(2024) 14:2
Kamiya ﻿Language Testing in Asia
https://doi.org/10.1186/s40468-024-00272-6

Language Testing in Asia

Open Access

RESEARCH

Is the Common Test for University
Admissions in Japan enough to measure
students’ general English proficiency? The caseof the TOEIC Bridge
Nobuhiro Kamiya1*   *Correspondence:
kamiya@fic.gpwu.ac.jp
1

Department of International
Communication, Gunma
Prefectural Women’s
University, 1395‑1 Kaminote,
Tamamura‑Machi, Sawa‑Gun,
Gunma 370‑1193, Japan

Abstract
This study investigated to what extent the scores of two English tests are correlated
to each other, namely, the English test of the Common Test for University Admissions(Common Test, henceforth) in Japan and the TOEIC Bridge, a commercially available
English test developed by Educational Testing Service (ETS) that measures four skillsof listening, reading, speaking, and writing. Moreover, this study examined to what
extent the two tests’ constructs overlap from the viewpoint of L2 competence. In total,
128 university freshmen and high school seniors took the Common Test at the official
venues and also the TOEIC Bridge at the researcher’s university (n = 92) or at home(n = 36) a few months later. Results indicated that the scores of the corresponding skills
are moderately correlated to each other across the two tests (Reading = .548; Listening = .646; Total = .732). Confirmatory factor analyses demonstrated that the degreeof data fitting of the three models of test constructs (unitary, correlated skills, correlated tests) was statistically similar to each other. On the basis of substantive and statistical results, however, we claim that the correlated skills model should be chosen
as the best-fit model and, consequently, that the productive skills should be measured
in addition to the Common Test.
Keywords: Common Test for University Admissions, TOEIC Bridge, Language Testing,L2 competence structures

Introduction
BackgroundA majority of Japanese high school students who wish to continue studying in tertiary
schools are required to take a test held nationally, organized by the National Center for
University Entrance Examinations in Japan (National Center, henceforth). The inceptionof this test dates back to 1979, which was updated to the National Center Test for University Admissions (Center Test, henceforth) in 1990. Then, the newest version, the Common Test for University Admissions (Common Test, henceforth), was launched in 2021.
The Common Test’s English test consists of two sections of reading and listening and is© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permitsuse, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original
author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third
party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or
exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://
creativecommons.org/licenses/by/4.0/.

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held face-to-face at around 700 testing centers all over Japan. Due to its large number oftest-takers, which counts over 500,000 annually, all of the questions are in a multiplechoice format for the sake of time efficiency and fairness (see Table 1).
The Ministry of Education, Culture, Sports, Science, and Technology (MEXT, henceforth) originally scheduled to replace the English test within the Center Test with commercially available, private English tests of four skills when the Center Test would beswitched to the Common Test due to the criticism that the Center Test measured only
the receptive skills (reading and listening), despite the fact that the national curriculum guidelines stipulate that not only the receptive skills but also the productive skills(speaking and writing) must be cultivated in a balanced manner in Japanese high schools(MEXT, 2018a). This motivated Kamiya (2017) to conduct a study to investigate thescore compatibility between the Center Test and one of the four-skilled private tests,
namely the TOEFL Junior Comprehensive. The overall results supported the validity of a
replacement of the former with the latter; however, the data also indicated that test-takers’ general English proficiency alone occupied the major portion of the scores, regardless of skills, across the two tests.
Due to several concerns raised during the transition period from the Center Test to
the Common Test, such as difficulty in securing fairness across students with diverse
economic statuses (i.e., opportunities to take private tests) and residential background(i.e., accessibility to testing venues) and score incompatibility between different private
tests derived from distinct test constructs, MEXT officially announced in 2019 to postpone the replacement until 2024. However, partly because MEXT planned to use both
the Common Test and private tests concurrently until then, a few major changes havebeen made from the Center Test to the Common Test. First, the questions to measure “pronunciation and accent” and “grammar and usage” were deleted in the reading
section because, arguably, (a) the former would be better measured in a speaking test,
whereas the latter in a writing test; (b) the knowledge and skills necessary to answer
these questions do not emulate what is necessary for communication; and (c) they canbe measured indirectly even in reading and listening sections (National Center for University Entrance Examinations, 2021). This essentially resulted in the section predominantly measuring reading comprehension skills alone. Second, in the Center Test, thescores were unevenly divided between reading (200) and listening (50) sections. But
reading and listening sections each weigh evenly in the Common Test (100 & 100) (however, the actual score allocation of each of these two sections is left to the discretion of

Table 1 Components of the English test of the Common Test

Contents

Reading

Listening-There is no prescribed test format common every
year-Typical passages include newsletters, articles, blogs,
emails, posters, and so on

