korean efl learners' vocabulary use in reading-based writing:...

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English Teaching, Vol. 66, No.l , Spring 2011

Korean EFL Learners' Vocabulary Use in Reading-based Writing: According to Topic and Learner Proficiency

Sung-Yeon Kim (Hanyang University)

Young-sook Ryoo (University of Seoul)'

Kim, Sung-Yeon & Ryoo, Young-sook. (2011). Korean EFL learners'

vocabulary use in reading-based writing: According to topic and learner

proficiency. English Teaching, 66(1),91-109.

The study investigated whether Korean EFL students' vocabulary used in reading

based writing differed according to writing topic and their reading and writing

proficiency. C이lege students enrolled in writing courses (n=95) were asked to write

argurnentative essays in response to two readings on judging people by appearance

(JPA) and disc10sing personal information ofserious criminals (DPI). These students

were divided into high and low proficiency writer groups and into 비gh and low

proficiency reader groups according to their writing and reading scores respectively.

The students' vocabulary used in writing was then analyzed by VocabProfile, which

provided fo따 lexical frequency Iists: the first 1000 frequent words (K 1) including

function words (F찌') and content words (CW), the second \000 frequent words (K2), academic word Iist (AWL), and offthe Iist words (OLW). 까le results indicated that

the topic JPA produced a higher proportion of Kl and content words, whereas DPI

generated more K2 and offthe Iist words. None ofthe vocabulary profiles, however, significantly differed according to the students’ reading proficiency. In contrast, proficient writers were found to use significantly more K 1 and function words than

their counteφ따ts . With the topic effect further considered, for JP A, proficient writers

used more K 1 words and function words whereas less proficient writers 따ed more

K2 and off the list words. With regard to DPl, proficient writers were found to use

more function words than low proficient writers. Findings are discussed in more

detail, along with implications.

1. INTRODUCTION

In recent ye따s， an integrated skill approach rather than a discrete skill approach has

• First author: Sung-Yeon Kim, Corresponding autl1or: Young-sook Ryoo

92 Kim, Sung-Y eon & Ryoo, Y oung-sook.

received more favorable attention from ELT practitioners. In particular, the use of

integrated reading and writing tasks has e매oyed popularity both for classroom instruction

and for assessment (Leki & Carson, 1997; Plakans, 2008; Weigle, 2004). The writing

component in the TOEFL iBT test is a good example of a reading integrated w디tingtask.

까ús reading-based writing 없sk， althou양1 it is a real-life challenge for L2 learners in

acadellÚc contexts (Baba, 2009), is etIective since it is designed to resolve problems of

conventional writing tests that lack authenticity and validity. According to Plakans (2008), reading integrated writing tasks are close to academic writing assignments and thus less

demanding from students' perspectives.

In a similar vein, Weigle (2004) illustrates some advantages of reading-based writing

tests over prompt-based writing tests. According to Weigle, the use of reading materials is

beneficial for test-takers in that they can write in response to the source texts. The source

texts can serve to activate writers' background knowledge about a topic and to facilitate

writers' idea generation.

Since source texts supply second language learners with more information, content, and

ideas for writing, L2 writers in Plakans (2008) were found to prefer a reading-based

writing task and plan more while performing reading-based writing tasks. Based on the

findings of the study, Plak없15 suggested that reading-based writing tasks should be used

for evaluating a writer’s ability to plan during the writing process.

It can be inferred from the earlier studies that providing relevant reading texts can be of

great help to EFL writing instruction because students can recycle some words or sentence

pattems from the source texts to produce writing. However, few studies have been

conducted to explore how reading can be integrated into writing and more specifically, how L2 learners use vocabulary in reading-based writing. The questions are even more

intriguing when we note L2 learners’ vocabulary knowledge is not necessarily equal to

their ability to use vocabulary (Read, 1997, 2000).

In line with Read (1 997, 2000), Laufer and Nation (1 995) devised the Lexical

Frequency Profile (LFP) to assess L2 learners' vocabulary in writing and claimed that the

LFP is a reliable measure of lexical richness in L2 writing. They state that the LFP

“ provides similar stable results for two pieces of writing by the same person 때d

discriminates between lea

Korean EFL Le하ners’ Vocab비ary Use in Reading-based Writing: According to Topic and ... 93

11. THEORETICAL BACKGROUND

1. Previous 8tudies on L2 Reading and Writing

As one ofthe early studies that explored the relation between reading and writing, Tsang

(1996) examined whether Hong Kong learners of English would benefit from extensive

reading in regards to the following sub-skills of writing: content, organization, vocabulary, language use, and mechanics. The findings of the study indicated that the extensive

reading expe끼ence helped the students with content delivery and language use when

writing. In relation to the fmding, Tsang (1996) argued for the need to expose students to

reading materials. Hinkel (2006) went so far as to argue that teachers should select reading

from various genres oftext (narrative, argumentative, expository, etc.) to facilitate learners'

noticing of grammar and vocabulary.

