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Making a difference in languagelearning: the role of socioculturalfactors and of learner strategyinstructionMichael Grenfell a & Vee Harris ba School of Education, Trinity College, University of Dublin ,Dublin , Irelandb Department of Education , Goldsmiths College, University ofLondon , London , UKPublished online: 19 Dec 2012.

To cite this article: Michael Grenfell & Vee Harris (2013) Making a difference in language learning:the role of sociocultural factors and of learner strategy instruction, The Curriculum Journal, 24:1,121-152, DOI: 10.1080/09585176.2012.744326

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© 2013 British Curriculum Foundation

The Curriculum Journal, 2013Vol. 24, No. 1, 121–152, http://dx.doi.org/10.1080/09585176.2012.744326

Making a difference in language learning: the role of socioculturalfactors and of learner strategy instruction

Michael Grenfella* and Vee Harrisb

aSchool of Education, Trinity College, University of Dublin, Dublin, Ireland; bDepartmentof Education, Goldsmiths College, University of London, London, UK

There has been increasing concern over the poor performance andlack of interest in modern language learning among secondary-schoolstudents. Although there is some evidence as to the under-achieve-ment of boys in modern languages (ML), there is less information asto the degree to which other factors such as social class, and bilingualor monolingual status play a role; the focus of much ML researchbeing on individual rather than sociocultural differences in languagelearning. The present study took place in two London schools with120 students aged 12–13 years learning French. Using multipleregression analysis, it brings together psychological and socioculturalperspectives to examine the role of these factors on performance andmotivation. In addition, it explores if these same factors are alsosignificant in terms of students’ responses to explicit instruction toteach students the strategies they need to operate autonomously.Findings suggest that at this early stage in their language learningcareer, there was no significant difference in terms of gender onperformance or motivation but all bilingual students, regardless ofwhether they were in the control or experimental classes, out-performed their monolingual peers in listening comprehension;linguistic features of their home background appeared to providesome explanation. Furthermore, the strategy instruction was also asignificant factor in determining progress. The 12–13 age range maybe a critical time for students, when teaching them how to learn mayreverse an otherwise downward spiral in achievement and motivation.

Keywords: data analysis; learning strategies; pedagogy; modernforeign languages

Introduction

The last two decades have seen something of a crisis in modern language(ML) learning in English secondary schools. It has been describedrecently as ‘close to extinction’ (Shepherd 2011), because the number ofstudents taking French and German General Certificate in Secondary

*Corresponding author. Email: grenfelm@tcd.ie

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Education (GCSE), taken at age 16, has more than halved in the last 16years. The picture is almost identical for those studying French A-level(taken at age 18) since 1991 (Curtis and Shepherd 2009). While the newmillennium has seen concern over the under-achievement of boys in MLperformance (Department for Education and Skills [DfES] 2007; Sedghiand Evans 2011), social class has been largely ignored. In contrast, asWhitty (2012) points out, social class inequalities in education have been aconstant feature of English education research since the early part of thetwentieth century, broadening out in the 1980s to include other socialdifferences such as gender, sexuality and race. However, within secondlanguage acquisition research the learning process has been perceived asan individual cognitive process located in the mind of the learner. The last10 years have seen this view challenged by those for whom it is a socialenterprise whereby meaning is co-constructured by interlocutors in aparticular sociocultural context. Summarising the two positions, Larsen-Freeman (2007, 784) comments: ‘Our field is beset by dialectics: learningversus use, psychological versus social, acquisition versus participation,and yet, it is focussing on the dynamic coupling of each pair that is likelyto be the most productive’.