1. Short sentences
2. Short conversations
3. Short monologues
4. Long monologues
5. Long conversations

Number of questions

47–49

37

Test time (Minutes)

8030

Score range

0–100

0–100

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each institution). After a series of meetings held by a special committee run by MEXT,
however, MEXT announced in 2021 that the introduction of private tests at university entrance examinations would be aborted, mainly for the abovementioned reasons.
Due to these changes from the Center Test to the Common Test, the applicability of theresults obtained in Kamiya (2017) to the Common Test was called into question, whichis the rationale for conducting the present study.
TOEIC Bridge

Although it would have been ideal to use the same private test as Kamiya (2017), namely,
the TOEFL Junior Comprehensive, for the sake of comparability of results, at the timeof conducting this study, the TOEFL Junior Comprehensive was defunct. Therefore,
we needed to choose another private test. Among various candidates, we selected theTOEIC Bridge because it is designed to target beginning to lower-intermediate level
learners, namely, from A1 till B1 levels of the Common European Framework of Reference
for Languages (CEFR; Council of Europe, 2020) (Schmidgall, 2021). According to thesurvey conducted by MEXT, only 0.3–0.4% of third-year high school students reachedB2 levels (MEXT, 2018c). Thus, we considered the test appropriate from the perspectiveof difficulty (but see the Limitations section).
The TOEIC Bridge originally started in 2001 as a test to measure two skills, reading
and listening only. However, it had been upgraded to measure four skills starting in
2019. The test is held widely in around 35 countries (as of 2019; IIBC, personal communication, March 27, 2023). In 2021, there were 140,700 and 34,900 test-takers for listening and reading and speaking and writing, respectively (IIBC, n.d.). The test comprises
four skill-based sections as shown in Table 2. The reading and listening tests can betaken either on paper or online, and all the questions are presented in a multiple-choice
format. In the speaking test, test-takers record their voices through microphones in
response to prompts. In the writing test, they unscramble words to complete sentences
or type sentences or paragraphs. Both speaking and writing tests are held only online
and their answers are evaluated by raters certified by Educational Testing Service (ETS),
the organization that administers the TOEIC Bridge. Due to its recent introduction, to
our knowledge, there have been only two attempts to compare its scores with the Common Test (and none with the Center Test). IIBC, which runs the TOEIC Bridge in Japan,
has reported correlation coefficients of reading and listening scores between the TOEIC
Bridge and the Common Test for 2 years in a row (IIBC, 2021, 2022). The results showed

Table 2 Components of the TOEIC Bridge

Contents

Listening

Reading

Speaking

Writing

1. Four pictures
2. Question-response
3. Conversations
4. Talks

1. Sentence completion
2. Text completion
3. Reading comprehension

1. Read a short text aloud2. Describe a photograph
3. Listen and retell
4. Short interaction
5. Tell a story
6. Make and support a
recommendation

1. Build a sentence
2. Write a sentence
3. Respond to a brief
message
4. Write a narrative
5. Respond to an
extended message

Number of questions

50

50

8

9

Test time (minutes)

25

35

15

37

Score range

30–10030–10030–10030–100Kamiya ﻿Language Testing in Asia

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moderate to strong correlations in reading (r = 0.554, 0.592), listening (r = 0.490, 0.559),
and with total of both sections (r = 0.623, 0.665). However, the score of the Common
Test was self-reported, not confirmed by official score reports; thus, there is a suspicion
that their self-scoring might not be accurate. More importantly, their data on the TOEIC
Bridge were limited in scope without speaking or writing scores. In sum, there has notbeen any attempt to explore the score relationships between the Common Test and fourskilled private tests.
Models of test constructs and structure of L2 abilities

