across various disciplines, provide valuable references for teaching English. However, to utilize the textbooks in relation to academic purposes, it is necessary to evaluate the presence of textbook vocabulary in the corpus of academic texts. Input from the textbook series New Horizon English (Zheng, 2011), and 310 different academic texts were analyzed using the computer programs, Range and Frequency (Heatley, Nation, & Coxhead, 2002). Results show that GSL and AWL provided a smaller coverage of vocabulary in general academic corpus than textbooks. A small number of technical words occurred more frequently in general academic corpus, but also contained a very large number of low-frequency words. The GSL and AWL lists provided some overlap between the two corpora, but the vocabulary words beyond both lists had little overlap. Vocabulary in textbooks that go beyond the high frequency words are of little value for learners for academic purposes. This has important pedagogical implications for students, teachers, material writers, and researchers. Supplementary sources of suitable reading for academic purposes are recommended. Keywords: academic texts, GSL, textbook, AWL

Introduction

There has been a growing interest in the corpus-based research of vocabulary, wherein the word lists are analyzed and developed over time. The first remarkable list, which contained 1,964 widely-used word families, was known as the General Service List (GSL) (West, 1953). This list is a classic collection of high-frequency English words, and is of significance to initial English courses. The University Word List (UWL) was the first attempt for orienting learners from the GSL towards a more academic vocabulary (Xue & Nation, 1984). An in-depth Academic Word List (AWL) containing 570 semantic fields was further established for learners advancing to academic study (Coxhead, 2000). New specialized word lists were also created for fields such as: engineering (Mudraya, 2006), medical (Wang, Liang, & Ge, 2008), finance (Li & Qian, 2010), and applied linguistics (Vongpumivitch, Huang, & Chang, 2009). A new academic vocabulary list (NAVL) was derived from an academic subcorpus of 425-million-word Corpus of Contemporary American English (Gardner & Davies, 2013). A New General Service List (NGSL) was recently developed (Browne, 2013). It contained 2,368 word families by using Level 6 of Bauer and Nation’s (1993) word family taxonomy. The words in the GSL cover around 80% of academic texts and newspapers, and around 90% of conversation and novels (Chung & Nation, 2003). There have been some doubts on its adequacy because of its age and relatively small coverage (Brezina & Gablasova, 2013). Hence, a new General Service List (NGSL) was created. According to Browne (2013), “The 2,368 word families in the NGSL provide 90.34% coverage while the 1,964 word families in the original GSL provide only 84.24%” (p. 16). Beyond the high-frequency words of the NGSL, a student of English who wishes to continue academic studies needs the list of 570 word families known as the Academic Word List (AWL) (Coxhead, 2000). It covers around 8.5% of the running words in academic texts. A learner who acquires GSL and AWL words have about a 90% coverage of academic texts.

Schmitt (2010) divided vocabulary into four levels: high-frequency words, academic vocabulary, technical vocabulary, and low-frequency words. There is a common consensus that English learners need to first focus on the words that appear most often in printed materials (high-frequency words) (Hu & Nation, 2000; Nation, 2006), such as the General Service List (GSL). This is of practical use to language teachers as well as curriculum planners, and is the resource for contriving simplified reading materials for students who learn English as a Foreign Language (EFL) (Carter, 2012).

However, much research has shown that at least 95% coverage of a text is needed to achieve reasonable comprehension or to infer meaning of unknown words from context (e.g., Hu & Nation, 2000; Laufer & Ravenhorst-Kalovski, 2010; Teng & He, 2015; Van Zeeland & Schmitt, 2012). To achieve this coverage, an EFL student should advance their word level to the third and fourth levels. The third level of vocabulary is technical vocabulary, which are the words that occur frequently in a specialized area but either do not occur or occur less in other fields. Technical vocabulary covers about 5% of the running words in specialized texts. The fourth level of vocabulary is the low-frequency words, which also typically cover around 5% of the running words in texts (Nation, 2013).