One initiative to reverse the downward trend in the study of MLhas been explicitly to teach students language-learning strategies (LLS)(Macaro and Mutton 2009; Cohen and Macaro 2007; Harris 2007;Grenfell and Harris 1999). The LLS research field itself has alsowitnessed a shift from psychological to sociocultural perspectives. Withsome notable exceptions (Wong Fillmore 1979), early studies into LLScould be characterised as being more from a psychological perspective,stemming from Rubin’s (1975) seminal study ‘What the ‘‘GoodLanguage Learner’’ can teach us’, which sought to uncover what itis that these individuals do that separates them from their lessproficient peers. O’Malley and Chamot’s (1990) seminal taxonomyidentified cognitive strategies, such as inferencing, and metacognitivestrategies such as planning, monitoring and evaluation. It also includeda limited number of social strategies, defined as those involved ininteracting with others. It is only within the last decade that LLSstudies have explored how what might be termed ‘the widersociocultural context’ impacts on strategy use. In line with Gipps’(1999) study of the sociocultural aspects of assessment, the definitionof ‘sociocultural’ in the present article includes economic and politicalcontexts, as well as social and cultural ones, thus connecting toWhitty’s (2012) discussion of social inequalities. Norton (2000), forexample, explains how a seemingly shy, unforthcoming immigrant canbe dismissed as a ‘poor language learner’, rather than acknowledgingthe power relations that distance her from unsympathetic, impatientnative speakers. This restricts her opportunities to engage in

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communication with peers or colleagues and thus to develop herlanguage. Although less common, the sociocultural approach has alsobeen extended to strategy instruction (SI), where learners are explicitlyencouraged to develop the tools they need to succeed. The majority ofsuch studies focus on the cognitive processes within the individual,examining changes in performance or strategy deployment as a resultof the SI. However, in outlining his social autonomy model, Holliday(2003) takes a broader view, criticising teachers who provide‘imperialistic’ SI based on their own alien cultural values rather thanencouraging students to choose strategies according to their ownpersonal goals.

Although there is increasing evidence for the effectiveness of SI(Hassan et al. 2005), many of the studies focus on adults and universitystudents, often learning English, rather than on young school studentslearning a ML such as French. Furthermore, little is known about the‘weight’ of the SI relative to other potentially powerful factors, such asgender and background that may impact on a learner’s progress.Although socio-economic background has been shown to play animportant role in determining educational achievement generally (Cassenand Kingdon 2007), to what extent does this apply specifically to ML?And do such factors also come into play in determining students’response to the SI itself?

The present article addresses these questions in the context of aprogramme of listening and reading SI undertaken over the course of ninemonths with near-beginner learners of French in two London secondaryschools, each with a different socio-economic intake.

A combination of qualitative and quantitative measures was used.Student progress was measured using tests. However, recognising theimportance of assessing not just their performance but the students’shifting use of strategies as they tackle a task (Manchon 2008), 27 case-study students undertook think-alouds in listening and reading compre-hension. The students also engaged in semi-structured interviewsregarding their existing strategy use and their reactions to the SI. Detailscan be found in Harris (2006, 2007). However, the present articlediscusses the quantitative findings, as the focus is the relative contributionto student progress of a range of sociocultural and individual factors.Although limited, some reference will be made to the qualitative findingswhere they can shed light on particular issues raised.

Background

Although the ‘good language learner’ (GLL) was a key concept inestablishing the study of learner strategies as a legitimate field ofresearch, the approach has been criticised subsequently for two main

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reasons; the first broadly psychological, the second sociocultural.What characterises the successful learner is not the number ofstrategies used but how they are used and orchestrated in combinationwith other strategies and how they vary according to task (Cohen andMacaro 2007). Using prior knowledge, for example, may be unreliableif the listener jumps to unwarranted conclusions, without monitoring ifit makes sense.