This study seeks to unveil the test constructs of the Common Test and the TOEIC Bridge
through the lens of the structure of L2 abilities. Because there are a host of studies on
this topic, we restricted the selection only to those that used at least one of the widely
available private tests. As can be seen in Table 3, four major models of a structure of
L2 abilities have been proposed as their candidates. A unitary or unidimensional model(Fig. 1) presupposes that L2 abilities are a single construct. Therefore, all of the testscores will be subsumed under a single, unobserved latent variable. An uncorrelated
model (Fig. 2) presupposes that L2 competence consists of multiple, divisible, first-ordervariables, such as receptive and productive skills, but these variables are not correlated
highly to each other. When these are highly correlated, it is called a correlated model(Fig. 3). Finally, when all of these first-order variables are subsumed under a single second-order variable, it is called a high-order, second-order, or hierarchical model (Fig. 4).
The history of these inquiries originated from Oller (1979). He analyzed multiple data
sets and consistently claimed that all data could be subsumed under a single dimension.
He even stated, “the current practice of many ESL programs, textbooks, and curriculaof separating listening, speaking, and reading and writing activities is probably not justpointless but in fact detrimental” (p. 458). His indivisibility hypothesis instigated a hostof ensuing explorations, most, if not all, of which criticized Oller’s use of principal component analysis (see Fouly et al., 1990), and instead, adopted more rigorous methods ofconfirmatory factor analysis.
Since then, among numerous kinds of private tests, a lot of attention has been paid to
the TOEFL, probably due to its large number of test-takers with various backgrounds(around a million test-takers in around 160 countries annually; ETS Japan, personalcommunication, May 30, 2023). This convenient feature makes it easy to secure strong
statistical power and to compare data among multiple diverse groups (Stricker & Rock,2008). Through this line of research, a clear trend has appeared, which is that either acorrelated or a higher-order model is acceptable, rejecting unitary and uncorrelated
models (except Wilson, 2000, but see In’nami & Koizumi, 2012, for its possible reasons).
When the number of first-order factors is two, a higher-order model cannot be identified. When it is three, these two models are statistically indistinguishable from eachother; in such a case, a higher-order model is chosen based on the principle of parsimony. Thus, it is often impractical to decide which one is the best fit. As the consensus
has been almost reached on the structure of L2 abilities, the momentum toward identifying the structure of L2 abilities has waned, and we witness a shift of studies toward
validating newly made tests, such as the TOEFL iBT and the TEAP when they came out
in public. Pertinent to the present study, however, is that there has been only one study

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Table 3 List of studies on test constructs and structure of L2 abilities using private tests
Study

ParticipantsParticipants’ L1

Private Tests

Unitary

Uncorrelated Correlated

Bachman et al.
(1995)

Various

Various

Cambridge Examinations & TOEFL
PBT

×

×

△

○

Fouly et al.
(1990)

University
students

Various

TOEFL PBT + α

×

×

○

○

Gu (2015)

Aged 11–15

Various

TOEFL JC

Hale et al. (1988)

Various

Various

TOEFL PBT

×

×

×

×

-

×

○

Hale et al. (1989)

Various

Various

TOEFL PBT

University
students

Mostly Japanese

TOEIC LR

×

×

×

○

In’nami et al.
(2016)

University
students

Japanese

TEAP & TOEFL iBT

×

×

×

Kamiya (2017)High school
students

Japanese

TOEFL JC & Center
Test

Kunnan (1995)

Various

Various

TOEFL PBT

Manning (1987)

Various

Various

TOEFL PBTJapanese

TEAP

Nakamura (2022) University
students
Oller (1979)

Various

△

×

○

○

×

○

×

×

×

○

×

×

×

○

×

Various

TOEFL PBT

Oller and Hinofo- Universitytis (1980)
students

Various

TOEFL PBT

Stricker and Rock Various(2008)

Various

TOEFL iBT××

Sawaki et al.
(2008)

Various

Various

TOEFL iBT××

Sawaki et al.
(2009)

Various

Various

TOEFL iBT××

Sawaki and
Sinharay (2018)

Various

Various

TOEFL iBT×-

Shin (2005)

Various

Various

TOEFL PBT

Swinton andPowers (1980)

Various

Various

TOEFL PBT×

Wilson (2000)

VariousJapanese &KoreanTOEIC LR

×

×

×

×

×

○

○

○

In’nami andKoizumi (2012)

×Higherorder

×

×

△

△

△

○

△

○
×

○
-

×

×

○

○

○

△

○

○

-

×

×

The table is not intended to be an exhaustive list of previous studies on this subject. TEAP Test of English for Academic
Purposes (available only for Japanese university applicants), TOEFL JC TOEFL Junior Comprehensive, TOEIC LR TOEIC
Listening & Reading. “△” denotes that this model was chosen as the second best. “–” denotes that this model was notconsidered. In the case of higher-order model, it was not considered due to the fact that the number of first-order factors
was less than four (see the main text for its rationales)on the TOEIC (In’nami & Koizumi, 2012), but only for listening and reading, not for
speaking or writing, and none for the TOEIC Bridge.
Somewhat unpredictably, in Kamiya (2017), which targeted the Center Test and the
TOEFL Junior Comprehensive, although the correlated model was chosen as the bestfit model, the unitary model was found to be almost equally a good fit as well. However,
although not reported in the article, when only the data of the TOEFL Junior Comprehensive were extracted and analyzed, the correlated model with two variables of receptive and productive skills was shown to be clearly better than the unitary model (e.g.,
SRMR = 0.0040 and 0.0132, respectively). This implies that the Center Test, especially its
reading section, was measuring general English proficiency rather than reading abilities
alone, which skewed the whole data set to close on the unitary model. If so, since thepronunciation and grammar sections in the Center Test were excluded at the transition

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Fig. 1 Sample of unitary or unidimensional modelFig. 2 Sample of uncorrelated modelFig. 3 Sample of correlated model

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Fig. 4 Sample of high-order, second-order, or hierarchical modelto the Common Test, we can predict that, in the case of the Common Test, the correlated model will demonstrate a better fit when compared to the unitary model.