The introduction of various kinds of word lists has enriched our understanding of how likely words are to be used in different fields. Indeed, the release of word lists has been a yardstick for illuminating the teaching of vocabulary (Nation, 2013). Likewise, it is widely acknowledged that vocabulary supports reading fluency and comprehension (Nation & Angel, 2006), and learners should be introduced to the appropriate authentic input for acquiring the target language (Gilmore, 2007; Teng, 2014). The issue of controlling vocabulary level has been highlighted in the development of materials for vocabulary teaching and learning, such as in graded readers (Nation, 2013) and textbooks (O’ Loughlin, 2012), and there is now a collection of vocabulary research studies demonstrating how knowledge of high frequency words is important for text coverage (e.g., Beglar, 2010).

Recently, in line with a sustained interest in corpus linguistics and vocabulary teaching, Coxhead (2008, 2014) has argued for a more phraseological approach to probe deeper into analyzing more discourse contexts in relation to word lists. To EFL learners, the currently most important and assessable input appears to be textbooks (Byrd, 2001). However, textbooks seldom address vocabulary sufficiently (Lessard-Clouston, 2013). This may result in a gap between the vocabulary load of EFL textbooks and academic texts. Therefore, it is essential to conduct a corpus-based study and understand the vocabulary in EFL textbooks. The present study focused on analyzing the relationship between curriculum-based textbooks and the academic texts corpora. This provides guidelines for how vocabulary lists in the textbooks can be helpful for reading academic texts.

Literature review

Along with the development of computer technology, research in corpus linguistics has become popular (Simpson & Swales, 2001). The contribution of corpus linguistics to EFL teaching and learning is related to the importance that it puts on the large databases of language (Tognini-Bonelli, 2001). Most importantly, it describes how language items are used in textbooks. These descriptions are especially important for EFL teaching as textbooks play an important role in EFL students’ learning. As argued by Kwon (2002), textbooks for EFL learners and teachers have commonly included incomplete or misleading explanations. They also suggest that textbooks do not always reflect native-like use of certain discourse functions. Another branch of research that has emerged from corpus linguistics is related to the generation of word lists in vocabulary learning. With the application of corpus linguistics, it has become possible to enumerate the words that are common across a variety of academic texts. In this connection, it is no longer surprising to know that learners need to have a high coverage of words in order to read academic texts. For example, Nation (2006) noted that, if 98% coverage of a text is needed for unassisted comprehension, a vocabulary of 8,000 to 9,000 word families is needed for comprehension of written text and a vocabulary of 6,000 to 7,000 for spoken text.

In an early study conducted by Cobb (1995), he analyzed The New Cambridge English, a set of EFL course books. His study provided a lexical match with Hindmarsh’s (1980) Cambridge English Lexicon, which is the basis for the Cambridge PET test. The result was counter-intuitive because together, these different series of course books only covered 1,284 (53.5%) of the PET’s 2,400 words. Thus, Cobb argued that these course books do not provide sufficient lexical coverage for passing the Cambridge PET test. This contradicted the Cambridge course book writer’s proposal that each additional course book added roughly 350 new PET words, thus accumulating 2,400 words by the end of Book 6.

Eldridge and Neufeld (2009) evaluated the vocabulary profile of the textbooks and graded readers. Results revealed that textbooks contained few vocabularies that are of value to EFL learners. In this regard, vocabulary development is limited when learning is only from textbooks. Likewise, Cobb (2008) analyzed over 375,000 running words in a series of graded readers and purported that “Reading these texts in their entirety cannot provide enough repeated exposures to enough 3,000-level vocabulary words to support the acquisition of a minimal functional lexicon” (p. 109). Thus supplementary reading materials within a framework of corpus-based studies remains a necessary method of vocabulary acquisition, e.g., through computer-based text design and computational enrichment of texts (Cobb, 2007).

O’ Loughlin (2012) collected input from three levels of the course book series, New English File, and found that there were many words in the textbooks that appeared to be of little use to EFL learners. He thus concluded that over the course of 3 years of using these texts, fewer than 1,500 of the frequent words of the General Service List (GSL) would be introduced. In addition to this, over half of the words outside of the GSL occur only once in the textbook series, indicating that teachers and learners would be forced to spend a lot of time on low-frequency words. To avoid this, “Teachers should guide learners towards supplementary sources of suitable reading material” (O’ Loughlin 2012, p. 265).

