Learning Styles and Performance in Second Language Tasks

Edited by JOHN FLOWERDEW University of Leeds ALI SHEHADEH United Arab Emirates University Learning Styles and Performance in Second Language Tasks ELENI ANDREOU, GEORGIA ANDREOU, and FIL

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Edited by JOHN FLOWERDEW

University of Leeds

ALI SHEHADEH

United Arab Emirates University

Learning Styles and Performance in Second

Language Tasks

ELENI ANDREOU, GEORGIA ANDREOU, and

FILIPPOS VLACHOS

University of Thessaly

Volos, Greece

䡲 Learning styles, which refer to a student’s preferred mode for perceiv-ing, organizperceiv-ing, and retaining information, have aroused a great deal of attention since Kolb’s influential work on the topic was published in

1976 Kolb’s (1981, 1984) experiential learning theory postulates the existence of four learning modes that combine to form two learning dimensions: concrete/abstract and active/reflective Kolb theorized that almost every individual utilizes each learning mode to some extent but has a preferred learning style resulting from the tendency to learn either

through concrete experience (CE) or through abstract conceptualization (AC;

i.e., the construction of theoretical frameworks) combined with the

ten-dency to learn either through active experimentation (AE) or through

reflective observation (RO; i.e., reflection) These learning style preferences

are described by Kolb (1976, 1984) as divergent (CE/RO), assimilative (RO/AC), convergent (AC/AE), and accommodative (AE/CE) He

pre-dicted that the styles would be relatively stable over time, like personality characteristics, although they are influenced by long- or short-term situ-ational factors and level of maturity

Results obtained using Kolb’s Learning Style Inventory (Kolb, 1985)

in discipline-based research demonstrate some measure of agreement among researchers regarding the learning style preferences typically found in specified disciplines and more agreement if disciplines are

subsumed under more general descriptions such as arts or sciences It was found, for example, that arts students tend to favour divergent or assimilative learning styles (Kolb, 1985; Kruzich, Friesen, & Van Soest, 1986; Willcoxson & Prosser, 1996), social science students tend to favour accommodative learning styles (Kruzich et al.; Wilson, 1986), and exact science students prefer convergent learning styles (Katz, 1988; Reading-Brown & Hayden, 1989; Willcoxson & Prosser) Probably a part of the students’ learning process stems from a personal habitual way of learn-ing, and another part is influenced by the actual learning context stu-dents are confronted with (Slaats, Lodewijks, & van der Sanden, 1999) For example, a computer scientist with a general preference for a con-vergent style might adopt a different style when learning English as a second language (L2) However, the preferred mode for learning an L2 might be different from the general tendency

Regarding L2 learning, there is a great deal of theoretical and em-pirical support (Jones, 1997; Reid, 1987; Rossi-Le, 1995) that students tend to favour kinesthetic and tactile styles (e.g., prefer active participa-tion, experiences, and hands-on work) However, very few studies have looked at the links between styles and discipline (e.g., science vs arts) Melton (1990) found that arts students favoured kinesthetic and indi-vidual styles, and science students did not It was also found that science students have a stronger preference for group styles and that arts stu-dents have a stronger preference for auditory and individual styles (Pea-cock, 2001) It should be noted that none of the above studies checked learning style preferences in connection with different L2 verbal fluency tasks (e.g., phonology, syntax, semantics) In addition, a more recent study (Drew & Ottewill, 2002) suggested that careful consideration be given to learning style and related factors that may contribute to suc-cessful language learning Although the study was inconclusive with re-spect to learning style, it suggested that more can be done to maximize student achievement, such as providing students with opportunities for exploring the learning process

Given the paucity of research that has examined associations between learning styles and chosen academic discipline in connection with per-formance on different L2 verbal fluency tasks, we undertook the current study with the aim of investigating the relationship between Greek stu-dents’ learning styles and performance on English phonological, syntac-tic, and semantic tasks Differences by gender and academic discipline (science vs arts) were also examined in order to elucidate the role that these individual differences play in L2 learning More specifically we investigated (a) the preference for a specific learning style among males and females and among arts and science students, (b) the association of learning styles with high or low scores in L2 verbal fluency tasks, and (c)

each learning style’s relative contribution to performance on L2 verbal fluency tasks