With the same argument reflected in teaching method, Plakans (2008) further supported

an integrated approach to teaching writing. Plakans' (2008) study offers a clear connection

between reading and writing. 까le study designed reading-to-write tasks and writing-on1y

tasks and compared the effectiveness of the two. The study used a think-aloud verbal

protocol to compare ten students' composing process in academic writing. Four

participants thought of the writing-only tasks as more difficult because they had to develop

their own ideas. By contrast, six writers reported they performed better on the reading-to

write tasks. Nine of the students actually reported that they preferred the reading-to-write

tasks to the writing-only tasks. In addition, while performing the reading-to-write task, hi양11y experienced and motivated writers interacted more actively with the source texts.

Based on the findings of the study, Plakans recommended that reading-to-write tasks

should be used to make inferences about writers' abilities.

The reading-writing connection was also examined with vocabulary being a medium of

the two. Webb (2009), for example, explored the effects of two different ηpes of

vocabulary practice on Japanese EFL students' English reading and writing. The study

examined whether ways of learning vocabulary would affect reading and writing. One

group of students learned nonsense vocabulary while performing a receptive learning task;

the other group performed a productive learning task for vocabulary learning. The results

showed that the receptive task (word translation of L2 into Ll) led to improvement in

reading comprehension, whereas the productive task (word translation of Ll in

94 Kim, Sung-Yeon & Ryoo, Young-sook.

examine the relation. For ex따nple， it would be helpful to take into account L2 le따ners’

reading and writing proficiency with regard to their vocabulary knowledge in writing. The

relationship will be interesting to investigate since L2 leamers' vocabulary knowledge is

intrinsically connected to text comprehension (reading) and production (writing).

2. L2 Learners' Vocabulary Knowledge and Language Proficiency

It has been pointed out that L21eamers' vocabulary knowledge is closely related to their

language proficiency and researchers have σied to explore what is meant by knowing a

word in L2. Previous studies (Morris & Cobb, 2004; Muncie, 2002; Qian, 2002; Saville

Troike, 1984) have argued that vocabulary is central to second language leaming and

teaching and further suggested that measures of vocabulary knowledge are useful

indicators ofL2 proficiency.

As one of the earlier studies, Saville-Troike (1984) explored the relationship between

EFL children’s English language performance and their academic achievement. The study

found that the children’s accuracy in English morphology and syntax in spoken language

was of little importance to their academic achievement and that the correlation between

their reading achievement and grarnmatical accuracy was very weak (r =.025). Reporting

the findings, Saville-Troike claimed that vocabulary knowledge was the single most

important aspect of second language competence p따ticularly when the leamers are

leaming an L2 in the target language.

With more focus on different types of lexical competence, Laufer and Goldstein (2004)

examined what type of vocabulary knowledge was the best indicator of general language

competence. F or this question, Lauf농r and Goldstein divided L2 leamers' vocab비따y

knowledge into the following four categories: active recall, passive recall, active

recognition, and passive recognition. πleir study found that the best predictor of success in

foreign language class was passive recall of word meaning. Based on the findings of the

study, they suggested that vocabulary knowledge is not an all-or-nothing phenomenon and

is more related to what learners are required to do with the knowledge.

Another line of argUDlent on the role of vocabul없y was made by Morris and Cobb

(2004). Their study reported that vocab띠하y profiles instead of passive recall of words

would function as useful measures of leamer proficiency in higher education. 깐leir study

noted some correlations between TESL students' vocabulary profiles and their academic

performance in a pedagogical grarnmar course. The hi양lest correlation was found between

the use of academic words and grades in the grarnmar course. Two significant correlations

were also obtained between 1,000 most frequent words (K l) and grades, and between

function words and grades. In a comparison of the TESL students and native speakers, the

study found

Korean EFL Learners' Vocabulary Use in Reading-based Writing: According to Topic and ... 95

words from the first one thousand words (Kl) and the function words (FW). Compared to Morris and Cobb, other studies paid special attention to the association

between vocabulary knowledge and reading proficiency (Nassai, 2004; Qian, 2002) on the

grounds that reading exposes L2 learners to vocabulary, and thus facilitates the acquisition

of reading fluency. For instance, Nass매 (2004) found that vocabulary knowledge, P따ticularly the depth of L2 vocabulary knowledge, was sσongly correlated with learners’

ability to read and understand written texts. It can be inferred from the finding that L2

vocabulary knowledge plays a crucial role in reading comprehension.

