University of California Influence of Learning Styles on Learning Achievement Paper

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J Psycholinguist Res (2018) 47:1069–1084
https://doi.org/10.1007/s10936-018-9578-3
The Influence of Learning Style on English Learning
Achievement Among Undergraduates in Mainland China
Fang Huang1,2 · Cathy Ka Weng Hoi2 · Timothy Teo2
Published online: 26 March 2018
© Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract Learning style is one of the main factors that determines how students learn
English and has a significant influence on students’ learning strategy selection, which further
affects their learning outcomes (Ehrman and Oxford in Mod Lang J 74(3):311–327, 1990;
Oxford in Language learning styles and strategies: an overview, 2003. http://web.ntpu.edu.tw/
~language/workshop/read2.pdf). This study examines the learning style preferences of Chinese university students and whether those preferences influence their English achievements.
Four hundred undergraduates from one university in eastern mainland China participated in
this study. Data from 329 valid questionnaires were analysed. The results revealed that the
Chinese university students preferred the visual learning style the most, followed by the
auditory and kinaesthetic styles. However, no learning style preference was found to influence the students’ English proficiency. Cultural reasons are discussed to explain the findings,
which contradict those of previous studies of learning style theories and practices. This study
recommends that Chinese scholars consider issues of English teaching and learning in China
and to adopt appropriate teaching methods to effectively improve English teaching.
Keywords Learning style · English achievement · Chinese undergraduates · Culture
B Cathy Ka Weng Hoi
CathyHoi@umac.mo
Fang Huang
huang311fang@163.com
Timothy Teo
Timothyteo@umac.mo
1
School of Foreign Languages, Qingdao Agricultural University, Qingdao, China
2
Faculty of Education, University of Macau, Macau, China
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Introduction
Language learning is a complex adaptive system that comprises dynamic interactions between
language, agents and the environment (Beckner et al. 2009). Researchers have found that
many factors influence language learning. These include external factors such as the learning
environment and professional and educational guidance (Tabatabaei and Mashayekhi 2013)
and internal factors such as the individual learner’s motivation (Oxford and Shearin 1994),
attitude (Masgoret 2003) and personal engagement (Tabatabaei and Mashayekhi 2013). Individual differences (IDs) have been found to affect language teaching and learning outcomes
(Dörnyei 2005; Ellis 2012). Particularly, Sun and Teng (2017) noted the importance of teachers’ awareness of students’ learning style on their learning process. Researchers have posited
that when teachers are aware of learners’ IDs, they tend to adjust their teaching strategies in
effective ways to better meet learners’ individual needs (Sadeghi et al. 2012).
According to Ehrman et al. (2003), IDs generally relate to learning aptitude, culture and
demographic variables such as gender and age. They can be classified into three areas: learning styles, learning strategies and affective variables (e.g., motivation, self-efficacy, anxiety,
empathy and interaction between learners and instructors) (Ehrman et al. 2003). Learning
styles significantly influence learners’ strategy choices (Ehrman and Oxford 1990) and affective factors, in that an awareness of learning styles helps learners to convey their preferences
to instructors, thus facilitating the interactions between teachers and instructors and learners’
self-efficacy while reducing learning anxiety (Ehrman and Oxford 1990). Therefore, learning
styles remain the key elements that determine language learning outcomes (Oxford 2003).
Scott (2010) asserted that learning styles are a widely used method for discerning and classifying students’ IDs. They refer to how individuals acquire, retain and retrieve information
(Bailey et al. 2000). Learning styles also explain how an individual processes information
(Naserieh and Sarab 2013), and act as a mechanism through which learners deal with difficulties and challenges in their learning (Barmeyer 2004). However, studies of learning
styles have mainly focused on identifying students’ learning style preferences (e.g., Naserieh
and Sarab 2013), cross-cultural comparisons of learners with different cultural backgrounds
(Reid 1987), relationships between learning style characteristics and learning environments
(Dörnyei 2009) and adjusting teaching methods to suit learners’ learning styles (Ford and
Chen 2001). Empirical research investigating the influence of learning style preferences on
learning outcomes, which is the aim of this current study, is still insufficient (Zhang and
Evans 2013).
Currently, learning styles research in second language acquisition (SLA) is inconclusive
(Ellis 2008). Relatively few general conclusions have been drawn on learning styles (Ellis
1994). Researchers have found a weak relationship between learning styles and second language (L2) achievement (Ellis 2008). Nonetheless, there is ample evidence that learners differ
in how they prefer to be presented with information, process information, and acquire new
information (Hatami 2012). Advocates of learning styles assessment in language education
such as Sternberg et al. (2008) believe that learning styles are valuable teaching tools that can
inform language teaching and learning by matching individual learning styles and teaching
methods.