METHOD

Sample

The sample comprised 452 undergraduate students (146 males and

306 females) from a medium-sized university in central Greece Subjects were between 18 and 26 years of age (mean age 19.50; standard deviation 1.83) As for academic disciplines, 232 students were enrolled in the Faculty of Arts, and 220 were enrolled in the Faculty of Science The students’ native language was Greek, and none of their parents spoke another language at home At the time of the research, they were in their first or second year of their university studies They had studied English

as a second language for about 9 years (mean: 9 years and 5 months) and had obtained the First Certificate in English (Cambridge or Michigan or both of them) about 4 years (mean: 4 years and 2 months) before the beginning of the research

Measures and Procedure

Learning styles were assessed by Kolb’s (1985) self-reported Learning Style Inventory (LSI) Twelve short statements concerning learning situ-ations were presented and respondents were required to put four sen-tence endings in rank order

Table 1 shows the coefficient alpha reliabilities and an intercorrela-tion matrix of the LSI scales The reliabilities range from 0.82–0.89 Table 1 also shows the correlations between the scales Consistent with the hypothesis that there are two bipolar dimensions, the AC scale is negatively correlated with the CE scale at a statistically significant level, as

TABLE 1 Coefficient Alpha Reliabilities and Scale Intercorrelations

CE (0.83) −0.31** −0.37** −0.54** −0.16* −0.04

RO (0.89) −0.14* −0.77** 0.00 −0.71**

AC (0.86) −0.69** 0.39** −0.08

Note CE = concrete experience, RO = reflective observation, AC = abstract conceptualization,

AE = active experimentation; coefficient alpha shown in diagonals; *p < 0.05, **p < 0.01

are the AE scale and the RO scale The matrix also shows that the two bipolar dimensions are essentially independent of each other, as ex-pected from the theory These two dimensions formed four quadrants reflecting four learning styles (accomodative: AE + CE; divergent: CE + RO; convergent: AC + AE; and Assimilative: RO + AC)

Students’ verbal fluency in the foreign language was measured by their answers in semantic, syntactic, and phonological tasks For seman-tic verbal fluency, we used the Set Test (Isaacs & Kennie, 1973) In this test, the subjects are asked to write as many items as they can in 1 minute, from four successive categories: colours, animals, fruits, and towns The score is the total number of items written, 40 being the highest possible score For syntactic verbal fluency, the subjects were asked to produce as many sentences as possible in the active and passive voice from mixed words, by making the necessary changes or additions for the passive voice but keeping the same tense of the verb in both voices The sentences

given were (a) the, boy, girl, kisses, the; (b) car, the, the, washes, boy; (c) an,

the, child, apple, eats; (d) boy, the, carries, a, package The highest possible

score was 10 This test is a test of written grammar which is considered to measure second language syntax (Sparks & Ganschow, 1993) and has previously been used in other studies (Andreou, Vlachos, & Andreou, 2005; Grober & Bang, 1995) For phonological verbal fluency, a spelling test was used because spelling is considered a measure of phonology (Sparks, Ganschow, & Patton, 1995) The subjects were asked to write down 10 high frequency regular and exception English words and 10 low frequency regular and exception words, previously used in other studies (Andreou, Andreou, & Vlachos, 2005; Graham, Patterson, & Hodges, 2000) The reliabilities of the verbal fluency tests ranged from 0.69–0.81 Most of the questionnaires were administered at the beginning or end

of a lecture, with the permission of the lecturers The purpose of the study was briefly explained to the students It was pointed out that the questionnaires were anonymous and only grouped data would be re-ported Generally, they took about 45 minutes to complete the task

RESULTS

Descriptive Statistics

Analyses of variance were used to investigate gender and discipline differences Males had a systematically more convergent learning style

than females [F(1450)=33.953, p < 001] Females had a more divergent style than males [F(1450)=13.576, p < 001] and scored significantly higher on semantics [F(1450)=20.086, p < 001] No significant gender

difference was found for either phonology or syntax

Table 2 presents the means and standard deviations for all variables grouped by discipline Arts students displayed a tendency to emphasize

a more divergent and assimilative learning preference than science stu-dents Science students displayed a preference for convergent learning style and had systematically lower scores on phonology and semantics For this reason, correlations between learning styles and performance on verbal fluency tasks were conducted separately for arts and science stu-dents

Correlations

Pearson correlation coefficients were calculated separately for the samples from each faculty to assess whether learning styles (LS) had different associations with performance on L2 verbal fluency tasks These correlations are shown in Table 3 For both arts and science students, higher scores on the phonology test were positively associated with higher scores on the divergent LS scale, and higher scores on syntax were positively associated with higher scores on the accommodative LS scale For science students, higher scores on both syntax and semantics