The above-mentioned studies show much useful information, such as word frequency counts, essential lexical coverage for reasonable reading comprehension, and important word lists. The above-noted studies also point out that some textbooks are not suitable for learners. However, there is little published information investigating a match between the vocabulary students learned from textbooks and the vocabulary collected from academic texts. This also indicates that there is a lack of comprehensive corpus-based studies of textbooks in the Chinese EFL context. In addition, there has been little discussion of technical vocabulary and low frequency words (Chung & Nation, 2003).

Whenever English is taught as a foreign language for academic purposes, classes are made of learners who are required to acquire English from textbooks. Such classes are often taught from a series of textbooks with the expectation students will acquire relevant experience in grammar, vocabulary, and discourses that are useful for academic purposes. Research has found that EFL textbooks rarely include adequate words for learning English (Teng, 2015). The present study was undertaken to determine the extent to which vocabulary used in EFL textbooks resembles the vocabulary used in academic texts. The assumption behind this study was that learners needed to increase their vocabulary to a certain level for reasonable comprehension. In this case, familiarity with more than 95% of the running words will make this possible (Nation, 2013). Although the two corpora were compared on a small scale, this study can evince the kinds of insight which corpus-based comparison provides for applied linguistics purposes. As such, coherent texts were turned into lists of seemingly unrelated words so that information gained can provide insight into different aspects of difficulties faced by learners in comprehending academic texts. This original and innovative research also helped us understand whether studying textbooks is useful for learners who want to read academic texts, and whether teachers should guide learners with an academic purpose towards supplementary sources of suitable reading material. By comparing the vocabulary of the two corpora, this study aims to answer the following research questions:

1. How large a vocabulary is needed to have a reasonable comprehension of the textbooks?
2. Does having learners read a range of academic texts impose too high a vocabulary burden on them?
3. How important are the low-frequency words in comprehending academic texts?
4. What is the importance of studying textbooks for learners who want to read academic texts?
5. How important is the technical vocabulary in comprehending academic texts?

Method

The Features of the Two Corpora

The two corpora that this research was based on were a series of university textbooks, New Horizon English (Zheng, 2011), and a corpus of a similar length consisting of 310 different academic texts (each about 1,000 words long), retrieved from a variety of fields including business, medicine, sports, entertainment, health, technology, science, engineering, and culture. The series of textbooks are regarded as the most popular textbooks in China, and commonly used for intermediate and advanced EFL tertiary-level students. Table 1 concludes the features of the two corpora. For convenience, the corpus consisting of the EFL textbooks is called the “textbook corpus.” The collection of 1,000 word academic texts is called the “general academic corpus.”

The textbook corpus represents an English collection of textbooks. The general academic corpus is a representation of an English collection and resources from various academic disciplines.

Procedure

The publisher’s permission was obtained to scan the textbooks into a computer database. The general academic corpus consisted of a wide range of academic texts. These consist of academic essays written by learners of English from a variety of first language backgrounds. The general academic corpus also consisted of BBC online news (www.bbc.com), which were collected in 2014. These analyses were conducted through the Range and Frequency programs (Heatley, Nation, & Coxhead, 2002). Some benefits of these programs include the ways to determine the coverage of a text by certain word lists, create word lists based on frequency and range, and discover shared and unique vocabulary in several pieces of writing. The computer programs are freely available from Paul Nation’s website.

Findings

Question 1: How large a vocabulary is needed to have a reasonable comprehension of the textbooks?

Table 2 includes the results of comparing the two corpora. The two corpora were compared in terms of length (running words, also called tokens); the number of different types (also called word forms); and the number of different word families (includes the base word plus its inflected and derived forms; e.g., teach, teaches, teaching, taught, and teacher were all counted as members of the same word family).

In spite of the corpora being roughly the same length, 302,459 words and 313,829 words, there is a striking difference in their vocabulary size with the general academic corpus contained well over twice as many word families as the textbook corpus. This suggests that if the vocabulary of the general academic corpus represents the vocabulary to be learned in an English course then the students would be faced with an enormous vocabulary load. In answering the first question, learners needed 6,828 word families to have a reasonable comprehension of the textbooks.

Question 2: Does having learners read a range of academic texts impose too high a vocabulary burden on them?

Findings shown in Table 2 also provides evidence to address the second research question. As noted above, the two corpora were roughly the same (302,549 vs. 313,829 running words). However, the general academic corpus contained at least 6,034 word families that the learners would not encounter in their textbooks. This accounts for 46.9% of the total 12,862 word families in the general academic corpus, indicating that learning the series of textbooks would result in learning many vocabulary words that are of no value in general academic settings. This also revealed that learners would have to focus on the language or vocabulary of particular academic texts after they master the vocabulary in the textbooks.