Most researchers have focused on defining and classifying models (Oxford 1993; Scott
2010) and the influence that learning styles have on teachers’ strategy choices (Ehrman
and Oxford 1989; Oxford and Ehrman 1988) compared with learners’ agency (Dörnyei
2009). Studying learners’ agency is important, as it is a key element in language learning
in addition to the target language itself and the environment (Beckner et al. 2009). The
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influence that learning style has on language learning achievements reveals the concerted
importance of examining language learners’ learning style preferences (Oxford 2003). As
one of the main individual factors behind researchers’ concerns in studies of English as
a foreign language (EFL), individual learners’ learning styles determine how they learn
and influence their selection of learning strategies, further affecting their learning outcomes
(Ehrman and Oxford 1990; Oxford and Ehrman 1988; Reid 1987). In addition, the precise
determination of a learner’s learning style effectively helps teachers to assist the individual
learner by designing and adjusting teaching strategies that meet the learner’s needs. Therefore,
without an awareness of individual learners’ learning styles, teachers are likely to adopt
inappropriate teaching methods that decrease students’ learning motivations and enthusiasm,
thereby limiting the students’ learning outcomes (Oxford 2003).
Individuals within a culture tend to have common patterns of learning (Oxford and Anderson 1995). Affected by Western individualist culture, learners and instructors in the West (e.g.,
America) respect IDs. Learners are very competitive and open to challenges from authority
(e.g., knowledge and teachers). They prefer kinaesthetic or experiential learning rather than
rote memory learning. They are also accustomed to explicit verbal communication in the
learning process (Cagiltay and Bichelmeyer 2000; Reid 1987). Chinese learners, on the other
hand, are distinctively different from Western learners in that they are passive, compliant
and obedient. They tend to accept knowledge without questioning and rely on rote memory
learning. They tend to lack critical thinking skills (e.g., Biggs 1991; Chen 2009; Reid 1987)
and are strong visual and auditory learners (Reid 1987; Zhang and Evans 2013).
Despite the IDs in learning style preferences between Chinese and Western language
learners noted by Reid (1987), Chinese language learners’ visual and auditory preferences
could be fostered by the traditional-authority-oriented language teaching and learning in
China. In particular, lecture and textbooks formed the central source of knowledge for Chinese
learners who passively recited what they saw and heard (Melton 1990; Zhang and Evans
2013). In addition, students relied on rote learning, memorisation, and repetition as their
prevalent learning methods (Huang and Brown 2009), which was driven by the traditional
language testing requirements that emphasised listening and reading skills. However, later
studies have presented contradictory findings on the learning styles of Chinese learners.
Wang (1992) found that Chinese university English majors showed a preference for the
kinaesthetic learning style; they perceived learning as taking place in the performance of
physical activities, rather than in listening to lectures (auditory) or watching demonstrations
(visual). In the context of English language learning, Gan et al. (2004) found that Chinese
learners displayed overall positive attitudes towards self-directed learning, contrary to the
stereotyped notion of Chinese students being passive learners.
Problem Statement and the Need for This Study
The inconsistency of Chinese learners’ learning style preferences and the lack of empirical
studies of the influence that learning styles have on learning outcomes show the need for this
study to re-examine Chinese learners’ learning style preferences and whether learning styles
relate to learning outcomes.
Students’ learning style preferences have been well researched in the West and covered a
variety of issues, such as how to define learning styles and their categories (Oxford 1993; Reid
1995); how learning styles influence learners’ strategy choices and learning achievements
(Ehrman and Oxford 1989; Oxford and Ehrman 1988); whether effective learners share cer-
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tain style and strategy preferences (Wong and Nunan 2011); and the demographic differences
in learning style preference (Wehrwein et al. 2007). However, most of the studies have been
Western-oriented and considered Chinese learners as a subsample in cross-cultural investigations of EFL learners (e.g., Reid 1987). Research into learning styles in diverse contexts
is necessary to deepen people’s understanding of the learning style literature (Sahragard
et al. 2016). Even fewer recent studies have considered the learning style preferences of
Chinese populations (Zhang and Evans 2013), a situation dramatically out of line with the
fact that China has the largest group of English learners (Taylor 2002). In addition, few
researchers have empirically examined the role that learning styles plays in foreign language
achievement (Bailey et al. 2000), and this lack of research is also reflected in the Chinese
EFL context (Cheng and Guan 2015). Zhou (2011) indicated that it is particularly critical
for English teachers to understand English learners’ learning styles, as this knowledge can
help teachers to plan their lessons, match or adapt their teaching methods and provide the
most appropriate and meaningful activities or tasks to suit a learner group at different stages.
Given that the view of English as a global language is pervasive in China (Crystal 1997;
Pan and Block 2011), English achievement matters greatly to university students seeking
degree, grants, and future career opportunities (Jin and Yang 2006). Considering the importance of learning style in EFL research (Li 2005; Wu and Wang 2009), the paradox between
the concerted influence that learning styles have on English achievements (Oxford 2003),
and the insufficient empirical studies published internationally on whether Chinese English
learners’ learning styles influence their English performance (Cheng and Guan 2015), there
is a new need to re-visit Chinese learners’ learning style preferences and examine whether
their learning style preferences influence their English achievements. In doing so, teachers
may gain a better knowledge of students’ preferred learning styles and adjust their teaching
strategies accordingly to enhance teaching and learning outcomes.