As to the relationship between different aspects of vocabulary knowledge and reading

skills, Qian (2002) investigated whether the breadth or the depth of vocabulary would

influence L2 learners’ reading process. Qian (2002) defined the breadth of vocabulary (or

vocabulary size) as the number ofwords one knows, and the depth ofvocabulary as how

well one knows words. The study found that the depth of vocabulary was as important as

vocabulary size as an indicator ofL2 students' academic reading performance. Qian further

suggested that tests that measure both the depth and the size of vocabulary should be used

to better predict learners' reading performance.

In a more recent study, Qian (2005) investigated L2 learners’ use of vocabulary

knowledge in the process of making lexical inferences while reading. The results of the

study indicated that the depth of vocabulary knowledge contributes to reading

comprehension for Chinese and Korean ESL learners of English. Based on the findings, Qian emphasized the need to foster the depth of learners' vocabulary knowledge and

advised L2 instructors to focus on this for their classroom teaching.

The studies reviewed thus far examined the relationship between L2 learners’

vocabulary knowledge and their reading comprehension 뻐d found that vocabulary

knowledge was a sπong predictor of learner performance in reading. There are also studies

interested in the relationship between L2 learners’ vocab비따y knowledge and writing

performance.

For instance, Engber (1995) investigated the relationship between various lexical

measures and writing quality. The study compared the quality of student writing in terms

of four measures of lexical richness: lexical variation, error-free variation, percentage of

lexical error, and lexical density. The study noted the hi방le

96 Kim, Sung-Y eon & Ryoo, Y oung-sook.

sho비d note that students’ use of vocabulary might differ according to their proficiency

levels. Thus, the study aims to examine how learners with different levels of reading and

writing proficiency use vocabulary in writing.

III.METHOD

1. Research Questions

For the purpose ofthe study, the following research questions were posed:

1. Are there differences in learners' use ofvocabulary according to writing topic?

2. How do students with different levels of reading proficiency use vocabulary in

reading-based writing?

3. How do students with different levels of writing proficiency use vocablilary in

reading-based writing?

2. Participants

The participants of the study were freshmen at a university in Seoul. The students had

similar educational backgrounds since they were newly admitted to a top-tier university

after taking the Korean scholastic aptitude test (SAT). However, they were from different

fields of study: industrial design, environmental sculpture, music, statistics, physics, life

science, law, business administration, and environmental engineering.

The number ofthe students was originally ninety-five, but for a clear comparison ofthe

hi양1 and the low proficiency group, the students rated as intermediate level were excluded

from the data. With regard to reading proficiency, there were 30 for the hi방1 proficiency

group and 25 for the low group. In terms of w디ting performance, 21 students were

classified as hi양피y proficient whereas 19 were grouped as a low group.

3. Data Collection Procedure

For data collection, students were asked to take both reading and writing tests. The

reading test extracted from a TOEFL preparation book (Cho, 2002) contained three

passages with five questions for each passage. The total number of questions being 15, the

maximum score students could obtain was 15. It took 15 minutes to conduct the reading

test.

According to the reading test results, the students were assigned either to a hi맹

Korean EFL Leamers' Vocabulary Use in Reading-based Writing: According to Topic and ... 97

proficiency group (RH) or to a low proficiency group (RL). πle students who obtained ten

or above were categorized as a hi맹 proficiency group (n=30, RH) and those with below

five as a low proficiency group (n=25, RL). The students with scores of six to nine were

excluded from the data analysis for a clear comp때son of the two groups.

After the reading test was administered, the students were asked to write argumentative

essays on two topics. The topics were chosen to induce learning interest from students, as

shown in the following:

• One should never judge a person by extemal appearance (JP A).

• Personal information of serious criminal suspects should be revealed (DPI).