The second criticism of the GLL research was the emphasis on theindividual, rather than on the group, on the cognitive rather thansociocultural. Subsequently, some studies have adopted a more socio-cultural approach. Takeuchi, Griffiths, and Coyle (2007) summarisestudies that discuss individual, situational and group differences,exploring the relationship between strategy use and gender, proficiency,and motivation. They point out that much of this research is inconclusiveor contradictory, sometimes because the cultural contexts themselvesdiffer. For example, Dreyer and Oxford (1996), in their study of SouthAfrican students, found that females use strategies more often than males,particularly social and metacognitive strategies. In contrast, in hisinvestigation of students in Singapore, Wharton (2000) reported thatmen use more strategies than women and neither Griffiths (2003) in NewZealand nor Nisbet, Tindall, and Arroyo (2005) in China found anydifference. Social class, however, is not included in Takeuchi, Griffiths,and Coyle’s (2007) review. They themselves acknowledge the relationshipbetween a wide range of both individual and sociocultural factors in theirplea that:

. . . future research, rather than trying to isolate these many variables fromeach other as much previous research has done, needs to develop methodsfor including consideration of the multiple factors which affect the waysthat individual learners learn in specific situations. (Takeuchi, Griffiths, andCoyle 2007, 92)

Such critiques of the GLL perspective have implications for the othermajor area related to LLS – namely explicit strategy instruction. A keyclaim is that ‘intervening in learners’ strategic behaviour can improvelearning processes and ultimate attainment’ (Cohen and Macaro 2007, 4).There is increasing consensus over the broad sequence of steps to befollowed in such SI programmes, from ‘awareness raising’ throughmodelling and practising new strategies to evaluating strategy use (Rubinet al. 2007; O’Malley and Chamot 1990). Although initially the learners’use of strategies is heavily scaffolded, the support is gradually removed toensure that students can operationalise them independently in a way thatis appropriate to the task in hand (Macaro 2001; Grenfell and Harris1999).

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Recognising that strategies are not deployed in a decontextualisedvacuum, one aim of the systematic Evidence for Policy and PracticeInformation and Co-ordinating Centre (EPPI-Centre)1 review of SI(Hassan et al. 2005, 2) was to:

. . . uncover differential effectiveness for different languages, differentlearners (school, university, adult), different stages of learning (beginner,intermediate, advanced) and different language skills (reading, writing,listening, speaking, overall ability etc). In doing so, we hoped to explorewhy different types of strategy training might or might not work.

While there is some evidence for the effectiveness of SI with adult learnersof English, Hassan et al.’s findings highlight the need for moreinterventions with school-level learners learning ML and for morelongitudinal studies. The large-scale ‘Learning how to learn’ (LHTL)study by James et al. (2007) provides invaluable insights into staffresponses to the initiative across subjects and across primary andsecondary schools. Implications of SI, specifically for ML and Englishcollaboration at secondary-school level, are explored by Harris (2008).However, a systematic study of the impact of SI on ML students in termsof both individual and sociocultural differences has not as yet beenundertaken. Oxford and Schramm (2007) argue that the psychologicaland the sociocultural should be complementary, explaining that a critical,sociocultural framework explores how issues of power, oppression,imperialism, and resistance come into play in the teaching and learning ofsecond language strategies. Although there are very few of such studies,the definition connects with Whitty’s (2012) reflections on developmentsin the field of the sociology of education.

It is with these considerations in mind that the present study wasundertaken. The first step in the investigation was to examine the extentto which research into the key role of factors such as social class andgender in determining educational success across the curriculum appliesspecifically to secondary-school students learning ML. The study movedon to investigate the impact of SI relative to these other factors. Finally, itexplored whether any potential benefits of the SI extend to all students orif they are limited to particular groups according to, for example, theirgender, background or bilingual status.

The next section begins by summarising research into individual andsociocultural differences in language learning success, reflecting on theirpossible weight compared with SI. For example, gender may be a moresignificant factor than the SI for the students in the study, given that moreboys than girls opt out of continuing their studies of ML to GCSE level(DfES 2007; Coleman, Galaczi, and Astruc 2007; Sedghi and Evans2011).

