eap reading and lexis for thai engineering undergraduates

Journal of English for Academic Purposes 8 (2009) 294e301www.elsevier.com/locate/jeap

EAP reading and lexis for Thai engineering undergraduates

Jeremy Ward

Suranaree University of Technology, 111 University Avenue, Muang District, Nakhon Ratchasima 30000, Thailand

Abstract

EAP programmes typically aim to enable students to read their academic textbooks. In Thailand this has become a matter ofpolicy for both the government and the university, and has implications well beyond the need for students (especially undergraduatestudents) to graduate. This study presents evidence that this aim is an ideal which cannot in present circumstances be attained. Thestudy estimates average student vocabulary knowledge to cover only half the General Service Word List, and less than half ofa foundation engineering word list e way below the level necessary for effective reading. Suggestions are made for dealing with theproblem.� 2009 Published by Elsevier Ltd.

Keywords: EAP; reading; engineering; vocabulary; Thailand

1. Background

For at least fifty years it has been the received wisdom that Thai engineering undergraduate students need to readEnglish language textbooks (Sagarik, 1978; Sri-saarn, 1998; Sukontarangsi, 1967; Tiranasar, 2000). Howevernowadays, as a visit to a Thai university library will reveal, more and more Thai language engineering textbooks arebeing written, especially at the lower undergraduate levels. This is no doubt because of the difficulties Thai under-graduate students have with reading English language engineering textbooks, difficulties which are shared with manyother developing nations and have been written about frequently over the years (e.g. Anwar, 1994; Brown, 1988; Cobb& Horst, 2001; Cohen, Glasman, Rosenbaum-Cohen, Ferrara, & Fine, 1988; Cooper, 1984; Dharmapriya, 1988;Dlaska, 1999; Flowerdew, 1993; Hassan, Neilson, & Thomas, 1986); such situations form at least part of the raisond’etre of EAP courses. Another reason for the appearance of Thai language textbooks is that for Thai lecturers, writing(or translating from English) a textbook is a big step towards promotion to a highly prestigious professorship.

1.1. Is EAP still necessary?

The existence of these Thai textbooks means that it is nowadays not so obvious that Thai engineering studentsshould have to read English textbooks in order to graduate, or to master the basics of their field. But there are still othercompelling reasons for him/her to do so; first, those who aspire to successful engineering careers may either want to

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295J. Ward / Journal of English for Academic Purposes 8 (2009) 294e301

work for foreign companies, which will necessitate consulting with foreign engineers, or will in any case want to keepup with new developments in their fields, which will almost certainly involve consulting English language sources.

Second, looking at the wider context, it is a cornerstone of Thai economic policy that technology transfer fromdeveloped nations should obviate the necessity for endlessly importing machinery needed for economic development(Sri-saarn, 1998; Tiranasar, 2000). A recent paper about university/industry cooperation and technology transferspeaks of Thailand as ‘‘.just at the point of losing its comparative advantage as a low-cost production site, thusfeeling the pressure to accelerate technological upgrading.’’ (Liefner & Schiller, 2008:277). The obvious conduits forsuch transfer (upgrading) are university-educated Thai engineers with access to English language technology sources;it is difficult to think of another group of people more likely to fulfil this role. But ‘‘Due to outdated curricula,textbook-based teaching, inadequate research capabilities and user feedback, many graduates have low problemsolving skills, are not able to think laterally, and fall short in English language and other soft skills.’’ (Liefner &Schiller, 2008:278).

A final justification for EAP is that Thai engineers wishing to study at the graduate level e whose problems withEnglish are well documented (Tubtimtong, 1999) e will certainly need to consult English language sources. At thevery minimum they will be obliged, when writing their theses, to undertake some kind of literature review, which willbe difficult without access to western technological literature.

Note here that the reader is not being asked to believe that all useful knowledge comes from the west (or Japan), northat development based on western technology is the only way forward. But pace the critical perspective, it is hardlydisputable that Thai engineering students could do well to use at least part of their undergraduate years learning to readengineering textbooks in English.