Literature Review
Learning Styles
Since the mid-1970s, there has been a substantial growth in learning style research in terms of
its definitions and dimensions (Oxford 1993; Oxford and Anderson 1995; Wintergerst et al.
2003; Reid 1984, 1995; Wintergerst et al. 2001). Although this area of study is nearly half
a century old, little agreement has been reached on the precise definition of learning styles
(Anderson and Adams 1992). Researchers have also disagreed on the overlap between the
concepts of learning styles, cognitive styles and learning ability (Leite et al. 2010). Various
conceptualisations of learning styles have been published, which has helped to sort out the
field (Leite et al. 2010; Sternberg and Zhang 2001). For example, as an early researcher
in the field, Keefe (1979) described learning styles as relatively stable cognitive, affective
and physiological traits that indicate how learners perceive, interact with and respond to
the learning environment. In the area of foreign language teaching, Reid (1987) suggested
that ‘learning style’ was a more general term and an internally based trait, unconsciously
perceived or used by language learners, that reflected an individual’s natural and habitual way
of absorbing, processing and retaining new information and skills. Most modern learning style
theories have focused on either the cognitive learning style, such as the holistic/analytical
approach to learning, or the perceptual learning style, such as the visual/auditory/kinaesthetic
(VAK) approach to learning (Riding 2001).
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The perceptual VAK learning style has been the most popular and widely researched topic
in the foreign language teaching research (Reid 1984, 1995). Its popularity comes from its face
validity, simplicity and ease of use (Leite et al. 2010). Considering that a learning style survey
must be content-specific (Ehrman 1996; Westman 1993) and that VAK was included in the
most well-known and widely studied learning style survey ‘Learning Style Survey: Assessing
Your Own Learning Styles’ (Cohen et al. 1995) in foreign language research, this study used
the VAK dimension in the instrument developed by Cohen et al. (1995) to investigate Chinese
EFL learners’ learning style preferences. The VAK dimension was measured based on how
language learners used their physical senses to approach and process information (Cohen
et al. 1995).
Dunn and Dunn (1979) suggested that the visual style was the dominant style for Western
students in foreign language teaching and learning, with 40% of students assigned to this style,
followed by the kinaesthetic (30–40%) and auditory (20–30%) styles. This was consistent
with Dale’s (1969) research finding that most EFL learners preferred the visual style. In Asia,
EFL students were reported as often highly visual, with Korean students scoring the highest
under the visual style (Kim and Kim 2014; Reid 1987). Chinese students most preferred
the visual style of English learning (Reid 1987). However, Wang (1992) suggested that
Chinese university English majors most preferred the kinaesthetic learning style. Considering
the inconsistencies in the literature, this study aims to re-examine Chinese EFL learners’
perceptual learning style preferences. Its first hypothesis is stated as follows.
H1 Chinese EFL learners score the highest under the visual style of learning.
Learning Styles and Foreign Language Achievement
In the second/foreign language teaching setting, studies have investigated the relationship between language learners’ dominant learning style preferences and language learning
achievements (Oxford 1993). Language learners who recognise their preferred learning styles
can adopt appropriate learning strategies in the given learning tasks and context and usually
convey their preferred learning styles to language teachers, who can adjust their teaching
strategies in time. In such a way, learners achieve higher levels of foreign language achievements (Jiang 2002; Oxford 1993). Studies have also revealed inconsistencies in the influence
that learning styles have on learning achievements; for example, they have found that learning styles are weakly or indirectly associated with achievements in foreign language learning
(e.g., Bailey et al. 2000; Oxford et al. 1993; Tabatabaei and Mashayekhi 2013). Despite
this, holding the belief that learning styles influence learning outcomes, Oxford and Ehrman
(1993) stated that visual learners achieve more by using written instructional materials. In
China, effective EFL learners prefer visual and auditory styles and strategies, while less
effective learners prefer kinaesthetic strategies (Wong and Nunan 2011). Xu and Yu (2012)
indicated that the auditory style is positively related to Chinese students’ English learning
performance. Based on these discussions, there is a need to re-examine whether EFL learners’ learning style preferences predict their English achievements. In this study, students’
College English Test Band 4 (CET-4) scores are used to investigate whether their learning
style preferences influence their English achievements. Other hypotheses are formulated as
follows.
H2 Chinese EFL students’ visual learning style predicts their CET-4 achievements.
H3 Chinese EFL students’ auditory learning style predicts their CET-4 achievements.
H4 Chinese EFL students’ kinaesthetic learning style predicts their CET-4 achievements.
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Fig. 1 The research model
Based on the above discussions, the research model illustrating H2 , H3 , and H4 were
presented in Fig. 1.
English Teaching in Chinese Universities
In Chinese universities, English is a compulsory course and students are required to achieve
a certain level of English proficiency to qualify as university graduates (Jin and Yang 2006).
CET, a national standardised proficiency test administered by the National College English
Testing Committee on behalf of the Chinese Ministry of Education, is a mandatory test for
undergraduates in all Chinese universities for graduation. It is held twice annually summer
and winter. CET tests students on listening, reading, translation, and writing. At this point in
time, there is no published records that attempt to compare the CET with TOEFL or IELTS.
