http://wjel.sciedupress.com World Journal of English Language Vol. 6, No. 4; 2016
Published by Sciedu Press 1 ISSN 1925-0703 E-ISSN 1925-0711
Vocabulary Facilitation on Technical Modules for ESL Learners: A Case
Study of a Sri Lankan Higher Educational Institute
Chathurika Senevirathna
1
, Shashitha Jayakody
2,*
& H Rangika Iroshani Peiris
2
1
English Language Teaching Unit, Sri Lanka Institute of Information Technology, Sri Lanka
2
Department of Business Management, Faculty of Business, Sri Lanka Institute of Information Technology, Sri
Lanka
*Correspondence: Department of Business Management, Faculty of Business, Sri Lanka Institute of Information
Technology, New Kandy Road, Malabe, Sri Lanka. E-mail: s.g.jayakody@gmail.com
Received: December 14, 2016 Accepted: December 19, 2016 Online Published: December 27, 2016
doi:10.5430/wjel.v6n4p1 URL: http://dx.doi.org/10.5430/wjel.v6n4p1
Abstract
This study focuses on the degree of facilitation of the English language module on a technical module offered for a
degree program in a higher educational institute in Sri Lanka. The sample consists of 5,855 words from one technical
module in the stream of Accounting and Finance and 10,554 words from one English language module prescribed for
the BBA (Special) Degree program during the first year first semester of undergraduates. The level of facilitation was
measured in terms of vocabulary; an essential component found in the empirical literature to acquire the technical
knowledge in tertiary education. In order to achieve the main objective, “whether or not the language module
facilitates the technical module” the researchers utilized Academic Word List (AWL) and examined the presence of
AWL items in both modules and compared the common distribution of AWL items. The results showed 12.33%
presence of AWL items in the technical module and 3.95% in the language module. 65 AWL word families were
identified as common to both modules. The facilitation of the language module on the technical module in terms of
vocabulary is 42.20%. Interestingly, the most frequently used 10 AWL items are not common to both modules.
Collocation and gap making can be suggested as appropriate vocabulary activities in order to enhance the exposure
of the ESL learners to vocabulary.
Keywords: The Academic Word List (AWL); AWL coverage; facilitation; vocabulary; technical module
1. Introduction
There is a growing interest about using English as the accepted medium of instruction in Sri Lankan higher
educational system. However, this phenomenon triggers many social and research discussions regarding students’
academic adaptability in ESL context. Previous researchers looked into core components of language in relation to
achieving academic goals. It is in this background that vocabulary teaching has earned tremendous attention
worldwide in ESL research and ELT pedagogy. The studies carried out by Li and Qian (2010), Wang, Liang & Ge
(2008), Mudraya (2006), Coniam (1999), show the importance of vocabulary building in several disciplines with the
aid of AWL. Similarly in the Sri Lankan context, studies of Illangakoon (2012), Kumara (2009) and Perera (2006)
highlight the significance of English vocabulary building in the teaching and learning process of higher education.
The current study observes the degree of facilitation of the English module towards the selected technical module in
terms of vocabulary. Creating academic word list has dialectically evolved assuring AWL developed by Coxhead
(2000) still as a centralized research source. It is this backdrop that drove the researchers to utilize AWL as an
important yardstick to assist the present case study.
This study is an attempt to examine whether the prescribed English language teaching modules facilitate the
compulsory technical modules offered for the BBA (Special) degree program in the Faculty of Business, at Sri Lanka
Institute of Information Technology. This case study specifically focuses on the first year first semester technical
module, “Fundamentals of Accounting” (FA) and the English language module “English Language Skills I” (ELS1).
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1.1 Importance of Vocabulary
Importance of vocabulary for ESL learners is observed in different aspects. Shaw (1991) finds that the most
prominent language problem of both native and non-native learners in their academic learning and writing is
vocabulary. Especially in the university system vocabulary can be of paramount assistance for students to acquire the
essential technical knowledge. Li and Pemberton (1994) state that it is not discipline specific technical vocabulary
that tertiary students find difficult in their learning process, but “the vocabulary with a middle-frequency of
occurrence across the texts of various disciplines that students find most problematic (p.184).”
1.2 Needfulness of AWL in ESL Pedagogy
It is in this context that needfulness of AWL is proved important in the ESL pedagogy. To quote Coxhead (2000),
“the AWL shows learners with academic goals which words are most worth studying (p.1).” Vongpumivitch, Huang
& Chang (2009) emphasize “the importance of learning the frequently-occurring AWL words, especially those that
come from Coxhead’s first two sublists, regardless of the learners’ filed.” Hence, our research uses AWL as a foil to
address the research objectives. AWL is used to examine the common distribution of the academic words in the two
modules with the objective of finding out whether or not the ELS module serves as a facilitator module to FA in
terms of vocabulary.