1.2. Reading and lexis

As far as reading goes, the importance of vocabulary knowledge is hardly in dispute. We may look at the well-established psycholinguistic research (see e.g. Perfetti, 1985) suggesting first, that skilled readers focus on 80% ofindividual content words, and second, that the less time is spent processing individual words, the more mental capacityis freed up for higher-level types of information processing (verbal efficiency). We might also consider the verycommon behaviour of students who write L1 glosses over unfamiliar words in English texts, a phenomenon noted forat least the past 40 years (see Nation 2001:188 for sources). We might even adduce the common sense proposition thatfor reading a language, the more words you know, the better. This is not to claim that vocabulary is the only, or evennecessarily the most important, problem facing these Thai students; but since words may be said to represent the mostbasic level of meaning, it is perhaps the most pressing one.

1.2.1. Quantifying the problemOne obvious step towards solving the lexical problem described above is to quantify it. We may summarise the

tentative conclusions from research in this area thus:

1. There may exist a threshold of language knowledge (grammar and vocabulary) below which readers are unableto utilize their L1 reading skills to read L2 (Alderson, 1984; Laufer, 1989).

2. Applying the threshold idea specifically to lexis, some research has claimed that readers may need to knowa certain proportion of the running words in an English text to be able to read it effectively. In (among others)Laufer (1989), and Nation and Waring (1997), this proportion was claimed to be 95%, a figure which, accordingto Coxhead and Nation (2001), also applies to academic reading. In more recent work (e.g. Hu & Nation, 2000)the threshold was put at 98%. However the latter estimate was for ‘‘extensive reading for language growth’’(p. 423), where uninterrupted reading is more to be expected and desired than in intensive, academic reading,where students are reading technical material demanding precise knowledge of terminology. It is perhaps naturalfor this latter type of reading to be more ‘‘interrupted’’ and thus less dependent on sight knowledge ofvocabulary. Related to this is the point that the Hu & Nation study takes the ‘‘..somewhat extreme position.’’(Hu & Nation, 2000:423) that subjects had no access to dictionaries or glossaries. For these reasons we will takethe lower 95% figure as the benchmark for purposes of this study. This is an important claim e since we cancount how many words are in books, and get at least some idea of how many words a reader knows, we may beable to quantify one important variable affecting the readability of texts for the individual student.

296 J. Ward / Journal of English for Academic Purposes 8 (2009) 294e301

3. Depending on the type of text, the reader may need to know about 3000 word families to have 95% text coverage(Nation & Waring, 1997). (Of course the number increases greatly if 98% coverage is considered necessary).

Returning to the Thai context, what evidence is there that Thai undergraduates might be, lexically, in range of sucha target? First, the Ministry of Education in Thailand sets the lexical target for high school graduates at about 3600words (Ministry of Education, 1996). By words they probably mean lemmas, i.e. words and their inflected forms,although they do not specify this; certainly it is unlikely that they mean extended word families, i.e. words with theirderived as well as inflected forms. Still, these bare numbers might encourage us to think that they know enough wordsfor study purposes, although of course for our engineering students not all the 3600 words supposedly learnt at schoolwill be relevant to their university studies. Second, Ward (1999) shows evidence that for foundation engineeringtextbooks, his word list of only 2000 families (hereafter referred to as the Engineering Word List or EWL) is sufficientto provide 95% percent coverage of a 1,000,000 word foundation engineering corpus. This is considerably less, andthus more likely to be achieved, than the earlier target of 3000 cited above. (see. also Hazenberg and Hulstijn (1996)who put the figure at 10000 word families). A third point is that foundation engineering, at least, may not containa great deal of ‘‘technical’’ vocabulary, in the sense of many words requiring specialist knowledge to be understood.There is not sufficient space here to justify this claim in detail, but the most easily accessible evidence is in Mudraya(2006), whose own wordlist, based on a large and comprehensive foundation engineering corpus, clearly illustrates thepoint. (Incidentally the engineering word list used for this study is derived from Ward’s, not Mudraya’s corpus, thoughof course there is a good deal of similarity between the two).