Question 3: How important are low-frequency words in comprehending academic texts?

Table 3 shows the number of low-frequency word families occurring only one time, up to 20 times in the two corpora.

Table 3 shows that the general academic corpus had more word families than the corpus of textbooks for the low-frequency levels of 1 to 20 occurrences. This is evident that learners with academic purpose would continually encounter words that they would either encounter them a few times or even never.

Question 4: What is the importance of studying textbooks for learners who want to read academic texts?

Table 4 shows evidence as to how well the textbooks corpus prepares a learner for the general academic texts.

Table 4 shows that there was a remarkable difference in the distribution of high-frequency level word families in the two corpora. The general academic corpus appeared to have more word families for the frequency level of up to 600 times. However, the corpus of textbooks included more word families after the 600- frequency level. This is an indication that learners who focus mainly on academic texts would encounter fewer high-frequency words than when studying textbooks.

Table 5 includes the coverage of three word lists in both the corpora of textbooks and in general academic texts. The first and second thousand words are high-frequency words belonging to the GSL, while the third thousand words are academic vocabulary known as the AWL. Table 5 shows that the corpus of textbooks consist of a larger number of word families in the first 1,000-word level than the general academic corpus. The textbooks also had a larger coverage at the 1,000-word level.

A difference is noticed at the second 1,000 and AWL levels, with the general academic corpus having both a larger number of word families and coverage, which means that these words and the subtechnical vocabulary (represented by the AWL) are more important in the general academic corpus. Despite the slight difference between the two corpora, the vocabulary in the GSL and AWL lists are still of importance to students who are studying textbooks. Therefore, it is still valuable to learn the series of textbooks that covers most of the vocabulary in the two lists.

A major difference between the two corpora is the words not found in the above lists. For example, the general academic corpus has more word families not found in the word lists (the GSL and AWL). The percentage of coverage provided by these words differs significantly (6.63% vs. 14.04%). However, the difference in the actual number of families is more significant (6,828 vs. 12,862). Therefore, beyond the two word lists (GSL and AWL), there is little value in using textbooks for specific academic purposes.

Question 5: How important is technical vocabulary in comprehending academic texts?

As mentioned above, technical vocabulary is useful for a specific area of knowledge. It can be described as vocabulary with a higher frequency of occurrence in a specific discipline than its relative frequency over a range of disciplines. It can be concluded that, words that occur much more frequently in the general academic corpus than they do in the textbook corpus, or the words that occur frequently in the academic corpus and which do not occur in the textbook corpus, are the technical vocabularies that need to be studied.

It was estimated that the academic corpus contained 550 technical words in general (See the 39 items in Table 6). These words were chosen because they occurred frequently in academic corpus but infrequently in textbooks. English teachers can facilitate students to deal with these technical vocabulary words, perhaps drawing attention to their generally narrow meaning and pointing out their use in the specialized text.

Discussion

Re-examining the results of the analysis in Table 2 shows that a learner who follows the textbook series, New Horizon English, will be exposed to about one half of the words in academic texts, leaving them a heavy vocabulary burden in comprehending academic texts.

The GSL and AWL are of great value in providing coverage of the vocabulary in both textbooks. The general academic corpus provide more than 90% of coverage in textbooks, and more than 80% of coverage in general academic corpus. Similar results were also found in previous studies (Brezina & Gablasova, 2013; Carter, 2012). Therefore, there is a need for learners to focus on both lists. Interestingly, the GSL provided a rather low cumulative coverage in the academic texts in comparison with the textbook corpus (see Table 5). One reason may be the large number of technical words appearing in this academic text corpus. This suggests that learners need another kind of vocabulary, namely technical words as well as high frequency and academic words to understand various academic texts. Chung and Nation’s (2003) study supports this. They found a high percentage of technical vocabulary in their anatomy texts (37.6%). Therefore, there is a value in teaching technical words that occur in general academic corpus (Gablasova, 2015). This can help learners better comprehend academic texts. This also suggests that when learners are familiar with the GSL and AWL, they should receive some trainings with specific purposes, such as, learning technical words.