1.3 The Academic Word List
Compilation of word lists dates back to 1970’s (Note 1). However the most eminent word list in the academia is the
list created by Coxhead (2000). This consists of 570 word families from the disciplines Arts, Commerce Law and
Science which is based on a 3.5 million word corpus. The coverage of the AWL word list in the stream of commerce
is 12% (Coxhead, 2000). The AWL is grouped into ten sublists depending on frequency. Except the tenth sublist,
which has 30 word families the rest contain 60 word families each.
2. Objectives
The main objective of the study is to investigate whether or not the language module “ELS1” facilitates the technical
module “FA” in terms of vocabulary. In order to achieve the primary objective we have three research questions.
1) What is the presence of AWL items in the FA module?
2) What is the presence of AWL items in the ELS 1 module?
3) What is the common coverage of AWL items in both modules?
3. Methodology
3.1 Sample
Prescribed teaching material for the BBA (Special) degree program at the Faculty of Business, at Sri Lanka Institute
of Information Technology was considered for the study. The BBA (Special) degree program consists of five main
specializing streams (Note 2). The informal interviews with undergraduates and the subject specific lecturers
revealed that the difficulty of medium is a common barrier to acquire the required technical knowledge of the
particular modules. Therefore, we felt the need of considering the vocabulary items in the prescribed technical
modules. This case study limits only to the area of “Accounting and Finance”. The undergraduates are first exposed
to the subject “Accounting and Finance” during their first year through the module “Fundamentals of Accounting”.
Thus we selected FA as our technical module.
On completion of General Certificate of Education - Advanced Level (Note 3) examination, students from different
socio economic backgrounds enter the degree program which is totally conducted in English. Majority of the
students complete their secondary education in their first language. In this event, it is Sinhala or Tamil. Thus the
degree program would be the first experience of the majority in following technical subjects in the medium of
English. Thus the first year first semester modules were found crucial in orienting them to learning process of the
university education. Therefore we concentrated on first year first semester modules.
There are two English language modules for the degree program. Both modules are taught using the prescribed
English language text books “English Language Skills 1” and “English Language Skills 2”. Both text books are
taught during first year in first and second semesters respectively.
“English Language Skills 1” is a text book compiled by the in house staff at the institute with the objective of
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Published by Sciedu Press 3 ISSN 1925-0703 E-ISSN 1925-0711
enhancing the primary language skills of first year students’ (Note 4). The text book largely contains lessons from
General English. Fundamentals of Accounting module is comprised of presentation slides based on the module
outline prepared by the in-house staff (Note 5).
The teaching materials of both modules were standardized according to the method employed by Chen and Ge
(2007). We eliminated items which cannot be counted such as diagrams, charts, numbers and references. After the
standardization procedure our text consisted of 5,855 words from FA and 10,554 words from ELS1.
3.2 Method
In order to achieve the objectives of the current study we utilize the online software program developed by Tom
Cobb, the Compleat Lexical Tutor (CLT). This can be accessed free of charge on http://www.lextutor.ca/. The site
consists of various features which enables to carry out lexical analyses (Note 6). The “VocabProfiler“ feature in the
software breaks down the uploaded text into three lists, namely ‘first thousand frequent words’ (K1), ‘second
thousand frequent words’ (K2) both of which developed from the General Service List (GSL) and thirdly the
Academic Word List. The output from this feature shows the coverage in selected text relative to the aforementioned
three lists. Using this output we identified the coverage of AWL items in both FA and ELS1 modules. Further, we
extracted the AWL families (head-words) which are present in the input text of both modules with the intention of
mapping the technical module with the language module. The mapping of the head-words was carried out using
Vlookup function in MS Excel.
4. Results
Table 1. Coverage of the FA Text Book Material by the GSL and the AWL
Word list Number Word list description Families Types Tokens Percent
1 K1 Words, 1-1000 405 627 4184 71.47%
2 K2 words, 1001-2000 68 98 324 5.53%
3 AWL words (Academic) 154 237 722 12.33%
Not in the list Off List words 172 624 10.66%
Total 627 + 1134 5854 100%
Table 1 shows the coverage of General Service List (GSL) which represents K1 and K2 and the Academic Word List
(AWL) in the technical module FA. The results indicate that 89.33% of the tokens in the FA module represent a
combination of the GSL and the AWL. The AWL coverage of the tokens in the selected module is 12.33%.
This result justifies the statement made by Coxhead and Byrd (2007) that AWL “covers approximately 10% of any
academic text”. The results can further be compared to the recent research findings of Li and Qian (2010) which
covers 10.46% of their selected corpus. These researchres have profiled the presence of the AWL items in their
financial corpus, with the objective of exploring ways to effectively teach the AWL items in the Hong Kong
Financial Services Corpus. Our results further conform to the findings of Chen and Ge (2007) at their attempt to
identify the AWL words in selected medical research articles as their findings manifest a coverage of 10.07%.