까le fust one (JPA) was selected as an easier topic than the other one (DPI). Newspaper

articles on the topics were given to the students so that they could read the materials prior

to writing. They were not allowed to utilize any other kind of extemal aids including

dictionaries while writing. They had an hour to complete each writing task in class, and

they were told to produce a 300-word written text.

At the end of the task completion, two raters holistically scored student writing on

content and language (i.e., grammar and vocabulary). The two raters had been teaching

English writing to Korean c이lege students for five and ten years respectively. They had a

mock norming session in which they assessed several students' writing s따nples and

discussed the results of scoring. When there were disp때ties between the two raters, they

discussed reasons for their rating, and through discussion reached a consensus. The student

writing rated as neither high nor low got excluded from the data set tQ make sure there is

an obvious gap between the two writing proficiency groups. According to the fmalized

scores, 21 students belonged to the highly proficient writer group (WH) and 19 to the low

proficient group (WL).

4. Data Analysis

For data analysis, the students’ written essays were typed and converted into text files.

깐le text files were analyzed with the on-line computer program called VocabPr，야le. 까le

VocabPr，껴le program enabled us to obtain each student’s vocabulary profile in terms of

the following frequency word lists: the most frequent 1000 words (Kl); the second 1000

(K2); the Academic Word List (AWL) and words that do not appear on the other lists

(OLW).

In addition, function words (FW) 없ld content words (CW) as subsets of Kl were also

chosen for data analysis. πlese categorized frequency lists assume that the higher the

percentage of infrequent words, the larger the subject’s productive vocabulary. SPSS 18.0

98 Kim, Sung-Yeon & Ryoo, Y oung-sook.

was run to see whether there were statistical differences in learners’ productive vocabulary

according to writing topic and their reading and writing proficiency.

IV. RESUL TS AND DISCUSSION

1. Students’ Vocabulary Level and Writing Topic

To examine if and to what extent students' vocabulary use differed according to writing

topics (JPA and DPI), a multivariate analysis ofvariance (MANOVA) was run, with topic

as an independent variable and vocabulary profiles as dependent variables. Table 1

summarizes the res띠ts of the between subject effects obtained from the MANOVA. As

shown in Table 1, significant differences were found in most of the vocabulary profiles:

Kl , CW, K2, and OLW. In other words, depending on the writing topic, the students

differed in their use of content words, Kl and K2 words, and the words not in the list.

Source

Writing topics

TABLE 1 Tests of Between-Subjects Effects: Topic

Dependent Mean square df F variables Kl FW CW K2 AWL OLW

2354.739 .223 2651.066 1823.669 286.738 96.220

116.577 .006 153 .422 236.231 3.335 12.175

Sig.

.000

.937

.000

.000

.069

.001

To examine specific details, descriptive statistics were also obtained. Table 2

demonstrates mean differences in the six lists according to writing topic. As seen in Table

2, JPA presented as an easier topic produced more Kl and content words. on the other

hand, DPI prepared as a more challenging topic involved the use of more advanced

vocabul따y， i.e., K2 words. It is interesting in that writing topics influenced the kinds of

vocabulary the student used in writing. As expected, an easier topic was associated with

the use of the first 1000 words (K 1) and content words whereas a more difficu1t topic was

associated with the use ofthe second 1000 words (K2). In the same vein, academic words were predicted to be more frequent for a more

difficult topic, DPI. Contradictory to the expectation, however, academic words were

frequently used for JPA, an easier topic. The seemingly different mean scores may be

attributable to the 1따ge gap in stand따d deviations (SDJP~13.05 vs. SDDPI =1.3). Although

the mean difference may seem more than expected due to the standard deviations, it was


not significant in statistical testing.

Kl Jl’A 87.200 4.897 DPI 80.159 4.051

FW JPA 47 .429 4.880 DPI 47.360 6.862

CW JPA 39.771 4.037 DPI 32.300 4.274

K2 JPA 3.953 2.121 DPI 10.149 3.308

AWL JPA 5.402 13.049 DPI 2.945 1.300

OLW JPA 5.323 3.147 DPI 6.746 2.430

Note: JPA Gudging people by appearance), DPI (disctosing personal inforrnation ofserious c더minals)

It is interesting to note that the vocabulary profile in leamer writing, as shown in Table 2, indicates a similar pattem to the lexical disπibution in the original texts. Table 3

summarizes the results from the lexical frequency profile (LFP) analysis of the two source

texts given to the students. As shown in Table 3, the text on an easier topic, JPA was found

to contain a greater proportion of Kl and content words, whereas the text on DPI

contained more advanced vocabulary, such as K2 and academic words and off the list

words. The finding implies that the lexical disσibution of the source texts aff농cts the

vocabulary profiles of leamer w디ting.