Passing the CET-4 (paper-based test) used to be an essential criterion for university administrators to assess students’ eligibility to graduate with Bachelor’s degrees (Zheng and Cheng
2008). After the 2005 reform of the education system, each Chinese university was given
the autonomy to decide on the role of the CET-4 scores (Jin 2006) for graduation purposes.
Subsequently, the CET-4 went from an assessment of students’ English language competence to become an indicator for university ranking in the national league table in China (Jin
and Yang 2006). Another national standardised English proficiency test in China is the Test
for English Majors, known as TEM. Internationally well-known standardised tests such as
IELTS and TOFEL are not mandatory for Chinese university students and are usually only
taken by those who intended to apply for study in overseas universities.
As for English teaching in Chinese universities, Wang and Wang (2011) surveyed 530
Chinese university students and found that non-English major undergraduate students need
to complete a range of 13–16 credits in listening, speaking, reading, translation, and writing.
Students received English language learning mostly through English classes because English
is not used as the Medium for Instruction in most universities except for several world-class
universities such as Peking University and Tsinghua University (Ma and Zhang 2007).
However, English language teaching has been fraught with problems for many years.
Among these, there is the large teacher–student ratio of about 1:200 (Hu and McGrath
2011), typically, an English teacher teaches between 60 and 80 students in one class timeslot
that lasts 45 min. Teachers are constantly under pressure to focus on preparing students
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to perform well in exams to the detriment of the learning process (Pan and Block 2011).
Inevitably, EFL teaching in China is textbook- and teacher-centred (Hu and McGrath 2011),
with little consideration for learners’ traits. In recognition of the key role learning styles play in
learning EFL, the College English Curriculum Requirement (2007) was created to advocate an
emphasis on learners’ IDs, with special attention paid to learning style preferences, something
that has long been valued in the Western education system (Hu and McGrath 2011; Pan and
Block 2011).
Driven by policy promotion and student-centred pedagogy, research on learning styles has
been conducted in China, but it has arrived at contradictory findings on the learning styles
of Chinese learners, and studies of the learning style preferences of Chinese populations
remain few and far between (Zhang and Evans 2013). It is far from enough to make Chinese
learners a subsample in a cross-cultural investigation (Reid 1987). Therefore, it is necessary
to provide a clearer and more complete image of Chinese learners’ learning style preferences.
This study aims to provide a clearer picture of Chinese university English learners’ learning
style preferences and whether those preferences lead to success in their English achievements.
This study contributes to the learning style theories by providing empirical evidence of Chinese university EFL learners’ learning styles, in addition to practical suggestions for English
teachers and policymakers on curriculum design and instruction. It is also important for
Chinese language learners to recognise their own preferences and strengths, adopt effective
learning strategies and thus expand their learning potential (Wong and Nunan 2011). This
study answers the following two research questions.
RQ1. What are Chinese English learners’ learning style preferences?
RQ2. Do Chinese English learners’ learning style preferences influence their English
achievements?
Methods
Participants
The participants in this study included 329 Chinese students from a university in East China.
All of the students were enrolled in the college English course taught at the university. The
mean student age was 21.06 (SD = 1.87), and 173 (52.6%) of the students were female.
Among the participants, 67 and 33% majored in Computer Science and Communication
Studies, respectively.
Procedure
The participants were recruited with the help of English teachers at the university. Informed
consent forms were sent to all participants who were informed of their right to withdraw
from the study at any time with no questions asked. Participants were also informed of the
purpose of this study and the anonymity of their data. The questionnaires (in Chinese) were
completed during regular class sessions in no more than 20 min.
Instrument
The instrument in this study comprised two parts: demographic information and the learning
style survey (Cohen et al. 1995), which was specially designed to determine second or foreign
language learners’ learning style preferences. In particular, the first part of the survey, ‘How I
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Table 1 CET-4 scores of the
participants
J Psycholinguist Res (2018) 47:1069–1084
Major
CET-4
Mean
SD
t value
F
Sig.
Computer
science
(N = 226)
443.61
54.927
3.767
4.049
.000
Communication
(N = 103)
413.61
71.817
Total (N = 329)
use my physical senses’, was used to assess the visual (V), auditory (A) and kinaesthetic (K)
learning styles of the participants. In this part of the survey, each of the three kinds of learning
style was measured with 10 items, with a total of 30 items in the survey (Cohen et al. 1995)
to represent the VAK learning style preferences. The 30-item VAK learning style preferences
were measured on a 7-point Likert scale (1 = strongly disagree, 7 = strongly agree).
Two doctoral students who were bilingual in English and Chinese translated each item
from English into Chinese carefully to avoid any possible misunderstanding. Some minor
modifications were made in the wording that ensured the accuracy of the translation. Following this process, a standard back-translation procedure (Brislin 1986) was completed by
another two bilingual speakers who translated the Chinese set of items back into English. The
accuracy of the Chinese translation was indicated by a match of the vocabulary and meaning
of the two sets of English items.