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Although the evidence is grouped under key headings (‘gender’ or‘attainment’ for example), inevitably there is some overlap between thefactors. The headings also include whether each factor will or will nothave a role to play in determining students’ response to the SI itself. Todate little is known about whether there are differences in response to SI,even within the adult learning context. The majority of SI research hasfocused on the impact of the intervention in terms of test results or shiftsin patterns of strategy use. Because factors such as gender influenceprogress in language learning, it seems likely that they will play a role indetermining the students’ response to the SI. It may or may not succeed,for example, in reversing boys’ under-achievement.

Since few studies of SI have attempted to bridge the gap between thepsycholinguistic and the sociocultural, the literature review will raise asmany questions as it answers, particularly in relation to students’response to SI. Furthermore, breaking down boundaries betweenresearch fields risks failing to treat each in sufficient depth.

The role of sociocultural and individual differences in language learningprogress

Social class

The present study was based in two London schools: Moreton and West(pseudonyms). West School is a large, multi-ethnic, mixed comprehensiveschool in a working-class area of southeast London. Moreton School is asmall, mixed, voluntary-aided catholic school, serving a predominantlymiddle-class population in a London suburb. The schemes of work, alongwith teachers’ records, indicate that generally the national curriculumlevels at Moreton School are higher across the curriculum than at WestSchool. The issue in the present study was the extent to which social classimpacts specifically on the rate of progress in ML. In spite of thegovernment’s drive to raise standards in England, social class is still thestrongest indicator of educational success (Gilborn and Mirza 2000;Bynner and Joshi 2002). Eligibility for free school meals, for example, isstrongly associated with low educational achievement generally (Cassenand Kingdon 2007). Social class may also be associated with the level ofchallenging behaviour in the classroom and high or low parentalexpectations. Reay (2006) vividly describes how working-class pupilsmay be marginalised by teachers’ behaviour towards them. Little isknown about the links between social class and ML performance.However, it seems likely that the students’ attitudes towards languagelearning, whether positive or negative, will play a role in their progress,especially in the light of Bartram’s (2006) study of the importance ofparental influence on attitudes to language learning. Moreton Schoolstudents may have the advantage of holidaying in France or Spain and

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hence may be more motivated, since they see the relevance of learning anew language (Buttjes and Byram 1991). Motivation is a complex,controversial phenomenon; for example, whether it is a psychologicalattribute or a sociological condition and how the unit of analysis, oncedefined, can be researched. In contrast to Gardner and Lambert’s (1972)comparison between instrumental and integrative motivation, Dornyei(2001) emphasises its dynamic nature as it changes over time and also thekey influence of the learning situation and classroom ethos. As early as2002, Chitty (2002) highlighted the link between social class andmotivation, pointing out that students opting out of language learningat age 14 are much more likely to come from inner-city schools. The trendtowards languages as an elitist subject has continued (CILT 2006) and theGuardian warns that the study of ML is becoming a privilege largelyrestricted to private schools (Curtis and Shepherd 2009). It seems possiblethat the more positive attitudes of the middle-class students may alsomake them more willing to engage in LHTL. Qualitative data exploringmotivation issues in more depth are discussed in Harris (2006) and Harrisand Prescott (2005). The focus here is on the quantitative evidence toweigh up the potential impact of social class on these students’ progressand attitudes towards language learning, relative to the other factors.

Gender

The last 20 years have been marked by a preoccupation with the under-achievement of boys across many areas of the curriculum (Departmentfor Education [DfE] 2007, 2010). It has been evident in ML in England(Nuffield Foundation 2000; Ofsted 2004), Australia (Carr and Pauwels2005) and Canada (Kissau 2006). The problem in England has beenfurther exacerbated since students are allowed to opt out of studying alanguage after age 14. In 2004 the Chief Inspector for Schools had alreadyexpressed his concern that French and Spanish might become the preserveof middle-class girls (Bell 2004). The situation has continued todeteriorate (Rodeiro 2009). Figures regarding the gender imbalance inML in England are often drawn from a comparison of GCSE results.However, it is not clear at what age such disenchantment on the part ofboys occurs and whether the SI might contribute to reversing the process.Furthermore, the link between gender, motivation and attainment has tobe taken into account. Given boys’ under-achievement, the femalestudents may be more successful language learners and more motivatedthan their male peers, prior to the intervention. They may, therefore, bemore receptive to the SI. On the other hand, Harris et al. (2001) point outthat high attainers of either gender can become complacent, believing thattheir existing use of strategies already guarantees them success. Thepossibility that boys in particular might benefit from the SI is increased in