Research questions

Some additional explanations are necessary regarding the models that we consider. First,
owing to the fact that there are only two first-order variables (e.g., receptive and productive skills), this study is incapable of identifying a higher-order model. Second, uncorrelated models will not be considered as they were unidentified in Kamiya (2017). Third,
there will be two versions of correlated models to be examined, namely, skill-based andtest-based models. The former is following the convention of past literature (receptive
and productive skills). For the latter, whereas the Common Test must strictly follow thenational curriculum guidelines (MEXT, 2018a), the TOEIC Bridge has no such restriction for its worldwide administration. Therefore, dividing the test scores into test types,
rather than skills, may produce a better fit. Therefore, the test-based model was additionally considered. In sum, the present study was guided by the following two researchquestions.
1. How are the scores of the Common Test and the TOEIC Bridge correlated with eachother?
2. Which of the three models (unitary, correlated skills, and correlated tests) best represents the test constructs of the Common Test and the TOEIC Bridge?

Methods
Participants

The original plan was to recruit only high school students, following the procedure in
Kamiya (2017); however, due to the COVID-19 pandemic, the researcher could not get
permission to do so from the university. Therefore, the students of the researcher’s university were invited to participate throughout the study period. In the final year, though,this restriction was lifted, so a group of high school students participated. In total, 128
Japanese learners of English aged 18 or 19 participated in this study (118 females, 10
males), which consisted of four groups as shown in Table 4.

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The university students were all freshmen. Efforts were made to recruit students withdiverse majors in order to secure a wide range of English proficiencies for ensuringhigh reliability of analysis (Mizumoto, 2014): international communication (n = 36),
Japanese literature (n = 19), English literature (n = 18), fine arts (n = 10), and liberalarts (n = 10). The high school students were from five schools in the same district. This
study was approved by the ethics committee of the researcher’s university and all of
the participants agreed to participate in the study and read and signed the consent
form.
Procedure and analyses

For university students, solicitation emails were sent to all freshmen right after enrollment from the researcher. For high school students, the researcher first contacted theprincipals of 10 high schools for permission for recruitment of their third-year students.
After all of them agreed, the flier was distributed to them either face-to-face (paper) or
online (PDF) from a teacher in each school. For both university and high school students, those students who were interested in participation voluntarily contacted theresearcher.
All of the participants took the Common Test at the official venues in January. Highschool students took the TOEIC Bridge in the following March, in the same month ofgraduation. University students took it in the following May, a month after enrollment.
Three groups took the TOEIC Bridge in a CALL Lab at the researcher’s university. Dueto the spread of the pandemic, following the regulations imposed by the university, thosein 2021 needed to take it online at home using Zoom with a camera on, invigilated by the
researcher. The scores of the Common Test were confirmed by the official score reports
provided by the National Center. The scores of the TOEIC Bridge were confirmed by theofficial score reports provided by IIBC.
Analyses were conducted in three steps. First, Pearson’s correlations were conductedin order to see to what extent the score of each section and total of the Common Test
and the TOEIC Bridge are correlated. Second, confirmatory factor analyses (withmaximum likelihood estimation) were conducted to detect the model that best fits thecurrent data. Finally, chi-square difference tests were conducted in order to compare
model fits. In accord with the recommendation not to conduct an exploratory factor analysis prior to a confirmatory factor analysis on the same data set, as it leads tomodel overfit (overly optimistic modeling) (e.g., Fokkema & Greiff, 2017), it was not
implemented.
Table 4 Demographic information of participantsYear

Participants

N

Male

FemaleAdministration dates
Common Test

TOEIC Bridge

2021

University students

36

0

36

January 16

May 29, 30 (online)

2022

University students

32

0

32

January 15

May 7

2023

University students

25

0

25

January 14

May 13, 16, 17

2023

High school students

35

10

25

January 14

March 14, 16

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Results
Descriptive statistics