Data Analysis
Exploratory factor analysis (EFA) and structural equation modelling (SEM) were used to
examine the reliability of the items and the hypothesised relationship between the VAK and
CET-4 scores. For SEM, a two-step approach was adopted (Anderson and Gerbing 1988)
to analyse the measurement and structural models in sequence. The first step (measurement
model) involved evaluating the fit between observed variables and their underlying constructs
based on the sample data. The second step (structural model) required analysis of the hypothesised relationship between exogenous variables, i.e., the VAK scores, and the endogenous
variable, i.e., the CET-4 scores. Table 1 shows the CET-4 scores of the participants.
Results
Descriptive Statistics and Preliminary Analyses
The means, standard deviations, skewness and kurtosis values of the 30 items were analysed.
The means of these items were between 3.94 and 5.04 (SD = 1.42 and 1.93). Skewness ranged
between − .78 and .14, while kurtosis ranged between − 1.06 and .24. These two indices fell
within the cut-offs of |3.0| and |8.0|, respectively, and met the recommended guidelines to
support the univariate normality of the sample data (Kline 2010).
EFA using maximum likelihood estimation with promax rotation was conducted to provide preliminary results before further analyses of the reliability and validity of the items in
the VAK sections. All of the statistical analyses were performed using SPSS 19.0 and AMOS
20.0. The Kaiser–Meyer–Olkin (KMO) value was .90, indicating an adequate level of com-
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mon variance within the scale. The results showed that five factors had eigenvalues greater
than 1, accounting for 35.23, 7.41, 3.88, 2.44 and 2.3% of the total variance, respectively.
However, 10 of the 30 items had factor loadings below .50, indicating an insufficient amount
of variance explained by these items (Hair et al. 2010). These items were therefore removed,
with 20 items remaining. Nevertheless, eight more items did not load on their corresponding
factors and thus were removed from further analyses. Accordingly, 12 items (i.e., visual: 6
items; auditory: 3 items; and kinaesthetic: 3 items) were retained for further examination of
the measurement model.
Analysing the Measurement Model
Confirmatory factor analysis (CFA) was conducted with maximum likelihood (ML) estimation to examine the fit of a congeneric model with uncorrelated errors. As the ML estimation
typically assumes the multivariate normality of the observed variables in the measurement
model, Mardia’s normalised multivariate kurtosis value was examined. Using the formula p
(p + 2), in which p equals the number of observed indicators, Mardia’s coefficient was 27.05
for the current sample, lower than the value of 360 [18 (18 + 2)] and thus supporting the
presence of multivariate normality in the current sample (Mardia 1970).
Several criteria were used to examine the reliability of the items and validity of the instrument. These criteria included the composite reliability (CR), average variance extracted
(AVE), standardised estimates and t values (Teo and Fan 2013). The values of CR and AVE
and the standardised estimates of the items and factors had to be greater than .50 to indicate a
sufficient amount of variance accounted by the items (Hair et al. 2010). As shown in Table 2,
all of the standardised estimates, t values and CR and AVE values for the items are above .50,
except for the AVE value for the visual items. However, the standardised estimates, t values
and CR values indicate that the visual scale items were reliable.
To examine the fit of the measurement and structural models, several indices were assessed.
These indices included the minimum fit function χ 2 to its degree of freedom χ 2 /df . Schumacker and Lomax (2010) recommended that the ratio be less than 3.0 to indicate acceptable
fit. Other indices included the comparative fit index (CFI), Tucker–Lewis index (TLI) and
root mean square error of approximation (RMSEA), in addition to the standardised root mean
square residual (SRMR). The TLI and CFI values were recommended to be greater than .90
to show adequate model fit and .95 to show good model fit. The RMSEA and SRMR values
were recommended to be lower than .06 and .08, respectively (Hu and Bentler 1999). A
test of the initial measurement model showed an unacceptable model fit (χ 2 = 180.92, χ 2 /df
= 3.55, TLI = .89, CFI = .91, RMSEA = .088, SRMR = .065).
Modification indices were examined and showed that by adding correlations between the
errors of items 8 and 9, the χ 2 value would improve by 20.55. An evaluation of items 8
(i.e., ‘I understand lectures better when professors write on the board’) and 9 (i.e., ‘Charts,
diagrams and maps help me understand what someone says’) revealed that the wordings
could be problematic, as ‘understand lectures better’ and ‘help me understand what someone
says’ could have similar meanings to the participants. After correlating the errors of items
8 and 9, CFA showed sufficient fit of the measurement model (χ 2 = 149.79, χ 2 /df = 2.99,
TLI = .91, CFI = .93, RMSEA = .078, SRMR = .061).