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the light of the study by Jones and Jones (2001). This suggests that boysvalue explicit discussion of what and why they are learning and how toapproach it. They also benefit from developing greater skills of self-regulation (Watkins 2007). Thus, the issue is whether these 12–13-year-oldboys are already under-achieving and whether the SI can reverse thedownward trend? This may apply particularly to reading, compared withlistening, since Shapiro (2007) suggests that girls’ superior attainment is morepronounced for skills linked to literacy, even in their mother tongue (L1).

Bilingualism

Definitions of bilingualism are complex and include considerations ofwhen the languages are learned (in parallel or consecutively), whetherlearners are first, second or third generation, different levels of proficiencywithin the skill areas and the support and prestige offered for theirdevelopment in the school and in the community (Anderson 2008;Cummins 2000). For many years, bilingual students were consideredproblematic for the special needs they represented; competence in thehome language was seen as interfering with the development of English.The view was discredited by Cummins’ ‘common underlying proficiencymodel’, which argues that although on the surface the two languages aredifferent, underneath they are fused in a single, central, processing system(Baker 2006). Nevertheless, some groups do under-perform and the startof the millennium saw a raft of initiatives to support them (DfES 2004,2006). Uncovering the reasons for their under-performance is particularlycomplex since bilingualism is linked to class and race and there isconsiderable variation in educational achievement between ethnic groups(Gilborn and Mirza 2000).

Within ML, there is a growing body of evidence that bilingualismfacilitates the acquisition of a third language (see Jessner [2008] for anoverview of current findings). However, in light of Norton’s (2000) andCummins’ (2000, 2001) research, it seems likely that a complex range offactors may be involved in the progress of bilingual students learningFrench in these English secondary schools, including not only theirgeneral proficiency level, ethnic group, home environment and sense ofidentity but also the schools’ ethos and policies in relation to recognisingand validating that identity. It is, therefore, hard to predict the likelyimpact of the SI weighted against the role of the students’ bilingual ormonolingual status itself. Do bilingual students make more progress asthey have already developed some of the strategies? Or for that veryreason do they, therefore, perceive the SI as a ‘waste of time’? Do theyindeed make the connections between the ‘natural’ home languagelearning environment and the school classroom? In summary then, thequestion is whether the students’ bilingual status facilitates their progress

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in ML and if bilingual or monolingual status is a factor in determiningtheir response to SI.

Attainment

‘Attainment’ is the term used by the English government to capture thelearner’s level at a particular moment against set criteria regardless of age.Hence, for example, their concern to analyse over time student attainmentby gender (DfE 2010) and by minority ethnic group (DfE 2007).Attainment thus expresses the outcome of the interaction of a number ofcomplex factors, including those already discussed, such as motivation.While some of these factors might fluctuate over time, it seems likely thata student’s existing attainment level is a significant factor in determiningtheir progress; successful high attainers making greater progress over thecourse of the year than low attainers. Furthermore, high attainers’ widervocabulary may also enable them to benefit most from the SI. A commondistinction in terms of reading and listening strategies is made between‘bottom-up’ strategies such as word-for-word translation and more global‘top-down’ strategies such as inferencing. Macaro, Graham, andVanderplank (2007) argue that it may be that learners’ lexical knowledgeneeds to exceed a certain ‘threshold level’ if they are successfully to exploittop-down strategies such as prior knowledge. So for some low-attainingstudents in the present study, the SI may simply be ‘beyond’ them. However,the evidence is inconclusive. In one of the few studies of individualdifferences in response to SI, Ikeda and Takeuchi (2006) report on its impacton 210 Japanese university English as a foreign language (EFL) students.They noted that for the lower-proficiency group the intervention was noteffective enough to make them change their strategy use and surmised thatthey did not have enough EFL reading ability to make use of the top-downstrategies that were the main focus of the SI. In contrast, Kusiak’s (2001)study showed particularly positive results for the lower-proficiency groupand Van Der Grift’s (2007) weaker listeners in the experimental classes madeno fewer gains in listening than those in the control class.