TABLE3 Analysis ofVocabulary Distribution in Two Source Texts

KFW CW K2 AWL

78.88 42 .48 36.4 1 5.83 3.64 JPA DPI 71.48 42.96 28.52 11

뻐-뻐

떠

5.15

Note: Each number represents percentages ofthe vocabulary used in the source texts.

To sum up, it can be inferred that writing topics and more specifically, relevant readings

influence student writing, particularly their vocabulary use. In other words, depending on

writing topics, the kinds of words EFL leamers use are likely to vary sigr디ficantly.

Therefore, classroom teachers should consider writing topics as an important factor when

designing writing tasks or tests, since it can affect the quality of vocab비ary and writing


students would produce.

It is noteworthy that the fmdings ofthe study do not confinn Laufer and Nation’s (1 995)

study. Laufer and Nation c1aimed that two different pieces of writing by the same writer

have similar lexical frequency profiles and that the LFP can provide stable results for two

pieces of writin:g done by the same learner. Un1ike what they have argued, the present

study found that the LFP may not be so stable, in: that it varied according to writin:g topic.

ηle finding of the study, however, is consistent with Reid (1 990) and Tedick (1 990), which demonstrated that topic is an important factor affecting L2 le하ners’ vocabulary use

in English writing.

2. Students' Reading Proficiency and Vocabulary Use

The total number of student writings ended up to be 60 for the highly proficient

reader group (RH) and 50 for the low proficient reader group (RL) since the students in

each group (RH, n=30; RL, n=25) produced two pieces of writing on the two different

topics (JP A and DPI). The written essays were analyzed with VocabProfile to obtain

lexical frequency profiles. A MANOV A was then run with reading proficiency levels as

independent variables and lexical profiles as dependent variables. As seen in Table 4, none of the profiles were found to be significantly different according to the reading

proficiency level. In other words, the kinds of words learner used did not vary so much

between high proficient readers and low proficient readers.

TABLE4 Tests of Between-Subjects Effects: Reading Proficiency

Source Dependent Mean square df F Sig. variables Kl 33.550 1.041 .3 10 FW 16.079 .390 .534

Reading CW 5.497 .160 .690 proficiency K2 10.386 .644 .424

A WL 108.321 1.434 .234 OLW 27.285 3.506 .064

Table 5 displays the descriptive statistics of each vocabulary profile according to the

students' reading proficiency levels. Descriptive statistics also display the same pattern:

min:imal differences in mean scores due to reading proficiency. Highly proficient readers

used a few more function words, academic words and words from the Kl list; low

proficient readers used sli양lt1y more content words and K2 words, which may be due to

their use of writing strategies. π1ey mi양1t have sirnply referred to the source texts, from

which they copied some advanced words or words that carry important meaning.

Korean EFL Learners’ Vocabulary Use in Reading-based Writing: According to Topic and ... 101

TABLE5 Descriptive Statistics: Reading Proficiency

Dependent variables Reading proficiency Mean SD N

Kl RH 84.304 5.212 60 RL 83.195 6.191 50

FW RH 47.730 7.366 60 RL 46.962 5.050 50

CW RH 35.785 6.026 60 RL 36.234 5.649 50

K2 RH 6.756 3.610 60 RL 7.373 4.457 50

AWL RH 4.969 11 .678 60 RL 2.976 1.517 50

OLW RH 5.455 2.373 60 RL 6.455 3.221 50

TABLE6 Tests ofBetween-Su펙ects Effects: Reading ProficiencμJPA)

Source Dependent Meansquare df F Sig variables Kl .332 .014 .907

Reading FW .130 .005 .943 proficiency CW .047 .002 .961 (JPA) K2 .490 .102 .751

AWL 199.794 1.349 .251 OLW 19.706 2.217 .142

To further examine whether the overal1 eff농cts of reading proficiency remains the same

across difIerent topics, a MANOVA was perfonned for each topic. Table 6 and Table 7

summarize the results of the analysis. As indicated in Table 6, when the students were

asked to write about judging people by appe앙없lce， their use of vocabulary did not difIer

accon;ling to their reading proficiency. The student writing on a more difficult topic also

displayed similar lexical profiles regardless ofthe two proficiency groups (Table 7).