On the basis of all this, can we conclude that Thai engineering students should know enough lexis, at least, fortextbook reading to be a plausible goal? Possibly not. A study by Nurweni and Read (1999) shows that first-yearundergraduates in an Indonesian university knew only half of the 2000-word General Service List words (West, 1953),and only 30 percent of the University Word List (Xue & Nation, 1984). Further afield, so to speak, Cobb and Horst(2001) give similar figures for Omani incoming undergraduates. Of course the situations in Thailand and Indonesia aredifferent in some ways and similar in others. But if the actual vocabulary knowledge of Thai undergraduates isgenerally as low as that of their Indonesian counterparts, then the idea that they as a class might be able to readengineering textbooks would be shown to be unrealistic, and some impetus for required changes might be created.

As this introduction has tried to show, the issue has implications for the individual student, for graduate research inThai universities, for the secondary education system and for the economy as a whole. It is only one factor amongmany (no-one, for example, has suggested that the Japanese economic miracle was based on the ability of theeducation system to deliver proficiency in the English language), but its significance is surely undeniable.

This, then, is the purpose of the present study: to establish how near Thai undergraduate engineering students are tothe lexical threshold necessary for effective reading of English-language textbooks.

2. Method

Subjects were students completing their first year at a university of technology in northeastern Thailand. Thetesting method used was the yes-no checklist test. In this test, subjects are given a list of words and invited to check theones of which they think they know at least one meaning. The EWL (divided into two parts) was one of the lists tested,for the obvious reason that it contains the words needed to read engineering textbooks. In this respect we may claimthat the test is more focused than Nurweni and Read’s study, though of course no criticism of the latter is implied. TheGSL (similarly divided into two parts) was the other list tested for purposes of comparison with Nurweni & Read, andalso because the words in the GSL overall coincide more closely than the EWL with the words students are supposedto learn in high school; we might get an idea of what success has been achieved in teaching to the 3600-word target.

Perhaps the best-known modern proponent of yes-no tests is Paul Meara. In Meara and Buxton (1987), Meara andJones (1988), and Meara (1990) he extols the merits of the format. The first study found yes-no tests to be betterpredictors of FCE (Cambridge First Certificate in English) scores than the multiple-choice vocabulary component ofthe test itself. Such findings led to the format being used for placement at the well-known Eurocentre languageschools. Shillaw (1996:8), using three of Meara’s Eurocentre tests, concludes that ‘‘Yes/No tests are more thanadequate test instruments from the point of view of measurement criteria’’. Nation (2001:348) also sees the yes-no testas ‘‘.a reliable, practical and valid measure of second language vocabulary knowledge’’. More recent support comesfrom Mochida and Harrington (2006), though their work is with higher proficiency students than those in the present


study. More examples of Meara’s more recent work with yes-no tests can be found at www.lognostics.co.uk; see alsothe general discussion of yes-no tests in Read (2000:126e132).

Two pilot studies were conducted to investigate first, the effect of non-words (for explanation see the followingparagraph) and second, the word sample size.

The obvious objection to yes-no tests is that students may check as ‘known’ words which they do not in fact know, forany of a number of reasons. To take account of this a certain number of non-words e words which do not exist and thuscannot possibly be known e are inserted in the checklist, and the subject’s score is adjusted downwards according to howmany of these non-words he/she has checked. The precise formula for this adjustment has come under some discussionin recent years (including in the papers cited above), entailing a degree of mathematical detail perhaps inappropriate ina paper of this length. Rather than go into this I will refer the reader to Meara and Buxton (1987) for a detailed descriptionof the scoring procedure followed here, and to Huibregste, Admiral, and Meara (2002) for critical discussion ofthis approach. To give a simple illustration of Meara & Buxton’s approach, in pilot study 2 there were a total of 60non-words mixed in with 120 real words. Suppose that a subject checked 60 of the 120 real words; this would give a scoreof 50% (60/120). However if he also checked 5 non-words this would result in his score being lowered to 45%. In fact inthe pilot studies (as well as in the main study) the average number of non-words checked was indeed about 5 out of 60.We took this as an indication that subjects were being at least fairly responsible in their answers.

