Learning Styles and Performance in Second Language Tasks

BRIEF REPORTS AND SUMMARIES TESOL Quarterly invites readers to submit short reports and updates on their work These summaries may address any areas of interest to Quarterly readers 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 Ⅲ Learning styles, which refer to a student’s preferred mode for perceiving, organizing, 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 tendency 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 predicted that the styles would be relatively stable over time, like personality characteristics, although they are influenced by long- or short-term situational 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 TESOL QUARTERLY Vol 42, No 4, December 2008 665 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; ReadingBrown & Hayden, 1989; Willcoxson & Prosser) Probably a part of the students’ learning process stems from a personal habitual way of learning, and another part is influenced by the actual learning context students are confronted with (Slaats, Lodewijks, & van der Sanden, 1999) For example, a computer scientist with a general preference for a convergent 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 empirical support (Jones, 1997; Reid, 1987; Rossi-Le, 1995) that students tend to favour kinesthetic and tactile styles (e.g., prefer active participation, 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 individual styles, and science students did not It was also found that science students have a stronger preference for group styles and that arts students have a stronger preference for auditory and individual styles (Peacock, 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 successful language learning Although the study was inconclusive with respect 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 performance on different L2 verbal fluency tasks, we undertook the current study with the aim of investigating the relationship between Greek students’ learning styles and performance on English phonological, syntactic, 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) 666 TESOL QUARTERLY 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 years (mean: years and months) and had obtained the First Certificate in English (Cambridge or Michigan or both of them) about years (mean: years and 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 situations were presented and respondents were required to put four sentence endings in rank order Table shows the coefficient alpha reliabilities and an intercorrelation matrix of the LSI scales The reliabilities range from 0.82–0.89 Table 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 Coefficient Alpha Reliabilities and Scale Intercorrelations Scale CE RO AC AE AC–CE AE–RO CE RO AC AE AC–CE (0.83) −0.31** (0.89) −0.37** −0.14* (0.86) −0.54** −0.77** −0.69** (0.82) −0.16* 0.00 0.39** 0.03 −0.04 −0.71** −0.08 0.00 −0.07 Note CE = concrete experience, RO = reflective observation, AC = abstract conceptualization, AE = active experimentation; coefficient alpha shown in diagonals; *p < 0.05, **p < 0.01 BRIEF REPORTS AND SUMMARIES 667 are the AE scale and the RO scale The matrix also shows that the two bipolar dimensions are essentially independent of each other, as expected 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 semantic 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 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 reported 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 668 TESOL QUARTERLY TABLE Means and Standard Deviations for Variables in the Study, by Discipline Variable Total (N = 452) Arts (n = 232) Science (n = 220) F (1450) Accomodative Divergent Convergent Assimilative Phonology Syntax Semantics 65.42 (9.44) 61.89 (8.94) 55.86 (8.82) 52.81 (8.81) 10.73 (4.22) 7.17 (2.33) 31.02 (7.36) 64.61 (9.76) 63.28 (6.88) 54.82 (8.05) 53.94 (8.98) 11.57 (4.43) 7.37 (2.07) 32.58 (7.55) 66.42 (9.76) 59.74 (8.23) 58.71 (7.88) 52.92 (8.20) 10.31 (4.43) 7.76 (2.28) 30.03 (7.30) NS 29.95** 53.44** 6.11* 6.22* NS 8.10** Note *p < 0.05, **p < 0.01 Table 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 students 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 students 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 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 Correlations Between Learning Styles and Scores on L2 Verbal Fluency Tasks Phonology Accomodative Divergent Convergent Assimilative Syntax Semantics Arts n = 232 Science n = 220 Arts n = 232 Science n = 220 Arts n = 232 Science n = 220 −0.021 0.246** 0.058 0.088 0.033 0.199** 0.173* 0.015 0.138* 0.118 −0.067 0.248** 0.286** 0.117 0.196** 0.037 0.70 0.166* −0.008 0.077 0.056 0.010 0.250** 0.053 Note *p < 0.05, **p < 0.01 BRIEF REPORTS AND SUMMARIES 669 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 regressions 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 conceptualization, 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 semantics but not phonology (Gordon & Lee, 1986) Although some studies 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 670 TESOL QUARTERLY 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 preference 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 associated 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 semantics require the use of pedagogic techniques that favour concrete experience and reflective observation Thus, they can use handouts, videos, 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 hypotheses That is, reflection (on responses to one’s use of language) leads to concept development (the formation of new hypotheses about the construction 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 classroom Studies have repeatedly shown that matching teaching styles to learning styles can significantly enhance academic achievement; student BRIEF REPORTS AND SUMMARIES 671 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 learning styles may be important factors for teachers to take into account when designing and delivering their programmes and providing guidance 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 institutions 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 connection of learning styles and teaching styles is an important and underresearched 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 addition, 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 672 TESOL QUARTERLY 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 deficit and hyperactivity disorder, and neuropsychological approach of language development 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 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