The finding indicates that the students' reading proficiency did not contribute to

significant difIerences in their English vocabulary profiles shown in writing and that

writing topics did not create significant eff농cts， either. 까lÏs suggests that leamers’ LFPs

were not so much related to their reading proficiency. More specifical1y, the LFP does not

seem strong enou양1 to difIerentiate advanced readers from low proficient readers. As

Laufer and Nation (1995) reported, the LFP may be a good index oflexical proficiency. 1t

may thus be used to difIerentiate the lexical quality of leamer writing at difIerent levels of

proficiency, rather than te l1 good readers from poor ones.

102

Source

Reading proficiency (DPI)

Kim, Sung-Yeon & Ryoo, Young-sook.

TABLE7 Tests of Between-Subjects Eff농cts: Reading Proficiency (DPI)

Dependent variables Mean squ없e df F Sig.

Kl 57.998 3.958 .052 FW 28.203 .480 .492 CW 12.470 .693 .409 K2 27.639 3.047 .087 AWL .341 .182 .671 OLW 8.691 1.547 .219

To put it difIerently, the students' reading proficiency may not guarantee their lexical

proficiency in writing. The finding that their reading proficiency did not predict their

lexical proficiency in writing may be because L2 reading comprehension involves various

factors, such as learners' background knowledge, density ofunknown words in a passage, and learners' ability to infer from the passage,.etc. Another possible explanation is that L2

learners’ knowledge of receptive vocabulary difIers froin their ability to use productive

vocabulary. Thus, being able to recognize words does not necessarily mean the active use

ofthe words in writing, since the two types ofvocabulary are two difIerent entities.

3. Students’ Writing Proficiency and Vocabula깨 Use

The total number of student writings was 42 for the hi양1 proficiency group (WH) and

38 for the low proficiency group (WL) because the students in each group (WH, n=21;

WL, n=19) wrote two essays on the two difIerent topics (JPA and DPI). Student writing

was then analyzed with the on-line computer program, VocabPl1생le to obtain the students’

vocabulary profiles. Then, a MANOVA was performed to compare lexical frequency

profiles of the high and the low group. Table 8 presents the efIects of writing proficiency

on learners’ vocabulary profiles.

As seen in the table, statistically significant difIerences were found in Kl and function

words. In other words, advanced writers difIered from low proficient writers in the way

they used . the function words and the Kl words. For more details about the group

difIerence, descriptive statistics were obtained, as summarized in Table 9. In the

comparison of the mean scores across the two proficiency groups, we can see that

advanced writers used more Kl words and function words than their counterparts, which

confirms the results from s떠.tistical testing. According to desc디ptive s빼stics alone, hi빼y

proficient writers also used more academic words than low proficient writers, althou방1 the

difIerences were negligible.


TABLE8 Tests of Betweeo-Subjects Eπects: Writiog Proficieocy

Source Dependent variables Mean square df F Sig.

K 1 176.577 5.606 .020 FW 373.171 15.949 .000

Writing CW 36.433 1.321 .254 proficiency K2 43.804 2.3 11 .133

AWL 65.133 .626 .431 OLW 27.695 3.166 .079

It is interesting that the low proficient writers produced sli야tly more K2 words, content

words, and off the list words, although the differences were not statistically significant.

This finding conσadicts the general expectation that advanced writers would use more

sophisticated vocabulary such as K2 words and OLWs in their writing. It is noteworthy

that the . students with low levels of reading proficiency used more K2 words and off the

list words. This may be p따tly due to their strategy use. That is, when students have lirnited

proficiency in reading and writing, they are prone to use advanced vocabulary as well as

content words in the source texts.

TABLE 9 Descriptive Statistics: Writio융 Proficieocy

Dependent variables Writing proficiency Mean SD N

KI WH 84.927 5.750 42 WL 81.952 5.456 38

FW WH 49.468 4.686 42 WL 45.143 4.999 38

CW WH 35 .458 5.4 19 42 WL 36.809 5.060 38

K2 WH 6.367 4.308 42 WL 7.849 4.404 38

AWL WH 5.182 13.941 42 WL 3.375 1.996 38

OLW WH 5.646 2.628 42 WL 6.824 3.285 38

For a further comp때son of the two proficiency groups according to the two different

topics, a MANOVA was performed for both JPA and DPI (see Table 10 and Table 11).