The main conclusion from the pilot tests was related to the word sample used in the tests. Obviously a list of all thewords in the GSL and the EWL is too long to be tested in its entirety, so sampling is necessary. We would have liked totest each student on a sample from each of the four lists. For piloting purposes, therefore, a 30-word random samplefrom each of the four lists was taken and interspersed with 15 non-words, giving a total checklist of 180 words(30 wordsþ 15 non-words� 4 lists); it was felt that anything longer than this might try subjects’ patience. Howeverresults with these small samples proved somewhat inconsistent. In an attempt to rectify this, the random sample wasstratified and the samples were increased to 60 words from each of the four lists. This meant that each subject couldonly be tested on two lists, if we were to keep the checklist down to 180 words. Fortunately correlations in the pilot testwere extremely high between performance on GSL1 (the first 1000 words on the list) and GSL2, and on EWL1 (thefirst 1000 words on the list) and EWL2 (Spearman’s rho>: 0.9 in both cases), suggesting that performance on one testcould predict performance on the other, so it was decided to test each student on just one of the two engineering listsand one of the two general lists. As the priority was knowledge of EWL, 75% of the subjects were tested on EWL1,75% on EWL2, 25% on GSL1 and 25% on GSL2. Each subject did one ‘‘easy’’ list (containing more frequent words,i.e. EWL1 or GSL1) and one more difficult one. Half the subjects did the easier test first, the other half the moredifficult; this was to try and control for any fatigue effect.

Note that there is considerable overlap between GSL and EWL; both lists, for example, are headed by commonfunction words like the, of, can and is.

In the event, then, students were tested on four lists:

1) A sample of 60 words (mixed with 30 non-words) from EWL1, which covers about 92% of the running words inWard’s corpus (op.cit.). This test is shown in the Appendix.

2) A similar sample of EWL2. These words cover about 4% of the running words in the same corpus.3) A similar sample of GSL1. These words cover about 75% of the running words in most academic textbooks

(Nation & Waring 1997:15).4) A similar sample of GSL2. These words cover about 4e5% of the running words in most academic textbooks

(Nation & Waring 1997:15).

The test was administered in a differential equations class near the end of subjects’ first year. This ensured that onlyengineering students were present and, since these are large classes, that there would be a good turnout e in the event250 students attended. Subjects were not compelled to provide any information about themselves: it was feltanonymity might increase cooperation. There was however a space on the test form where they could write their yearof study, and their i/d number if they wanted to know their results. 106 subjects volunteered the former information,80 the latter. Of the 106, 97 were first year, 8 second, and one third. The lecturer confirmed the impression that thegreat majority of the class were first year students, who were yet to begin their engineering courses proper.

The administration of the test was put in the hands of two reliable and respected Thai teachers. Written and spokeninstructions were given in Thai. It was explained carefully to students that the purpose of the test was to improve the

http://www.lognostics.co.uk


English curriculum for them and their peers, and they were encouraged to do their best. One advantage of the yes-notest is that doing one’s best takes very little effort. In addition, the format makes collaboration or cheating rathermeaningless, (though this is not to say it cannot take place). Subjects were also reminded to check only words that theyknew the meaning of, rather than words they vaguely remembered seeing. Subjects took between 15 and 20 minutes tocomplete the test. My impression that students were cooperating and taking the process seriously was confirmed by theadministrators.

3. Results

Table 1 below gives the students’ scores. The left-hand column shows the wordlist tested, with the mean and sd inthe right-hand column. The figure 0.565 indicates that the mean score on the 1000-word list (adjusted for non-words)was 565; on this evidence, students thus know on average 565 of the 1000 words in EWL1.

These figures, then, suggest that students know 950 words from the 2000-word EWL, and 1200 from the GSL.

4. Discussion

If these figures are correct then there is no reason to look any further for an explanation of why students may notsucceed in reading their English language textbooks. There is a failure to get anywhere near high school learningtargets for general lexis, and the problem is exacerbated with foundation engineering vocabulary. It is impossible toestimate with any accuracy, but most students appear clearly to be operating way below the 95% lexical coveragelevel. The vital question, however, is this: do these results accurately reflect students’ vocabulary knowledge?