Moreover in the Sri Lankan context, Illangakoon (2012) reports similar findings (11.11%) in her corpus based on
five subjects in the stream of Arts. Contrastingly, a study based on a Chemistry corpus reveals only 9.6% of AWL
coverage which is lower than the percentages reported in the above studies (Valipouri & Nassaji, 2013).
Table 2. Coverage of the ELS1 Text Book Material by the GSL and the AWL
Word list Number Word list description Families Types Tokens Percent
1 K1 Words, 1-1000 682 1128 8251 77.44%
2 K2 words, 1001-2000 269 359 760 7.13%
3 AWL words (Academic) 186 237 421 3.95%
Not in the list Off List words 714 1223 11.48%
Total 1137+ 2438 10655 100%
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Table 2 shows the coverage of the language module, “ELS 1” by the GSL and the AWL. The total coverage in AWL
is 3.95%, when compared with the technical corpus-based studies, the above percentage stands lower than the
percentage (10%) reported by Coxhead and Byrd (2007). However, our findings are in consistence with the results of
Dang and Webb (2013) which shows a coverage of 4.41% in their study based on academic spoken English.
Table 3. Distribution of AWL Word Families in ELS1 and FA
ELS 1 FA
Summary Counts Percentage Counts Percentage
AWL total word families 570 570
AWL families in the input text 186 32.63% 154 27.01%
AWL families not in the input text 384 67.36% 416 73.15%
Note: All the percentage values are rounded to two decimal places. These percentages do not refer to tokens in text
but rather number of families. This analysis applies only to standard list items NOT any recognized proper nouns.
Table 3 shows the distribution of the total AWL word families in both modules. ELS 1 covers 32.63% while FA
covers 27.01%. Interestingly, ELS 1 has a 5.62 of higher percentage difference. This distribution has further been
illustrated graphically in Figure 1.
Figure 1. AWL Word Family Distribution
With reference to the third research question there are 65 AWL word families recorded common to both modules as
shown in Figure 1. The remaining 89 word families in the FA module are not covered in the ELS 1 module. Thus
these findings indicate that the degree of facilitation of the language module; ELS 1 on the technical module; FA is
42.20% in terms of vocabulary. The identified 65 common word families are illustrated in table 4.
Table 4. Common AWL items in FA and ELS 1 Text
Affect Contract Function Method Relevant
Approach Correspond Fund Negate Rely
Appropriate Create Generate Neutral Require
Assign Define Identify Normal Resource
Assist Distribute Indicate Occur Secure
Assume Document Individual Option Significant
Assure Economy Institute Overall Source
Available Error Internal Percent Specific
Benefit Establish Involve Period Task
Bias External Issue Physical Transfer
Chart Factor Job Proceed Trend
Communicate Final Margin Professional Vary
Consent Format Maximize Purchase Version
ELS 1
FA
570
186
154
65
121
89
295
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Figure 2 is an illustration of comparison in the distribution of AWL sublists in both modules. The coverage of AWL
sublists in Coxheads’ corpus manifests a decreasing trend (Coxhead, 2000). Vongpumivitch et al. (2009) have also
observed the same pattern. However in the selected modules in the present study the overall pattern follows the
similar decreasing shape of the distribution with minor differences in individual sublists.
Figure 2. Comparison of subsists
Further we extended our study to examine the frequency of AWL items in both modules to identify how frequently
the both modules expose the ESL learners to the top 10 AWL items.
Table 5. AWL Items (Word Families) in the Modules
ELS 1 FA
AWL item Frequency Item* % Cumulative % AWL Item frequency Item % Cumulative %
document 12 0.03 2.85 finance 70 0.10 9.70
format 12 0.03 5.70 credit 50 0.07 16.62
transport 12 0.03 8.55 ratio 36 0.05 21.61
appropriate 11 0.03 11.16 purchase 33 0.05 26.18
insert 10 0.02 13.54 journal 21 0.03 29.09
compute 9 0.02 15.68 period 20 0.03 31.86
job 9 0.02 17.81 income 19 0.03 34.49
confer 7 0.02 19.48 item 18 0.02 36.98
function 7 0.02 21.14 entity 16 0.02 39.20
paragraph 7 0.02 22.80 factor 15 0.02 41.27
*Item % = frequency of the specific word family / the frequency of all the AWL items in the module.
Table 5 shows the top 10 AWL items in ELS 1 and FA modules. ELS 1 has a cumulative coverage of 22.80%. FA has
a cumulative coverage of 41.27%. It is nearly twice the size of ELS1. Interestingly, none of the top 10 AWL items in
each module are shared mutually. Considering the 65 common items (Table 4), it is 5 from the top 10 AWL items in
ELS 1 module and 3 from the FA module. The findings further reveal that the learners are exposed to 8 common
word families from the above identified high frequency word families.
5. Conclusion
In our study to identify the degree of facilitation of the ELS 1 module on the FA module, we first profiled the