Surprisingly, the topic-based comparison yielded different results. As indicated in Table 10, significant mean differences were found for JPA in terms ofKl words, K2 words, function

words, and OLW.


TABLE 10 Tests ofBetween-Subjects Effects: Writing Proficiency (JPA)

Source Dependent var떠b1es Mean square df F Sig.

K1 196.450 9.500 .004 Writing FW 223.707 12.252 .001 proficiency CW .903 .070 .792

K2 21.543 5.666 .022 A WL 139.584 .680 .415 OLW 60.625 6.168 .018

on the other hand, for DPI the significant mean difference was noted only for function

words, as shown in Table 11. It can be inferred from the finding that function words can be

a good indicator of learners' writing proficiency, regardless of topics. More detailed

comp않isons are given in Table 12 and Table 13, which summarize descriptive statistics for

the two topics according to writing proficiency.

TABLE 11 Tests of Between-Subjects Effects: Writing Proficiency (DPI)

Source Dependent variables Mean square df F Sig.

Writing proficiency

KI FW CW K2 AWL OLW

22.814 152.829 57.548 22.263

.161

.118

1.266 .268 5.149 .029 3.191 .082 1.705 .199 .105 .747 .018 .894

As shown in Table 12, in writing on a relatively easy topic, high1y proficient writers

(WH) generated a greater amount of Kl words and function words, compared to their

counterp없잉. On the other hand, low proficient writers (WL) produced sli방ltly more K2

words and off the list words, which may have been due to their sσategy use. The

differences in descriptive statistics confmn the findings from the MANOVA. The notable

difference between the two groups in their use of academic words, which may be due to

the big standard deviation of the hi앙11y proficient group, did not lead to a statistically

significant one.

For a more difficult topic, the only significant difference was noted in the use of

function words (Table 11). π1Ís was also observed in descriptive statistics, as in Table 13.

Althou양1 statistically non-significant, the proficient group used slightly more Kl words

and off the list words than the low proficiency group. The students with limited

proficiency in writing used a few more K2 words, content words and academic words. All

these mean differences, however, were not big enou앙1 to lead to statistically significant

results (see Table 11).


TABLE 12 Desc꺼ptive Statistics: Writin훌 Proficiency (JPA)

Dependent variables Writing proficiency

Mean SD N (JPA)

K1 WH 89.056 3.806 21 WL 84.618 5.250 19

FW WH 49.641 4.3 12 21 WL 44.905 4.229 19

CW WH 39.413 3.506 21 WL 39.714 3.672 19

K2 WH 3.136 1.660 21 WL 4.606 2.228 19

AWL WH 7.608 19.609 21 WL 3.867 2.477 19

OLW WH 4.445 2.064 21 WL 6.911 4.002 19

TABLE 13 Descriptive Statistics: W꺼ting Proficiency (DPI)

Dependent variables Writing proficiency

Mean SD N (DPl)

K1 WH 80.798 4.182 21 WL 79.286 4.316 19

FW WH 49.295 5.134 21 WL 45 .381 5.777 19

CW WH 31.503 3.881 21 WL 33.905 4.619 19

K2 WH 9.598 3.657 21 WL 11.092 3.563 19

AWL WH 2.757 1.232 21 WL 2.884 1.242 19

OLW WH 6.846 2.621 21 WL 6.737 2.480 19

From the students' vocabulary profiles according to writing proficiency, we can see that

the more advanced the learners were, the more function words they used in their writing.

The finding indicates that the use of function words is associated with students' writing

proficiency. One possible explanation about the fmding is that proficient L2 writers are

more familiar with using various function words such as articles, prepositions, relative

pronouns, etc. Unlike advanced writers, low proficient writers have 따lÏted knowledge

about function words and thus are not able to use them in language production.

The 마lding that hi방lly rated writing contained more function words implies that

function words may be a major indicator of students’ writing proficiency. A similar

conclusion was also drawn by Morris and Tremblay (2002) as cited in Morris and Cobb


(2004). Moπis and Tremblay found that hi양ùy rated students’ essays carried more

function words.

v. CONCLUSION

The present study investigated the relationship between Korean c이lege students' lexical

proficiency and their reading and writing proficiency. In addition, the study examined

whether writing topic influences Korean EFL leamers’ vocabulary use in reading-based

English writing.