Understanding low-frequency words in general academic corpus is also important because these words account for about 14% of total words. Previous studies have provided a strong argument for pre-learning low frequency words. It is suggested that if learners knew the most frequent 3,000 word-families and pre-learned low-frequency vocabulary, comprehension may increase (Webb, 2010). Although some words in the GSL and AWL are considered useful, there are still many low-frequency words in the general academic corpus. The following is a selection of some of the off-lists words that occurred ten times in general academic corpus: conceive, scrappy, sublimate, irreparable, caprice, vicissitude, fortuitous, ominous, audacious, conundrum, altruistic, contagious, exponential, insomnia, miscellaneous, reciprocity, surmise, hereditary, invasive, inundate, invigorate, wrangle, collateral, amputate, transparency, avalanche, barricade, blunder, constellation, camouflage, conscientious, cosmopolitan, fraudulent, grenade, sarcastic, remorse, tedious, and vantage.

The results of the present study have pedagogical implications for learners, teachers, material writers, and researchers. First, tertiary-level language learners in an EFL context who are attending English courses typically take four years to complete the course requirements. It is assumed that by only textbooks, that they would be exposed to 86% of the words in general academic corpus. This suggests that learners who had finished learning these series of textbooks would still encounter 14% of unknown words while reading academic texts. Based on previous studies that 95% of the words are needed to achieve reasonable comprehension (Schmitt, 2010), it would be difficult for EFL learners to guess the meaning of unknown words and comprehend academic texts. Although no study has been conducted as to the significance of gap of 86% and 95% will have on the effect of reading comprehension, Hu and Nation’s (2000) study showed that the relationship between lexical coverage and reading comprehension is critical. They created four coverage groups (80%, 90%, 95%, 100%) by replacing some text words with non-words. The other words of the text belonged to the 2,000 most frequent vocabulary, which were known by the participants. They used two comprehension tests. Results showed that nobody could read adequately at 80% of coverage, some learners could at 90% coverage, but they were in the minority. The argument is that at least 95%, or ideally, 98%, is the lexical coverage for reasonable reading comprehension. Thus, learners need to form an awareness of accessing more vocabulary than is present in textbook levels. Second, teachers should guide learners with a specific purpose to study words that are considered useful. This is in tune with O’ Loughlin’s (2012) finding that supplementing specific reading materials for learners with an academic purpose is highly encouraged. Unfortunately, many EFL learners fail to see the usefulness of having a substantial amount of exposure to reading materials. Therefore, it is incumbent on teachers to raise their students’ awareness on this. Likewise, more emphasis should be placed on vocabulary development. This can be achieved in a range of ways on direct teaching and learning. In this regard, the teacher should provide information on how to use deliberate learning strategies, e.g., flashcards or the keyword technique (Nation, 2013). Vocabulary learning does not need to proceed at a slow pace, and that teachers can foster faster word learning progress through using word lists, as well as encouraging deliberate learning of word pairs, thus providing learners with access to a lot more vocabulary than is present in early textbook levels. Third, material writers should take advantage of research-based information and ensure that the learners are introduced to the words beneficial to them. As the importance of the most frequent words and their value to learners is clear, and textbook writers are in a position to ensure these words are available to learners. They could also incorporate word lists after each unit and provide frequency information for each word. Furthermore, they could include strategies for deliberate learning of the word lists. It should also be noted that textbooks influence teacher education and this would serve to raise the teacher’s awareness of the importance of these items (Rubdy, 2003). Fourth, researchers should know the importance of “using corpora to inform vocabulary teaching and learning” (Lessard-Clouston, 2013, p. 36). As McCarthy (2008) stated, “The corpus revolution is here to stay and teacher education cannot afford to sideline it” (p.573). Hence, it should be a priority for researchers to evaluate the materials that are corpus-informed, automate skills of evaluation, and become active revolutionaries in corpus research.

Conclusion

Vocabulary is one component that learners should think about because it consumes most of their learning time. The learning process of vocabulary is also one component that deserves attention from learners, teachers, material writers, and researchers. The purpose of this study was to direct attention to the proper areas.