Although the National Center tries to equalize the test difficulty of the Common
Test across multiple years, there are variations in the mean scores because the scores
are not adjusted to secure the same level of difficulty, a practice seen in the TOEFL
and the TOEIC, called score equating (Livingston, 2014). Therefore, the mean scoresof the Common Test need to be examined to check whether the three versions of
the Common Test used in the present study had approximately the same difficultylevel. Table 5 shows the means and standard deviations of the Common Test acrossJapan in the 3 years when this study was conducted (National Center for University
Entrance Examinations, n.d.-d). Although the mean scores admittedly varied among
these 3 years, no score adjustment was made and all the scores were aggregated forthe following reasons. First, the National Center stipulates that scores will be adjusted
when averages across subjects differ by over 20 (although this applies only to thosetests conducted in the same year, and English is not a subject for the adjustment),
but the widest gap in the present data was around eight (61.80–53.81 = 7.99 for reading), which is much lower than the benchmark of 20. Second, one-way ANOVAs confirmed that the total scores of the Common Test (p = 0.100) and the TOEIC Bridge(p = 0.113) were not significantly different across the four groups of participants.
Because the score equivalency of the TOEIC Bridge is established by score equating(Livingston, 2014), the English proficiency of these four groups can be assumed to behomogeneous. Since the groups’ scores on the Common Test were also similar, theCommon Test’s score equivalency was presumed. Table 6 shows the descriptive statistics of the scores of the participants in this study.
Pearson’s product‑moment correlation matrix

Table 7 shows the results of Pearson’s product-moment correlation matrix. As
expected, the highest correlations are observed between the scores of each section
and its total score within the same test, except for the TOEIC Bridge writing, whichmarked a rather low coefficient (r = 0.661). More importantly, the scores of the corresponding skills also demonstrated relatively high coefficients across the two tests(reading = 0.548; listening = 0.646). Moreover, the total score showed an even higher
coefficient (r = 0.732) (see Figs. 5, 6, and 7).

Table 5 Descriptive statistics of the Common Tests across Japan
Reading

Listening

Total

Full score

100

100

200

2021

58.80 (21.44)

56.16 (16.45)

114.962022

61.80 (20.30)

59.45 (18.16)

121.252023

53.81 (20.99)

62.35 (18.82)

116.16

Mean (standard deviation)

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Table 6 Descriptive statistics of scores
Common Test
Reading

TOEIC Bridge

Listening

Total

Listening

Reading

Speaking

Writing

Total

Full score

100

100

200

50

50

50

50

200

Mean

70.05

74.13

144.17

39.30

43.70

40.05

45.69

168.73

SD

14.76

11.63

22.99

6.77

5.69

7.63

4.40

19.75

Max

100

100

200

50

50

50

50

199

Min

28

43

75

20

22

15

27

102

Skewness

−.39

−.46

−.39

−.59

−1.48

−1.13

−1.62

−.99

Kurtosis

−.11

.23

−.04

2.64

−.15

1.11

2.78

.91

Speaking

Writing

Total

SD Standard deviation

Table 7 Results of Pearson’s product-moment correlation matrix
Common Test
Listening

TOEIC Bridge
Total

Listening

Reading

Common Test
Reading

.512

.901

.492

.548

.540

.350

.613

Listening

-

.834

.646

.573

.514

.374

.668

-

.643

.642

.606

.414

.732

Total
TOEIC Bridge
Listening
Reading
Speaking
Writing

-

.687

.582

.395

.854

-

.519

.462

.827

-

.440

.833

-

.661

All correlations are significant at p < .001

Confirmatory factor analyses

The results of model fits are presented in Table 8. The results of standardized regression weights are graphically presented in Figs. 8, 9, and 10. The results of unstandardized regression weights, variances, and squared multiple correlations can beobtained in the Additional file 1.
According to Table 8, all of the three models seem to be satisfactorily well
fit since most of the indices meet the minimum requirement levels (i.e.,
RMSEA < 0.08, SRMR < 0.05, CFI > 0.95, NFI > 0.95, TLI > 0.95; Byrne, 2016).
Because the unitary model is nested in the other two models, chi-square difference
tests were performed. The results demonstrate that the unitary model was not asignificantly better fit than the correlated skills model (p = 0.182) nor the correlated tests model (p = 0.688). That is to say, statistically speaking, all of these threemodels are equally well fit.

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Fig. 5 Scatter plot of reading scores (r = .548)

Fig. 6 Scatter plot of listening scores (r = .646)

Discussion
RQ1: Correlations between the Common Test and the TOEIC Bridge

The results of Pearson’s product-moment correlations showed that the scores of theCommon Test and the TOEIC Bridge are moderately correlated for reading (r = 0.548),
listening (r = 0.646), and also total (r = . 732). A higher correlation coefficient for the total
score than for the individual skill (reading or listening) is commonly observed in otherstudies in which the total score is derived from the sum of the two skills (reading andlistening) (IIBC, 2021, 2022) and of the four skills (Kamiya, 2017). Inspecting Figs. 5, 6,
and 7, we surmise that this is probably because the total score better reflects the participants’ English proficiency owing to the reduced amount of measurement error by combining the scores of multiple tests, which decreases the deviations from the regression
line. Plonsky and Oswald (2014) proposed new benchmarks of correlation coefficients