The possible negative impact of a ‘threshold level’ has to be balancedagainst low attainers’ increased motivation, since there is some evidencethat SI enhances motivation (Chamot et al. 1996). Rubin (1990, 282)highlighted its potential benefits for low attainers, linking it tomotivation: ‘Often poor learners don’t have a clue as to how goodlearners arrive at their answers and feel they can never perform as goodlearners do. By revealing the process, this myth can be exposed’.

Thus, the low-attaining students’ limited lexical repertoire might becompensated for by their increased motivation. Baines, Blatchford, andChowne’s study (2007) may be of some interest here, even though it wasnot concerned with teaching LLS specifically. Rather, the focus was on

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collaborative group work skills, the aim being to explore the impact oftraining primary-school students to develop them. They found that low,middle and high attainers made equal progress over the year; nor wasthere any difference according to gender. In summary, then, the issue hereis to establish whether, in spite of their attainment level, low attainers canmake as much progress as high attainers and whether they can benefitfrom the SI. The present study thus sought to explore the followingresearch questions:

(1) What are the potentially powerful factors such as socio-economicbackground, gender, bilingual status, and attainment, which makea significant difference to 12–13-year-old students’ performanceand motivation in ML?(a) How strong a predictor of success is social class specifically in

ML?(b) Do girls already out-perform boys at the age of 12–13?(c) Is students’ bilingual status a problem or an advantage?(d) To what extent does prior attainment predict future

performance?(2) What is the impact of SI relative to these other factors? Does it

make a significant difference, and if so, does it play more or less ofa role than gender or background?

(3) Within the group exposed to SI, what role do these other factorsplay, if any? Do some sub-groups benefit more from the SI thanothers?(a) Are middle-class students more motivated to ‘learn how to

learn’?(b) Do boys respond positively to explicit discussion about ‘how

to learn’?(c) Do bilingual students perceive SI as unnecessary since they

are already familiar with LLS?(d) Do low attainers in particular value learning the tools they

need to be more successful?

Research methods

Project participants and school context

Data were not collected about each individual student’s socio-economicbackground but Ofsted2 reports indicate that West School has a highernumber of students entitled to free school meals than the national averageand a higher number of students with special educational needs (SEN).Standards on entry are below the national average. In contrast, MoretonSchool has fewer students with SEN than the national average andstudents’ attainment level on entry is above the national average. The

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national curriculum levels in Moreton School are higher than for WestSchool, suggesting, in relation to the earlier discussion of a ‘threshold’level, that the learners may have a larger lexical repertoire.

The investigation was ‘quasi-experimental’ in design, using intact classgroups: in each school, two parallel classes of 30 students aged 12–13years learning French. The classes had been designated by the schools as‘top sets’. As is usual in experimental research such as clinical trials, therewas a control and an experimental class. Both classes followed the MLscheme of work in each school but the experimental classes were alsoexposed to an explicit SI programme (see Harris [2006, 2007] for adetailed description of the intervention). Thus, it was considered ethicallyacceptable, as it was a question of possible ‘added value’ for theexperimental classes and the control classes would not necessarily bedisadvantaged. Parental permission was sought and granted.