Analysing the Structural Model
The VAK scores were examined to assess the participants’ learning style preferences. To
evaluate the accuracy of the revised VAK scale (12 items) compared with the original VAK
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Table 2 Results of the measurement model
Variable
Item
SEa
t value
1. I remember something better if I write it
down
.51
8.61
Visual
2. I take detailed notes during lectures
.68
11.71
3. I use colour coding to help me as I learn or
work
.67
11.52
4. I need written directions for tasks
.64
10.95
5. I understand lectures better when
professors write on the board
.75
12.95
6. Charts, diagrams and maps help me
understand what someone says
.77
–
1. I need oral directions for a task
.71
11.24
2. I remember peoples’ names but not their
faces
.77
11.94
3. I easily remember jokes that I hear
.75
–
1. If I had a choice between sitting and
standing, I would rather stand
.76
10.77
2. I think better when I move around (e.g.,
pace or tap my feet)
.85
11.08
3. I play with or bite on my pens during
lectures
.64
–
Auditory
Kinaesthetic
CRb
AVEc
.83
.45
.79
.55
.80
.57
a SE standardised estimates
b CR composite reliability (λ)2 /(λ)2 + ((1–λ2 ))
c AVE average variance extracted (λ2 )/(λ2 ) +((1–λ2 ))
scale (30 items), the scores from the two scales were correlated. As shown in Table 3,
the scores of the original and revised versions had strong and significant correlations with
their corresponding scales, indicating that the revised VAK scale was able to reproduce and
represent the scores from the original VAK scale accurately. Scores from the revised VAK
scale revealed that participants attributed the highest score to the visual style, followed by
the auditory and kinaesthetic styles (see Table 4). Therefore, H1 was supported.
Analysing the Relationship Between Learning Style and English Test Score
The results showed an acceptable fit of the structural model (χ 2 = 158.85, χ 2 /df = 2.69,
TLI = .91, CFI = .93, RMSEA = .072, SRMR = .058). However, none of the learning style
variables predicted the CET-4 scores (all ps > .05). The visual learning style had a weak
negative relationship with the CET-4 scores (β visual = − .06, pvisual = .41). By contrast, both
the auditory and kinaesthetic learning styles had week positive relationships with the CET-4
scores (β auditory = .06, pauditory = .53; β kinaesthetic = .03, pkinaesthetic = .76). These results did
not support H2 , H3 or H4 .
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Table 3 Inter-correlation results for the original and revised VAK scales
Visual
(original)
Auditory
(original)
Kinaesthetic
(original)
Visual
(revised)
Auditory
(revised)
Kinaesthetic
(revised)
Visual
(original)
Auditory
(original)
.72**
Kinaesthetic
(original)
.66**
.78**
Visual
(revised)
.94**
.60**
.52**
Auditory
(revised)
.56**
.86**
.65**
.42**
Kinaesthetic
(revised)
.50**
.57**
.86**
.36**
.52**
**p < .01 Table 4 Chinese EFL learners’ learning style preferences from the revised VAK scale Mean SD Visual 4.71 1.16 Auditory 4.32 1.31 Kinaesthetic 4.31 1.42 Discussion Foreign language researchers have devoted themselves to studying learning styles and their effect on foreign language teaching and learning. It is arguable whether a learning style preference contributes to effective EFL proficiency based on previous discussions. This study examined Chinese EFL learners’ learning style preferences and whether those preferences led to their success in English achievements. The results indicated that Chinese university students prefer the visual learning style, a finding consistent with those of Reid (1987) but contrary to previous findings suggesting Chinese English learners prefer the kinaesthetic (Wang 1992; Xu and Yu 2012) and auditory (Xu and Yu 2012) learning styles. The students’ preference for the visual learning style can be attributed in part to the emphasis on rote memory learning through writing in traditional Chinese education. The results also suggested that learning style preferences do not predict Chinese university students’ English achievements. This finding is not in line with the previous finding that perceptual learning styles influence learning outcomes (Li and Qin 2006; Reid 1987; Wang 1992; Yu 1997). Although learning styles are individual internalised features and have widely been described as an important element in language learning, they have not been treated as significant in the Chinese English learning setting. Historically, Chinese education has been highly characterised as teacher-centred and examination-oriented, and rote memory has been considered the best strategy to succeed in tests (Hu and McGrath 2011). Students make great effort to memorise English words, phrases and even patterns for writing compositions so that they can achieve good scores in tests. In this case, their individual learning styles are usually neglected in English instruction (Hu and McGrath 2011; Pan 123 1080 J Psycholinguist Res (2018) 47:1069–1084 and Block 2011). Although student-centred pedagogy has been widely promoted for years and its potential for improving teaching and learning has been well noted, innovations in pedagogy and paradigm remain ineffective in China (Li 2014). As Zhu (2015) reported, in Chinese higher educational institutes, the potential for innovation has been neither fully recognised nor systematically implemented. In the Chinese EFL teaching context, the traditional teacher-dominating pedagogy is still ubiquitously observed (Li 2014). Teachers do not pay much attention to individual learners’ learning style preferences, and even if they intended to, the large gap in the teacher–student ratio would not empower them to focus on individual students’ learning style preferences and needs. Although the College English Curriculum Requirement (2007) promotes communicative teaching for the benefit of improving students’ communicative skills, teachers’ verbal teaching apparently cannot benefit those who prefer the visual or kinaesthetic learning styles. Furthermore, listening and reading comprehension are two important parts of the CET-4 tests and share the same proportion (35%) of the total score. To achieve satisfactory scores, students must practise both English listening and reading, which require them to have multiple information-processing skills. This explains the research finding that no specific learning style directly predicts English achievement. In addition to test-oriented