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Fig. 7 Scatter plot of total scores (r = .732)

Table 8 Results of model fits
χ2

df

RMSEA [CI]

SRMR

CFI

NFI

TLI

Unitary

13.2529.061 [0, .126]

.032

.986

.960

.977

Skills11.4768.058 [0, .128]

.029

.989

.965

.979

Tests

13.0918.071 [0, .137]

.032

.984

.960

.969

df Degree of freedom, CI 90% confidence interval

Fig. 8 Standardized regression weights of the unitary modelfor L2 studies, with 0.25 being weak, 0.40 being medium, and 0.60 being large. According to these criteria, all of these correlations can be said to be medium to large. Thesefigures are roughly equal to those correlation coefficients obtained for the Common

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Fig. 9 Standardized regression weights of correlated skills modelFig. 10 Standardized regression weights of correlated tests model

Table 9 Correlation coefficients between Center Test or Common Test and private tests
Study

Entrance exam

Otsu (2014)

Center Test

Eiken Foundation ofJapan (2015)

Center Test

Kamiya (2017)

Private test

Reading

Listening

Totala

TOEIC

-

-

.80

TOEFL ITP

-

-

.70

TEAP

-

-

.80

STEP ­Eikenb

-

-

.89

Center Test

TOEFL Junior Comprehensive

.78

.75

.86

IIBC (2021)

Common Test

TOEIC Bridge

.55

.49

.62

IIBC (2022)

Common Test

TOEIC Bridge

.59

.56

.67

Present study

Common Test

TOEIC Bridge

.55

.65

.73

a

Total refers to the added score of reading and listening except for Kamiya (2017) and the present study, which refers to theadded score of the four skillsb

STEP Eiken is a test to measure English proficiency conducted in Japan. The test is currently divided into seven levels, fiveof which measure four skills whereas the other two (the lowest levels) measure the receptive skills only

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Test or the Center Test against several private tests, as can be seen in Table 9. However,according to Dorans (2004), the correlation coefficient of 0.866 is minimally necessary
for a test to be replaced by another. Although the interchangeability of the Common Test
and the TOEIC Bridge is not the objective of our inquiry, at least from a psychometricstandpoint, their test constructs are distinct enough to warrant further examination of
their reasons. For the sake of comparisons, we summarized the selected specifications ofthese two tests in Table 10, taken from multiple sources for the Common Test (National
Center for University Entrance Examinations, n.d.-c, n.d.-d) and the TOEIC Bridge(Everson et al., 2021; Schmidgall, 2021; Schmidgall et al., 2019, 2021). From this table, it
is clear that although these tests share some commonalities, such as the objective to deal
with communication in real daily life contexts and CEFR levels to be measured (A1-B1),
there are a number of differences between them.
First, the Common Test presumably targets the life of high school students because
the questions are made considering the “situations in which students learn in the classroom, discover problems in their social and daily lives” (National Center for University
Entrance Examinations, n.d.-b, pp. 1–2). In contrast, the TOEIC Bridge deals with adultlife, which makes some of the questions irrelevant to high school students. For instance,
IIBC provides sample questions about the TOEIC Bridge on their website (IIBC, n.d.). A
listening question plays, “What color is your car?” A reading question (fill in the blank)reads, “We have received your order for twelve yellow roses.” A speaking question asks
to summarize the announcement made by a company president at a staff meeting. A
writing question asks to reply to a question, “what types of training or education do you
think people will need to get well-paid jobs in the future?” High school students would
probably never encounter a situation to be exposed or use any of these sentences in their
daily lives even in the L1 (Japanese).
Second, the Common Test is expected to follow the national curriculum guidelines(MEXT, 2018a) whereas the TOEIC Bridge bears no such obligation. Thus, in the latter, some of the linguistic items may go beyond what is supposed to be covered in theformer. For example, a sample reading section of the TOEIC Bridge (Educational Testing
Service, 2020) has a choice of “An employee’s retirement” in a multiple-choice question.
Although this is a high-frequency phrase in the workplace, high school students may not
be familiar with such a phrase.
Finally, the Common Test mainly consists of American English, and to a much lesser
extent, British English and Japanese-accented English (National Center for University

Table 10 Selected specifications of the Common Test and the TOEIC Bridge
Common Test

TOEIC Bridge

Objective

To measure the skills to use knowledge of English
To measure English language provocabulary, expressions, grammar, and language funcficiency in the context of everyday
tions appropriately in real-life communication according adult life
to the purpose, situation, and circumstance