The students had begun to learn the language at the start of theprevious year, with approximately two hours a week of lessons; thusapproximately 80 hours of language learning prior to the intervention.Within the 120 students across the control and experimental classes, 51%of the students were female in each school; 33% of the students at WestSchool and 3% at Moreton School (i.e. 18% across both schools) weredesignated as ‘bilingual’. For the study’s purpose, the designation of thestudents as ‘bilingual’ was mainly determined by the school’s ‘English asan additional language’ list. Students between stages 3 and 5 in English onthe list had been educated in the UK from birth or an early age and aquestion in a pre- and post-intervention attitude questionnaire establishedif they were regularly exposed to another language within the extendedfamily and community networks. They were thus operating in twolanguages from an early age. They came from a wide range of culturalbackgrounds, typical of London, including Vietnamese, Somali, Turkish,Yoruba and Tamil (National Literacy Trust 2006). There was, therefore,not a particular dominant group in terms of the link to social class.

While there was a risk of both teachers and pupils in the experimentalclasses sharing experiences with those in the control classes, it was decidedto locate the classes in the same schools, rather than different schools, inorder to maximise parity of socio-economic background. The experi-mental classes were taught by the two teachers working on the project andthe control classes by another experienced teacher in each MLdepartment. The SI lessons were developed through close collaborationbetween one of the authors and the teachers (Harris 2008; Harris andPrescott 2005) and based on the model of four steps described earlier towithdraw the support gradually until the students could use the strategiesindependently.

Given the need for extensive practice in the strategies involved in eachskill area, it was decided there was insufficient time to deal with all four

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language skills in sufficient depth over the course of the project. A pilotstudy conducted with the teachers finalised the choice of reading andlistening as the skill areas (Harris 2007) since the students reported findinglistening comprehension one of the hardest skills and reading was felt tobe a useful, related ‘way in’. Both are receptive skills but readingstrategies might be more accessible because the learner has greater controlof the process, as they have the time to read and re-read. Furthermore, SIin these skill areas has been more extensively researched than speaking(Cohen and Macaro 2007). Appendices 1 and 2 list the strategies in bothskill areas. In relation to each specific skill, Oxford et al.’s (2004) revisedversion of Ikeda and Takeuchi’s reading questionnaire was drawn on toidentify the reading strategies. Their focus on task-based strategyassessment overcomes some of the vagueness of generic strategytaxonomies (‘advance organisation’ or ‘inferencing’ for example) andprovides clear descriptions specific to reading (‘I use the title to helppredict the contents’, ‘If I don’t understand something, I guess itsmeaning using clues from the text’); a particularly important factor giventhe students were only 12 years old. Similar reasons guided the selectionof listening strategies from Van Der Grift (1997, 2003), since while theterms remain generic, definitions and representative examples are given.Bearing in mind Cohen, Weaver, and Li’s (1998) observation of thedifficulties learners experience with unclear strategy definitions, thewording was adapted and some strategies were ‘unpacked’ into sub-strategies to make them more accessible to the pupils. In addition, wherepossible, the wording was similar across listening and reading strategies toencourage transfer between the two skills. In the overall selection of thestrategies from the aforementioned taxonomies, care was taken to ensurethat they included both metacognitive and cognitive strategies since, asGraham, Macaro, and Vanderplank (2007, 182) suggest, metacognitivestrategy development appears to be a common feature of the moresuccessful SI listening programmes. Oxford et al. (2004) highlightmetacognitive planning, monitoring and evaluation by listing strategiesunder ‘before/while/after reading’ and this was adopted for the layout ofthe strategy checklists given to the students. The selection included both‘top-down’ and ‘bottom-up’ listening and reading strategies to reflect thecomplex parallel interaction between world knowledge (topic, genre, etc.,to build a conceptual framework for comprehension) and linguisticknowledge or compensatory strategies to cope with lack of suchknowledge.

The SI initially focussed on reading strategies rather than listeningstrategies, as they are easier to model and arguably easier to use, since thelearner has time to reflect on the areas of difficulty and return to them(Grenfell and Harris 1999). Over a nine-month period, the experimentalclasses were taught 25 lessons or parts of lessons incorporating SI; the

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control class was merely exposed to the same reading and listening texts.3

The importance of a gradual approach, in which clusters of strategies arefirst presented in familiar contexts, and the need for even more practicethan had been anticipated are discussed in Harris and Prescott (2005),and an analysis of the qualitative data on the students’ opinions of the SIin Harris (2007).