English learning in China, learners’ individual portraits are not valued as highly in China as they are in Western countries (Zhu 2013). Hierarchy is an important value in China (Hofstede 1980). In the teaching and learning process, teachers are regarded as occupying a higher position in the hierarchy, and students show their respect to those teachers, even when they do not favour their teaching styles. Teachers are inclined to prefer leadership in the Chinese educational context (Zhu 2013); in other words, teachers must take a leading role and give clear guidance to students, while students need to be disciplined (Zhu et al. 2010). Thus, students’ individual traits are not emphasised in the Chinese educational context. It is reasonable to believe that students’ learning style preferences do not necessarily relate to their learning achievements in the long run. Limitations and Further Study The results of this study must be interpreted under consideration of the following limitations. First, all of the participants came from one Chinese university, and considering the geographic diversity of the Chinese population, the research findings in this study cannot represent the entire situation of Chinese English learners. Second, data were collected using selfreported answers, which may raise validity issues in terms of data quality and response validity (Fan et al. 2006). The responses from the self-reported surveys might not have accurately reflected the participants’ true feelings. Thirdly, cultural values that may help explain people’s thinking and behaviour were not examined in this study. Researchers may consider investigating the extent to which Chinese learners adopt cultural cognitive processes such as collectivism mental characteristics. Further studies are needed to involve students from different universities to gain a wider understanding of Chinese students’ learning style preferences. In addition, empirical studies should be conducted to test how Chinese cultural habit influences English learners’ learning styles and behaviour. 123 J Psycholinguist Res (2018) 47:1069–1084 1081 Conclusion Given that individual learners perform differently in language learning, few general conclusions were drawn from the learning styles research (Ellis 1994). Nonetheless, Chinese scholars have shown increasing interest in investigating students’ learning styles in the foreign language learning setting. In particular, with the increasing trend of students studying abroad, quality teaching, which is characterised by constructivist teaching and an emphasis on students’ IDs, is promoted to better prepare students for their future study experiences in different countries (Biggs and Tang 2007). Chinese university English teachers have been striving to empower students with sufficient intercultural knowledge (Zhang 2007), such as by informing them of the teaching styles and students’ learning styles and strategies adopted in the West. Unfortunately, a severe lack of empirical studies and insufficient reports on the subject have been published in international journals (Wu and Wang 2009). This study provides insight into Chinese English learners’ preferred learning styles and whether their learning style preferences predict their English achievements. The findings suggest that although Chinese EFL learners prefer visual learning, learning styles in China are not as important as those in the Western context, in that they do not predict Chinese students’ English achievements. This study contextualises learning style research in the Chinese English learning context, enriches understanding of learning style theories and provides valuable empirical evidence for both English teachers and learners in terms of strategy selection and reflective teaching practice. In addition, it describes the cultural influence on Chinese English teaching and learning. It is important for both students and teachers to be aware of the convergence and divergence between teachers and students. English teachers in mainland China should be aware of students’ needs to adjust their teaching. Furthermore, considering the stereotypes that have arisen in the past few decades regarding Chinese learners’ learning style preferences, Chinese learners’ overall learning style preferences must be uncovered to benefit students, teachers and academics in the field. 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A cross-cultural study of teacher perspectives on teacher roles and adoption of online collaborative learning in higher education. European Journal of Teacher Education, 33(2), 147–165. 123 Session 9_ Lit review, Research Evaluation, and Research Proposal Research Literacy (A&HL 5575) Common Research Stages Topic Selection Literature Review & Research Evaluation Research Problem Research Methodology Research Questions Research Purpose Context and Method Ethical Considerations Writing a Research Proposal Interpretations & Conclusions Data Analysis Data Collection Research Communication Vafaee, A&HL5575 (Class 9) 2 Literature Review Benefits ! Helps you see the frontiers of the particular research area. ! Helps identifying research gaps: " Make the case that the existing research in the area is incomplete or requires extension. ! Helps put the original research questions in perspective. ! Helps in limiting research questions. ! Leads to a better definition of the concepts and constructs. ! Leads to a better operationalization of the constructs. ! Provides insights into the reasons for contradictory findings. ! Shows what methodologies can be used. ! Helps avoiding unintentional replication of previous studies. ! Helps with interpretation of the results. Vafaee, A&HL5575 (Class 9) 3 Literature Review Goal ! Overall Purpose: to tell a coherent story. It’s a narrative with headings and subheadings. It’s an argument built on synthesizing and critiquing a group of studies related to a topic. ! Tie together the results of the studies so that their relevance is clear. No patch writing!! ! Don’t make the review a series of quotations. ! Provide opening and closure for each section. ! It’s part science and part art: ! Science: Critical evaluation of theory & empirically-based literature. ! Art: a storyline that is told from sources you choose & from your reading & categorization of these original sources. Vafaee, A&HL5575 (Class 9) 4 Literature Review ! To Achieve the Goal: we need to summarize, synthesize, critique, and discuss