Dialects

The USA, the UK, JapanThe USA, the UK, Canada, Australia

Restrictions of Yes
guidelines

No

CEFR

A1-B1

A1-B1

Kamiya ﻿Language Testing in Asia

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Entrance Examinations, n.d.-a). This is because Japanese students are used to American
English for two reasons: (a) most, if not all, English textbooks used in Japanese schools
are written in American English (e.g., Mitsumura Tosho, n.d.; Tokyo Shoseki, 2018),
and (b) the majority of teachers who come from abroad to teach English are Americans.
For instance, in one of the largest programs for hiring foreign teachers, the JET (Japan
Exchange and Teaching) Programme, as of 2023, Americans comprise 55% of the entire
faculty (Council of Local Authorities for International Relations, 2015). In regard to theuse of Japanese-accented English, because sharing the same L1 between speakers andlisteners is known to facilitate comprehension (e.g., Tergujeff, 2023), high school students should find Japanese-accented English easier to comprehend. On the other hand,in addition to American and British English, the TOEIC Bridge contains those dialectsof Canada and Australia, both of which are lacking in the Common Test. Because highschool students are unfamiliar with Canadian and Australian English, they may have difficulty understanding them compared to American English.
All in all, these discrepancies in specifications between these two tests may haveyielded correlation coefficients not high enough to be replaceable. Looking at Table 9
we find that most of the correlation coefficients in the previous and the present studies
did not reach the benchmark of 0.866 (Dorans, 2004). This makes sense because the test
specifications required for university matriculations imposed on Japanese high school
students should be quite distinct from those for assessing the English proficiencies oftest-takers all over the world.

RQ2: Test constructs of the Common Test and the TOEIC Bridge

The results of confirmatory factor analyses revealed that the three models compared(unitary, correlated skills, correlated tests) explained the data equally well (see Table 8).
The correlated skills model and the correlated tests model have the same degree of freedom; therefore, a chi-square difference test cannot be conducted between these twomodels. Comparing the values in each index, the correlated skills model seems to besuperior to the correlated tests model (e.g., RMSEA = 0.058 and 0.071, respectively).
Moreover, in the correlated tests model, the two latent variables (Common_Test and
TOEIC_Test) are highly correlated to each other with the correlation coefficient being
0.98. Traditionally, when the correlation coefficient is over 0.9, they are regarded as
being statistically indistinguishable (Gu, 2015). Therefore, we deem that the correlated
tests model should be rejected.
Following this notion, among the two models left (unitary and correlated skills), if we
follow the principle of parsimony, the simpler model with more degrees of freedom (unitary) should be chosen over a more saturated model with fewer degrees of freedom (correlated skills). Yet, because this homogenous result may be ascribed to the small sample
size (see the Limitations section), we must consider other criteria for judgments, and wedeem that the correlated skills model is the best-fit model for the following reasons.
First, as can be seen in Table 3, Oller’s studies are the only ones that fully supported
the unitary model, and a large body of literature following them uniformly negates it.
Based on the accumulation of such empirical evidence, it is more natural to disregard its
viability.

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Page 16 of 20

Second, since the correlation coefficient of the two latent variables (Receptive_skills
and Productive_skills) is not over 0.9, due to the abovementioned reason, it is more
valid to set up these two constructs separately, rather than combining them into a single
construct.
Finally, in order to find out to what extent the TOEIC Bridge was capable of distinguishing the receptive and productive skills, we performed confirmatory factor analysesof two models (unitary and correlated skills) only with the data of the TOEIC Bridge.
Table 11 shows the results of model fits. To our surprise, unlike the TOEFL JuniorComprehensive, the TOEIC Bridge does not seem to well distinguish between receptive and productive skills. A chi-square difference test also confirmed that these twomodels are statistically homogenous (p = 0.128). This may be because of the nature ofsome of the questions for speaking and writing tests, in which integrative skills are necessary to answer such questions (see the Limitations section for another possible reason). Looking at Table 11, the unitary model is superior to the correlated skills models at
two indices (RMSEA and TLI) whereas the opposite is true for the other three (SRMR,
CFI, and NFI). Therefore, there is no consistent pattern as to the superiority of either
model. Compared to that, when combined with the scores of the Common Test, all theindices consistently favor the correlated skills model because the correlated skills modelrecorded (a) the lowest values in RMSEA and SRMR and (b) the highest values in CFI,
NFI, and TLI (Table 8). Adding the scores of the Common Test strengthened the model
fit of the correlated skills model indicating that the Common Test itself measured receptive skills rather than general English proficiency.
Limitations