First, learners need at least 6,828 word families to have a reasonable comprehension of this series of textbooks. Second, the general academic corpus contained at least 6,034 word families that the learners would not encounter in their textbooks. This is evident that reading a range of academic texts imposes a big vocabulary burden to learners. Third, GSL and AWL provided a smaller coverage of vocabulary in the general academic corpus than in textbooks. Thus vocabulary in textbooks that go beyond the high frequency words are of little value for learners with academic purposes. Finally, the academic corpus contained more low-frequency words and technical vocabulary than the textbooks. This shows the importance of low-frequency words and technical vocabulary in comprehending academic texts.

Therefore, in order to facilitate student comprehension of academic texts, teachers should be mindful of the use of textbooks, add supplementary reading materials and focus on some technical and low-frequency words.

Limitations and future research

First, the present study was unavoidably affected by the limitations in using the Frequency and Range programs to analyze the data (Nation & Webb, 2011). For example, the Range program is inconsistent in dealing with compound words. It may classify some low-frequency words as high-frequency words (e.g., apostrophe). As noted above, more current vocabulary lists—NGSL and NAVL—have been made. Yet the current Range and Frequency programs still stick to the GSL and AWL lists. Second, some technical words in the general academic corpus occurred both frequently and infrequently. Defining both types of technical words in the general academic corpus using the same method will make the present study more inclusive. However, that needs a predetermined list of words that can be explored in future research. Third, the textbooks included for the analysis may be different from other series of textbooks. More research needs to be done on a larger amount of textbooks. In addition, the textbook corpus is from one author. The academic texts are too diverse with subject matters ranging from humanity to natural science. Future studies using a more careful design of corpora should be done. Finally, this study simplifies the factors that are involved in judging a learner’s comprehension of a text. It is commonly known that vocabulary is not the only factor; one has to take subject matter, sentence pattern, and semantic density into consideration. This one-sided claim that knowing a huge portion of vocabulary will guarantee the comprehension should be cautious.

References

Bauer, L., & Nation, I. S. P. (1993). Word families. International Journal of Lexicography, 6(4), 253–79.

Beglar, D. (2010). A Rasch-based validation of the vocabulary size test. Language Testing, 27, 101-118.

Brezina, V., & Gablasova, D. (2013). Is there a core general vocabulary? Introducing the New General Service List. Applied Linguistics, 36, 1-22.

Browne, C. (2013). The new general service list: Cerebrating 60 years of vocabulary learning. The Language Teacher, 37(4), 13–16.

Byrd, P. (2001). Textbooks: Evaluation for selection and analysis for implementation. In M. C. Murcia (ed.), Teaching English as a second or foreign language (pp. 415–427). Boston, MA: Heinle.

Carter, R. (2012). Vocabulary: Applied linguistic perspectives. London: Routledge.

Chung, T. M., & Nation, I. S. P. (2003). Technical vocabulary in specialized texts. Reading in a Foreign Language, 15(2), 103–116.

Cobb, T. (1995). Imported texts: analyzing the task, TESOL (Arabia). Al-Ain, United Arab Emirates. Available at: http://www.lextutor.ca/cv/Al-Ain.html

Cobb, T. (2007). Computing the vocabulary demands of L2 reading. Language Learning & Technology, 11(3), 38–64.

Cobb, T. (2008). What the reading rate research does not show: Response to McQuillan & Krashen. Language Learning & Technology, 12, 109–114.

Coxhead, A. (2000). A new academic word list. TESOL Quarterly, 34(2), 213–238.

Coxhead, A. (2008). Phraseology and English for Academic Purposes: Challenges and Opportunities. In F. Meunier, & S. Granger (eds.), Phraseology in language learning and teaching (pp. 149–161). Amsterdam, Philadelphia: John Benjamins.

Coxhead, A. (2014). Corpus linguistics and vocabulary teaching: Perspectives from English for Specific Purposes. In M. Gotti (ed.), Corpus analysis for descriptive and pedagogical purposes (pp. 289–301). Bern, Switzerland: Peter Lang.

Eldridge, J., & Neufeld, S. (2009). The graded reader is dead, long live the electronic reader. The Reading Matrix, 9 (2), 224–244.

Gablasova, D. (2015). Learning technical words through L1 and L2: Completeness and accuracy of word meanings. English for Specific Purposes, 39, 62-74.

Gardner, D., & Davies, M. (2013). A new academic vocabulary list. Applied Linguistics, 35(3), 305–327.