The results of the study indicated that the students' use of vocabulary in their writing

differed significantly according to topic. Differences were found in almost all of the

vocabulary lists, such as Kl , CW, K2, and OLW. More specifically, an easier topic was

associated with the use ofthe first 1000 words (Kl) and content words; a more difficult

topic was associated with the use ofthe second 1000 words (K2). πlÎs finding tells us how

the students' written vocabulary was affected by source texts provided for the in-class

writing task.

With regard to the relationship between reading proficiency and lexical profiles, none of

the vocabulary profiles were found to be si뺑ficantly different according to reading

proficiency. on the other hand, proficient writers were found to produce more Kl words

and fimction words. According to topic-based comparison, for JPA, proficient writers

generated more KI words and fimction words, whereas less proficient writers produced a

hi양ler proportion of K2 and OLW. This indicates that writing proficiency involves more

dexterous use of words that are highly frequent, not necessarily the ability to use more

sophisticated words. For a more difficult topic, DPI, proficient writers were found to use

more function words than their counterparts.

The present study has several important pedagogical implications. First, writing topics

and reading materials should be fully considered when providing reading-based writing

tasks since different topics can lead to significantly different vocabulary profiles. πle

present study found that students relied on the source texts provided for a writing task,

regardless of their language proficiency levels. Therefore, when providing reading-based

writing tasks for students, the reading material is an important factor to consider as well as

writing topic. Classroom teachers should also design tasks that encourage the students to

make a full use of the source texts.

Another finding of the study showed that EFL learners' lexical proficiency assessed by

the LFP was not related to their reading proficiency. In other words, the students' reading

proficiency did not show significantly different vocabulary size assessed by the LFP. It

s

Korean EFL Learners' Vocabulary Use in Reading-based Writing: According to Topic and ... 107

context (reading) and the ability to use them in context (writing). π1Ïs finding is

particularly informative for classroom teachers because previous studies have shown that

L2 learners' acquisition of productive vocabulary usually comes after their receptive

vocabulary, and thus L2 leamers' receptive vocabulary seems to be larger than productive

vocabulary.

In addition, it is important to note that the LFP may not be the best predictor of Korean

college students' reading proficiency although the LFP has been shown to reliably

differentiate leamers with different proficiency levels. The results of the study do not seem

to support this, in that the LFPs of the two different reading proficiency groups did not

show a significant difference. Therefore, classroom teachers need to be cautious about

using the LFP as an indicator ofEFL learners' English proficiency.

Finally, the inclusion of vocabulary profiles as part of writing assessment is worthy of

consideration. The students' vocab비ary profiles were significantly different according to

their writing performance. The study results revealed that students' writing performance

was definitely affected by their vocabul없Y in writing because hi앙dy-rated writing showed

that the students made a more use offunction words. This finding also tells us that students

should leam how to make appropriate use of function words to obtain hi앙1 ratings on their

wntmg.

πle findings of the present study, while 띠teresting and informative, should be

confirmed in a replication study with more participants, different types of writing tasks, and other types of language proficiency tests. In other words, future studies should

consider the effect of different writing tasks on students’ vocabulary profiles according to

language proficiency levels. The analysis of the writing task effects on students'

vocabulary profiles may provide a deeper understanding of the relationship between L2

writing and vocabulary knowledge (LFP). Further research is also needed to explore

whether different types of language proficiency tests would yield different results for the

relationship between leamers' vocabulary knowledge (LFP) and their language proficiency.

In particul따~ the relationship between comprehension 뻐d production of L2 vocab비ary

may provide some guidance for future English writing classes for Korean c이lege students.

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Applicable levels: primary, secondary, tertiary Key words: vocabulary profiles, lexical frequency profile (LFP), reading integrated writing,

reading proficiency, writing proficiency, topic

‘ . Sung-Y eon Kim - 끼."Hanyang University

:;~{1.，7 Haengdangdong, Seongdonggu 익 Sëoul (1 33-791), Korea

TEL: (02) 2220-1141 E-mail: sung양‘k이im@h뼈lanyan탬l땅g.ac . k‘kr 〈αr

Young씌ook Ryoo 101-401', Hanyang Su-ja-in Apt. Bora-dòng Kiheung-gu Yongin-si Kyungki-do, 446-904, Korea Tel: 010-6360-1756 E-mail: ysryoo2@hanmai l.net

ReceNed in Decémber, 2010 Reviewed in:[ebruary, 2011 Revised version received in March, 2011

-.、"'"

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