There is a claim (Barrow, Nakanishi, & Hoshino, 1999) that the yes-no test gives inflated estimates of students’vocabulary size, based on a comparison with their performance on the criterion measure, a translation test on the sameitems. But the study used only nonsense-type non-words (thus ignoring the factor of poor orthographic skills), andincluded only a relatively small proportion these non-words e 15%, to 85% real words; these decisions may haveinflated scores on the actual yes-no test. On the other hand, their 80-item translation test may well have deflated scores;the study does not seem to have taken into account any effect for fatigue, or boredom, for subjects taking such a longtest, and perhaps underestimates the effects on morale of asking subjects (with the translation test) to prove that theywere in fact telling the truth in their responses to the yes-no test.

My main concern prior to the test was the opposite e that students, far from demonstrating an inflated knowledge,would not perform to the best of their ability, most likely because of apathy towards English tests. This was the mainreason for choosing the yes-no format; the test was quick and required little hard concentration. In addition an attemptwas made to motivate students by giving a positive reason for taking the test (to help them and their peers readengineering textbooks). Other possible reasons for low performance might have included resentment at being used asguinea pigs, or at being forced to demonstrate ignorance. To try to counteract such factors students were grantedanonymity and the test was administered by well-liked and well-respected teachers.

In the event the main evidence that students actually failed to do their best resides in the very fact that the scoreswere so low. But there are countervailing arguments.

The results are somewhat similar to those of Nurweni and Read (1999) in Indonesia. There, first-year under-graduates showed knowledge of about 1000 of the 2000 GSL words. The format there was translation, which may beassumed to be more reliable than the yes-no test since the possibility of ‘‘deception’’ is reduced, but the scores are littledifferent to the 1200 in this study. Secondly, the scores in this study are identical to those of the second pilot test, whichwas taken by engineering undergraduates at another Thai university; surely it is much more likely that both sets of

Table 1

Scores on the yes-no test of approx. 250 students.

n Range Minimum Maximum Mean (þsd)

EWL1 177 0.72 0.14 0.86 0.565 (0.1268)

EWL2 175 0.75 0.00 0.75 0.388 (0.1436)

GSL1 70 0.65 0.31 0.96 0.713 (0.1551)

GSL2 70 0.75 0.18 0.94 0.520 (0.1714)


subjects were performing to the best of their ability rather than both being equally lazy. Third, there are goodcorrelations between the two (30-word) halves of the 60-word lists tested: Table 2 below gives the figures. This at leastindicates some consistency of performance.

There is, then, reasonable evidence that the results reflect students’ real knowledge of the word lists tested. Ofcourse they do not tell us students’ total vocabulary size, since students must know words which are not in the liststested. Nurweni and Read (1999) estimated this figure at ‘‘a few hundred’’. Some of these non-listed words are sure tobe engineering-related, but most, judging from a look at high school textbooks, are more likely to be related to localeveryday life. We must therefore face the possibility that students are quite unequipped for the lexical task facing themas undergraduate engineers. It appears they are on average in the range of 1000 words short of the target. This lookseven worse when we consider the figures from Milton and Meara (1995) and Schmitt and Meara (1997), where theaverage undergraduate student’s increase in word knowledge was estimated to be in the region of 300 words per year.Learning 1000 words is far from impossible, but it is a burdensome task which will not be undertaken by a lot ofstudents; note, again the remarks in section 1 about Thai-language textbooks. Any readers who have been forced tostudy a foreign language may sympathize.

As noted in section 2, subjects were given the option of identifying themselves in order that they could be informedof their results. Those that did so scored noticeably higher than their peers, as may be seen from Table 3 below.Although the scores for all the lists look appreciably different, a one-way ANOVA test (see the two right-handcolumns below) showed that the difference was significant (p< 0.05) only with EWL 1 and 2; but one hopes that self-identification might indicate various positive attitudinal traits e interest, desire to show knowledge, desire to succeede related to better performance. This also serves to counteract any impression that all the students at the institutionconcerned are poor in English, which is not in fact the case.

In the circumstances, it is surely appropriate to reconsider EAP engineering in terms of the groups for whom it istruly essential, rather than for the large body of students who have been, and are, studying every year without thelexical mastery needed for successful reading in English.

Of course, ideally, much greater efforts would be made to prepare high school students for the language demands oftheir university careers, but this is perhaps impossible to carry out, given the paucity of competent English languageusers teaching in the Thai secondary school system.