Gilmore, A. (2007). Authentic materials and authenticity in foreign language teaching. Language Teaching, 40(2), 97–118.

Heatley, A., Nation, I.S.P., & Coxhead, A. (2002). RANGE and FREQUENCY programs. Available at http://www.vuw.ac.nz/lals/staff/Paul_Nation

Hindmarsh, R. (1980). Cambridge English lexicon. Cambridge: Cambridge University Press.

Hu, M., & Nation, I. S. P. (2000). Unknown vocabulary density and reading comprehension. Reading in a Foreign Language, 13, 403–430.

Kwon, I. S. (2002). A corpus-based lexical analysis of middle school English textbooks. English Teaching, 57(4), 409-444.

Laufer, B., & Ravenhorst-Kalovski, G. C. (2010). Lexical threshold revisited: lexical text coverage, learners' vocabulary size and reading comprehension. Reading in a Foreign Language, 22, 15–30

Lessard-Clouston, M. (2013). Teaching vocabulary. Alexandria, VA: TESOL International Association.

Li, Y. Y., & Qian, D. D. (2010). Profiling the Academic Word List (AWL) in a financial corpus. System, 38, 402–411.

McCarthy, M. (2008). Assessing and interpreting corpus information in the teacher education context. Language teaching, 41(4), 563–574.

Mudraya, O. (2006). Engineering English: a lexical frequency instructional model. English for Specific Purposes, 25(2), 235–256.

Nation, I. S. P. (2006). How large a vocabulary is needed for reading and listening? The Canadian Modern Language Review, 63, 59–82.

Nation, I. S. P. (2013). Learning vocabulary in another language (2nd edition). Cambridge: Cambridge University Press.

Nation, K., & Angel, P. (2006). Learning to reading and learning to comprehend. London Review of Education, 4, 77–87.

O’Loughlin, R. (2012). Turning in to vocabulary frequency in course books. RELC Journal, 43(2), 255–269.

Rubdy, R. (2003). Selection of materials. In B. Tomlinson (ed.), Selection of Materials (pp. 37-57). New York: Continuum.

Schmitt, N. (2010). Researching vocabulary: A vocabulary research manual. Basingstoke, England: Palgrave Macmillan.

Simpson, R., & Swales, J. (2001). (Eds.). Corpus linguistics in North America: Selections from the 1999 symposium. Ann Arbor: University of Michigan Press.

Teng, F. (2014). Research into practice: Strategies for teaching and learning vocabulary. Beyond Words, 2(2), 41–57.

Teng, F. (2015). An evaluation of EFL students’ vocabulary size and their textbooks: A case study of vocational college students in China. Humanizing Language Teaching, http://old.hltmag.co.uk/oct15/mart03.htm

Teng, F., & He, F. (2015). Towards effective reading instruction for Chinese EFL students: Perceptions and practices of lexical inferencing. The English Teacher, 44(2), 56-73.

Tognini-Bonelli, E. (2001). Corpus linguistics at work. Amsterdam: Benjamins.

Van Zealand, H., & Schmitt, N. (2012). Lexical coverage in L1 and L2 listening comprehension: the same or different from reading comprehension. Applied Linguistics, 34(4), 457–479.

Vongpumivitch, V., Huang, J.Y., & Chang, Y.C. (2009). Frequency analysis of the words in the Academic Word List (AWL) and non-AWL content words in applied linguistics research papers. English for Specific Purposes, 28, 33–41.

Wang, J., Liang, S. L., & Ge, G. C. (2008). Establishment of a medical Academic Word List. English for Specific Purposes, 27(4), 442–458.

Webb, S. (2010). Pre-learning low-frequency vocabulary in second language television programs. Language Teaching Research, 14(4), 501-515.

West, M. (1953). A General Service List of English words. London: Longman, Green & Co.

Xue, G. Y., & Nation, I. S. P. (1984). A university word list. Language Learning and Communication, 3(2), 215–229.

Zheng, S. T. (2011). New Horizon English. Beijing: Foreign Language Teaching and Research Press.

Please check the English Language Improvement for Teachers course at Pilgrims website.
Please check the English Language Improvement for Adults course at Pilgrims website.
Please check the Teaching Advanced Students course at Pilgrims website.