both theoretical and empirical papers on the topic you are covering. ! You need to add the critical lens—from the personal perspective, the critical perspective & and application perspective. ! When conflicting findings are reported across studies, find possible explanations. ! Two Important Qualities: Breadth and Depth ! Breadth: the seminal studies and many of the contributing studies are covered. ! Depth: It includes adequate detail and a critical view (e.g., by questioning reliability/validity, etc.) Vafaee, A&HL5575 (Class 9) 5 Literature Review Writing Strategies ! Limit your search to what is relevant to your study purpose---not what is interesting!! ! Read widely consulting primary & secondary sources. BE CAREFUL about depending on secondary sources. ! Look for seminal and state-of-art (overview) articles in the area. These articles can provide you with a road map and other references to read—this is how the tree of information builds. ! Use Google Scholar or the following link: TC Library ! Dissertations are a good resource for this purpose, too. ! This link helps you find them: ProQuest Vafaee, A&HL5575 (Class 9) 6 Literature Review Writing Strategies ! Prepare an annotated bibliography. You can use the two following programs: Endnote and Nvivo. ! Get them for free from: TC Free Software Download ! Read deeply by summarizing the details of the article. ! You can use the following resource to evaluate the martials used in previous studies or even adopt them for your own research: IRIS ! Learn how to cite in-text references and create a reference list (see the APA manual). ! This is also a good source: OWL APA Vafaee, A&HL5575 (Class 9) 7 Literature Review Structures ! A Historical Perspective Approach: Theoretical developments, followed by research from the past to the present, leading to a statement of a research gap. ! A Contrastive Approach: Comparing and contrasting competing perspectives/theories about a topic, leading to a rationale for the study. ! An Aspect-by-aspect Approach: Description and discussion of the various research aspects under investigation, which can then be integrated in the proposed study. _______________________________________________________ ! To Achieve the Goal of Literature Review: You need to add the critical lens—from the personal perspective, the critical perspective & and application perspective Vafaee, A&HL5575 (Class 9) 8 Criteria for Empirical Research Study Evaluation ● Research Problem and Literature Review: It effectively identifies, analyses and synthesizes an issue or research topic through reference to an up-to-date selection of research materials. ! It establishes its significance in the field by using a suitable theoretical or conceptual framework and by considering relevant and significant previous research. ! The review of associated theories and previous research is accurate and critical. ! Key terminology is used precisely and consistently. ! The gap or need for the study is clearly identified from the existing research. ! The research questions and/or hypotheses to be investigated are important and relevant to the research issue or problem and connected closely to the review of literature. ! Vafaee, A&HL5575 (Class 9) 9 Criteria for Empirical Research Study Evaluation ● Research Methodology: ! It appropriately and adequately describes the methodology adopted, including the procedures used for the data gathering, ethical considerations and data analysis. ! It elaborates the rationale for the choice of the methodology for the research and, where appropriate, provides a connection between this methodology and research methodologies adopted in previous research on the topic. ! It demonstrates the researchers’ strong command of the research methodology, including an understanding, recognition or awareness of both the strengths and weaknesses of the methodology that influence the validity or trustworthiness of the interpretations. Vafaee, A&HL5575 (Class 9) 10 Criteria for Empirical Research Study Evaluation ● Research Procedures: ! It describes sufficiently the overall research procedures, including: ! a detailed description and explanations of the research setting ! the participants ! the ethical considerations ! the research instruments ! the data elicitation techniques ! the specific stages of the data analysis ! what care has been taken to ensure the data analysis is systematic and credible. Vafaee, A&HL5575 (Class 9) 11 Criteria for Empirical Research Study Evaluation ● Findings and Interpretations: ! It clearly and sufficiently presents and explains basic information on the findings in relation to the research aims, questions or hypothesis that are presented at the beginning of the study. ! The presentation of the findings meets the expected conventions of the particular research design. ! It takes an evidence-based approach in making inferences as well as offers a critical interpretation and discussion of the findings. ! It doesn’t overgeneralize its findings. ! It links the present findings to the relevant literature presented earlier. Vafaee, A&HL5575 (Class 9) 12 Criteria for Empirical Research Study Evaluation ● Conclusions and Implications: ! The originality and substantial level of the contribution of the study may be considered in the conclusion section. ! It clearly and sufficiently summarizes the key study findings. ! It recommends implications of the findings for the existing and future research. ! It notes potential study limitations. ! It provides recommendations for the future research. _________________________________________________ ● Overall Writing Quality: ● It’s well-written, well-organized, and coherent. ● It meets the standards (e.g., APA Referencing Style) in referencing, and presenting tables and figures. ● It is free from grammatical and typological errors. ___________________________________________________ Use the two following guideline article: Chapelle & Duff (2003) Vafaee, A&HL5575 (Class 9) 13 A Research Proposal ! Your proposal should have the following sections: ! Introduction " Purpose " Significance of the proposed study (what gap it fills) ! Background and Lit. review " Implications of the Lit. review (what gaps were identified) ! The Proposed Study " A brief summary of the goal and design " Research questions and/or hypotheses " Research methods ! Participants ! Materials ! Procedures " Planned Data Analysis " Anticipated results and conclusions Vafaee, A&HL5575 (Class 9) 14