TABLE 2 Means and Standard Deviations for Variables in the Study, by Discipline

Variable Total (N = 452) Arts (n = 232) Science (n = 220) F (1450) Accomodative 65.42 (9.44) 64.61 (9.76) 66.42 (9.76) NS Divergent 61.89 (8.94) 63.28 (6.88) 59.74 (8.23) 29.95** Convergent 55.86 (8.82) 54.82 (8.05) 58.71 (7.88) 53.44** Assimilative 52.81 (8.81) 53.94 (8.98) 52.92 (8.20) 6.11* Phonology 10.73 (4.22) 11.57 (4.43) 10.31 (4.43) 6.22* Syntax 7.17 (2.33) 7.37 (2.07) 7.76 (2.28) NS Semantics 31.02 (7.36) 32.58 (7.55) 30.03 (7.30) 8.10**

Note *p < 0.05, **p < 0.01

TABLE 3 Correlations Between Learning Styles and Scores on L2 Verbal Fluency Tasks

Phonology Syntax Semantics Arts

n = 232

Science

n = 220

Arts

n = 232

Science

n = 220

Arts

n = 232

Science

n = 220

Accomodative −0.021 0.033 0.138* 0.286** 0.70 0.056 Divergent 0.246** 0.199** 0.118 0.117 0.166* 0.010 Convergent 0.058 0.173* −0.067 0.196** −0.008 0.250** Assimilative 0.088 0.015 0.248** 0.037 0.077 0.053

Note *p < 0.05, **p < 0.01

were positively associated with higher scores on convergent LS scales For arts students, higher scores on syntax were associated with higher scores

on assimilative LS scale All these correlations were low but statistically

significant (p < 01).

Multiple Regressions

Because correlation does not imply causation and is more a function

of the sample size than of any close relationship, three multiple regres-sions were performed to determine the relative contribution of each of the learning styles to performance on L2 verbal fluency tasks

When phonology served as the dependent variable, R was significantly different from zero [R2= 0.23, F(4, 447) = 2.58, p < 05] Inspection of the

predictor variables revealed that only divergent learning style (beta =

0.22, t = 1.96, p < 05) significantly predicted scores on phonological

tasks Thus, it is the combination of concrete experience with abstract conceptualization that predicts high performance on phonology

For the regression on syntax and semantics, R was also significantly different from zero [R2= 0.39, F(4, 447) = 4.54, p < 001, and R2= 0.25,

F(4, 447) = 8.04, p < 001, respectively] Scores on syntactic tasks were

significantly predicted by accommodative learning style preference (beta

= 0.19, t = 1.87, p < 05), and scores on semantics were predicted by divergent learning style preference (beta = 0.25, t = 2.31, p < 05) Hence,

performance on syntax can be predicted by a tendency to learn through

a combination of active experimentation and concrete experience, and performance on semantics can be predicted by a tendency to learn through a combination of concrete experience with abstract conceptu-alization, as in the case of phonology

DISCUSSION

In our study, females performed better than males in both syntax and semantics, confirming earlier studies which found a female advantage for verbal skills (Gordon & Lee, 1986; Stumpf, 1995) especially in se-mantics but not phonology (Gordon & Lee, 1986) Although some stud-ies have found no significant difference in learning style preference between males and females (Kruzich et al., 1986; Willcoxson & Prosser, 1996), our study corroborates previous findings that revealed a tendency for females to emphasise a divergent learning style (Katz, 1988; Kolb, 1976)

Our mean score results for arts and science students in learning styles conform to results obtained through discipline-based research using the

LSI (Katz, 1988; Kolb, 1985; Kruzich et al., 1986; Reading-Brown & Hayden, 1989; Willcoxson & Prosser, 1996)

The results of our correlational analysis suggest that (a) the prefer-ence for the divergent learning style on phonological tasks and (b) the preference for the accommodative learning style on syntactical tasks might facilitate L2 learning for students from both disciplines These findings are generally consistent with previous studies (Jones, 1997; Melton, 1990; Peacock, 2001) However, some learning styles that are more preferred by science or by arts students are closely associated with higher scores on one or more verbal fluency tasks For example, for science but not for arts students, higher scores on convergent learning style were associated with higher scores on all three verbal fluency tasks For arts students, higher scores on assimilative learning style were asso-ciated with higher scores on syntax, and higher scores on divergent learning style were associated with higher scores on semantics