For undergraduates, three steps are suggested here. The first, in accordance with the findings presented here, is toabandon the pretence that engineering undergraduates as a body are adequately equipped to use English to becomebetter engineers, and institute a more comprehensive and systematic textbook translation programme. Translation hasalways been the policy in Japanese universities (Makino, 1997); is it possible that emphasis on the importance ofEnglish, in the Thai style, actually impedes growth of an engineering culture? If it is possible to present information ina form more easily accessible to students, does it make sense to do otherwise? EAP reading courses could still beoffered, but on a free elective basis instead of the compulsory credit system as at present. This would reduce thenumber of takers to those who felt the courses were worthwhile for their own sake. Second, rather than trying to plugthe large gaps in students’ general, and ‘‘general academic’’ vocabulary, EAP programmes should focus on the lexicaldemands of specific engineering disciplines (civil, chemical, etc). As well as being obviously more efficient, thismight serve to motivate students better than the type of wide-focus, popular science content seen at many universities,with its typical litany of environmental concerns. The approach suggested could probably not be undertaken withoutspecial training for (typically arts-trained) English teachers. Third, the faculties need to run EOP (English forOccupational Purposes) courses for senior students to prepare them for the real-life demands of an engineering career.Of course not all engineering graduates become engineers so one would hesitate to make such courses compulsory, butprospective employers might be interested to know whether and with what results applicants had taken the courses.

Table 2

Correlations between a and b versions of the yes-no test.

n Correlation Significance

EWL1 a/b versions 177 0.711 0.000

EWL2 175 0.645 0.000

GSL1 70 0.672 0.000

GSL2 70 0.838 0.000

Table 3

Comparison of means of identified and unidentified students.

Wordlist N (i/d) Mean (i/d) N (no i/d) Mean (no i/d) F Sig.

ewl1 56 0.6107 122 0.5392 5.812 0.004

ewl2 51 0.4454 123 0.3637 6.351 0.002

gsl1 22 0.7591 47 0.6959 2.090 0.132

gsl2 26 0.5576 45 0.4860 1.303 0.278


To sum up, in this context teaching needs become more focused. Overall, in order to increase subject specialisationin teaching, there is an obvious need for cooperation between engineering faculty and ELT staff. The idea that thelanguage (general and academic lexis, grammar and discourse structure) can be left to language teachers and thecontent (technical, conceptually specialised lexis) to the engineers may serve to make life more comfortable for bothsides, as well as furnish each side with a stick with which to beat the other, but it does not best serve the interests ofanybody.

5. Conclusion

This paper has presented evidence indicating that large-scale EAP programmes, aimed at enabling Thai under-graduate engineers to read textbooks in English, are unlikely to meet with success. The evidence consists of resultsshowing a severe lack of lexical knowledge, including lack of knowledge of foundation engineering vocabulary. Ofcourse more and better teaching of words would not solve the reading problem by itself, but it is probably a sine quanon of success. Unfortunately the figures presented here suggest that the task is an enormous one. As an interimsolution, greater efficiency could be achieved by rethinking the place of EAP in Thai universities, and by implicationin similar institutions elsewhere, in particular by more focus in terms of sub-discipline specialisation, both foracademic and occupational purposes.

Appendix.

A sample yes/no test: This is a section testing the first 1000 words of the EWL, i.e. EWL1, with 60 real words and30 non-words. A student taking this section of the test would also take the GSL2 test e see page 9.

(The following is a translation of the instructions in Thai)In this test please underline the words in the list below if you know their meaning.Example: if you see the four words dog san cat frass, and you only know the words dog and cat, you underline them

like this: dog san cat frass.This shows that you do not know the meaning of san and frass, but that you do know the meaning of dog and cat.About adequate alternative answer attach bolt borvel change clear correct curvature cut dapth defate deform

evident fealist four histarical ice instont investigate law liquidible listative load mardic mimimum montain negligibleplace product proportion puriness reason reductible respect select solutous terue to upon wall wheel withort abahtaccelerate affect beam belt bottle civilous collectional cressic deviate difficult dirtiate elongate end exoct flangeforwand from inclination let level material mean mortent note numeric obvious physsicle pin population positionprincipist procedive random real rebote review rhenish sarlent schematic side steel upward villuge wrench.

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