There were several limitations in the present study. First, there was a time gap of two(high school students) to four (university students) months between the Common Test
and the TOEIC Bridge. This was unavoidable due to logistic reasons. It is unknown
whether the participants’ English proficiency changed, and if so, how much, during thisperiod.
Second, although we aimed to recruit roughly the same number of participants as
Kamiya (2017) (n = 144), due to the limitation on budget, this was unfeasible. This could
be a reason why all three models were found to be homogenously well fit to the data.
Thus, the results should be interpreted cautiously.
Third, although the level of the TOEIC Bridge is appropriate for the majority of highschool students on the national level, it may have been too easy for the participants inthis study. Among the 93 university students, 54 (58.1%) were English majors. All thehigh school students were recruited from high-level schools in the district. According toTable 6, the accuracy rate reached approximately 80% across all the skills and all of theTable 11 Results of model fits of the TOEIC Bridge
χ2

df

RMSEA [CI]

SRMR

CFI

NFI

TLI

Unitary

5.325

2.114 [0, .237]

.0319

.981

.970

.942

Skills3.009

1.126 [0, .300]

.0210

.988

.983

.930

df Degree of freedom, CI 90% confidence intervalKamiya ﻿Language Testing in Asia

(2024) 14:2

data were negatively skewed, which may have weakened its discriminative power. Moreover, the mean score of the writing section was as high as 45.7/50, which may explain
why this section had the lowest factor loading in all the models.
Fourth, 36 participants who participated in the first year of this project needed to takethe TOEIC Bridge online due to the pandemic. Independent t-tests indicate that theyscored higher than those who took it face-to-face for speaking (p = 0.010) and total scores(p = 0.049). Although speculatively, the online participants may have felt less anxious
when speaking English aloud at home alone compared to those who took it in a computerlab with the presence of other students around them hearing their voices from each other.
Although this decision was beyond the researcher’s control, there is some doubt about
their score equivalency. The pandemic facilitated online administration of even highstakes tests, such as the TOEFL iBT, but to my knowledge, there has not been any systematic attempt to validate the score comparability of the speaking section between online
and face-to-face. This point may be worthy of being addressed in future studies.

Conclusion
Commotion ensued around 10 years ago when the idea of replacing the Center Test by
private tests of four skills was introduced by MEXT. After countless heated arguments,
this idea has been officially aborted. The introduction of assessment on the productive
skills, be they speaking and/or writing, to university entrance examinations, does notseem to be happening anytime soon.
However, the picture does not seem completely bleak for three reasons. First, a speaking test, called ESAT-J (English Speaking Achievement Test for Junior High SchoolStudents) has been introduced into an entrance examination for all public senior highschools in Tokyo from November 2022 despite the fact that speaking skills are “the mostlogistically challenging and controversial to assess” (O’Sullivan et al., 2022, p. 12) among
the four skills. Second, a few universities are devising their own ways to measure students’ speaking skills at their entrance examinations (Committee for Selection of Good
Practices in University Admissions, 2022). Third, a growing number of universities are
now utilizing the scores of private tests of four skills for entrance examinations by, forinstance, requiring a certain score for applying or adding extra points to the score of thetest conducted by each university (Kawaijuku Education Institution, n.d.). Thus, albeit
slowly, we are moving forward from the measurements of receptive skills only towardthat of four skills in line with the high school English curriculum guidelines (MEXT,
2018b), which stipulates that all of the four skills must be cultivated in a balanced manner. We truly hope that the National Center will create a reliable and valid measurementof four skills someday. But until that day comes, a viable solution seems to have each
university implement an assessment of productive skills on their own in addition to the
Common Test.
Abbreviations
CEFR	Common European Framework of Reference for Languages
Common Test	Common Test for University Admissions
ETS	Educational Testing Service
MEXT	Ministry of Education, Culture, Sports, Science, and Technology
National Center	National Center for University Entrance Examinations in Japan
Center Test	National Center Test for University Admissions

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Supplementary Information
The online version contains supplementary material available at https://​doi.​org/​10.​1186/​s40468-​024-​00272-6.
Additional file 1. Results of unstandardized regression weights, variances, and squared multiple correlations.
Acknowledgements
First, this study would not be feasible without the continuous support from Ayaka Shibata, a staffer of IIBC, which runs
the TOEIC Bridge in Japan. Second, I would like to express my deepest gratitude to Paula Winke, Rie Koizumi, and Yo
In’nami who gave me valuable comments on an earlier version of this paper. Third, I am grateful to Mark Freiermuth and
Neal Snape for proofreading this manuscript. Lastly, I thank all of the participants and the high school principals who
kindly allowed me to recruit students at their schools and, not to mention, the editor and anonymous reviewers for theirconstructive feedback.
Author’s contributions
NK singly designed the study, collected the data, performed the statistical analysis, drafted the manuscript, andapproved the final manuscript.
Funding
This work was supported by JSPS KAKENHI Grant Number JP21K00764.
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Declarations
Competing interests
The author declares that he has no competing interests.
Received: 9 October 2023 Accepted: 5 January 2024

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