These findings suggest that L2 teachers should strive for a balanced teaching style that does not excessively favour any one learning style—or rather, one that tries to accommodate multiple learning styles Teachers can present new information and materials in a variety of modes and use

a variety of activities However, as the results of our multiple regression analyses suggest, they should take into account that phonology and se-mantics require the use of pedagogic techniques that favour concrete experience and reflective observation Thus, they can use handouts, vid-eos, encourage note-taking and reading, write key information on the board, use class or group discussions, lectures, tapes, peer tutoring, give oral explanations and instructions, and encourage active participation, because these techniques favour both concrete experience and reflective observation

Moreover, performance on syntax can be predicted by the use of learning preferences that favour active experimentation and concrete experience The use of visual and auditory techniques does not help students so much as the use of problem-solving activities and practical experimentation Where experimentation does occur, as in the learning

of a foreign language, it consists of the oral or written testing of hypoth-eses That is, reflection (on responses to one’s use of language) leads to concept development (the formation of new hypotheses about the con-struction of the language) and the testing of the concepts developed, again through personal experience

Our results imply that L2 teachers need to be more willing to involve learners in planning lessons and tasks, give them more control over their own learning, and try to accommodate all learning styles in the class-room Studies have repeatedly shown that matching teaching styles to learning styles can significantly enhance academic achievement; student

attitudes and behaviour at primary, secondary, and even university levels; and specifically in L2 instruction (Oxford, Ehrman, & Lavine, 1991; Wallace & Oxford, 1992) The current study supports the idea that learn-ing styles may be important factors for teachers to take into account when designing and delivering their programmes and providing guid-ance for students This is especially true in a higher education system where all students, irrespective of age and gender, are being required to (a) take the initiative in learning, (b) move away from an overreliance on lecturers, (c) accept an active student-centred approach to learning as opposed to passive, and (d) understand that they should learn not just for the purposes of assessment but for their own intellectual growth, pleasure, and fulfilment (Sadler-Smith, 1996) Our results delineate the demands placed on teachers but mostly the demands placed on institu-tions to routinely assess their students’ learning styles and train their staff, teachers, and programme administrators, so that they can design instruction that meets the needs of their students and helps them make the most of it

Due to the cross-sectional and correlational nature of this study, which was based solely on self-reports, it cannot be assumed that learning styles determine L2 performance in every case However, because the connec-tion of learning styles and teaching styles is an important and underre-searched aspect of L2 classroom life (Peacock, 2001), further research is clearly needed in this area Moreover, given that a mismatch between teaching and learning styles could cause learning failure, frustration, and demotivation (Ehrman, 1996; Felder, 1995; Kulina & Cothran, 2003), research on L2 learners’ learning preferences may be beneficial to the improvement of learning, attitudes, behaviour, and motivation Future research should address topics such as learning style changes that could give all L2 learners an equal chance in the classroom and build their self-awareness and other possible intervention topics that are of special reference for both teaching methodology and syllabus development Work on students’ learning styles should also continue by collecting data from qualitative research, such as interviews and diary studies More research is also needed on university students’ learning styles because most of the research in the domain has been conducted with primary and secondary populations (Ehrman, Leaver, & Oxford, 2003) In addi-tion, a variety of L2 tasks should be used to delineate the role of each learning style in learning the phonology, syntax, and semantics of an L2 The results of future research will help us understand more fully how individuals learn languages, how and why they undertake and succeed or not in language learning, how one person differs from another in their learning styles, and what can be done to make teaching and learning styles converge in the most successful way

THE AUTHORS

Eleni Andreou is an assistant professor of educational psychology at the Department

of Primary Education, University of Thessaly, Volos, Greece Her research interests include language development, individual differences in students’ learning, social development, and psychosocial adjustment during childhood.

Georgia Andreou is an associate professor of linguistics at the Department of Special Education, University of Thessaly, Volos, Greece Her research interests include bilingualism, multilingualism, language development in children with attention defi-cit and hyperactivity disorder, and neuropsychological approach of language devel-opment.

Filippos Vlachos is an assistant professor of psychophysiology at the University of Thessaly, Volos, Greece His research interests include the psych-physiological and neuropsychological approach to learning and learning disabilities as well as the relationship between brain laterality and cognitive abilities.

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