Research measures

In order to examine whether SI results in improved performance, areading and listening test in French was administered pre- and post-intervention. Since there are no national standardised tests at this level(Macaro and Erler 2005), the tests first had to be piloted. Space does notpermit a discussion of the difficulties raised in devising the tests but someof the issues are discussed in the EPPI-Centre review (Hassan et al. 2005).For example, it was important to ensure that the nature of the testsallowed all the strategies to be used. Whereas the reliability of thelistening test, estimated by Cronbach’s alpha, was high (0.839), it wasslightly lower for the reading test (0.703). The tests were marked by theresearch officer, according to agreed criteria, and a sample marked by oneof the authors. Inter-rater reliability was high: 0.995 for the reading testand 0.986 for the listening test.

Drawing on Chambers (1999), who explored motivation with cohortsof ML learners of a similar age in England, a general attitude score wasconstructed by taking the mean of responses to Question 1 (‘How do youfeel about learning a new language like French?’) and Question 2 (‘Howhard do you think you try to learn French?’). While somewhat crude as ameasure, this score was used to give a broad indication of level ofmotivation.

Semi-structured interviews and think-aloud protocols were carried outwith 27 case-study students of different attainment levels and of bothmonolingual and bilingual status. A detailed description of the findings isnot included in the present article but they are discussed by Harris (2006,2007).

Research methodology

Separate independent samples t-tests and between-groups analyses ofvariance (ANOVAs) could have been used to assess the impact of SI onthe performance of the experimental classes compared with the controlclasses. However, the study sought to examine the role that factors otherthan the SI played in students’ progress, and their relative influence.Multiple regression analysis (MRA) allows comparison of an interven-tion’s impact with that of other factors determining students’ progress

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134 M. Grenfell and V. Harris

Table

1.

Squaredcorrelations(r2)betweenpredictors

andeach

other,andwithsummer

scores.

Experim

ental

group

School

Gender

Bilingual

Prior

listening

Prior

reading

Prior

attitude

Summer

listening

Summer

reading

School

Gender

Bilingual

(–)0.17***

0.02

Priorlistening

(þ)0.40***

(–)0.04*

Priorreading

(–)0.03{

(þ)0.13***

0.01

(þ)0.27***

Priorattitude

(þ)0.05*

0.01

(þ)0.03{

(þ)0.05*

Summer

listening

(þ)0.03{

(þ)0.16***

0.01

(þ)0.39***

(þ)0.24***

(þ)0.07**

Summer

reading

0.01

(þ)0.06*

(þ)0.03{

(þ)0.06*

(þ)0.25***

(þ)0.06*

(þ)0.14***

Summer

attitude

(þ)0.05*

(þ)0.06*

0.01

0.03

(þ)0.47***

(þ)0.05*

(þ)0.06*

Higher

is:

Experim

ental

group

SchoolR

Fem

ale

Bilingual

Higher

score

Higher

score

Higher

score

Higher

score

Higher

score

Notes:

(þ)and(–)indicate

directionofeff

ect(i.e.signofcorrelationbefore

itwassquared);

empty

areasindicate

r25

0.010;{ p

50.100;*p5

0.050;

**p5

0.010;***p5

0.001.

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(Brantmeier 2004; Hatch and Lazarton 1991). Since the aim of this aspectof the present study was to explore the relative ‘weight’ of the SI, theeffect of being in the experimental group was one of the factors includedin the regression. The other factors included for comparison were:students’ prior attainment (their autumn score on the same test); schoolattended (as an indication of socio-economic background); gender;bilingual status; and the autumn combined attitude score (as anindication of prior motivation). To explore whether the SI was especiallyvaluable depending on any of these variables (for example, whether it wasparticularly useful for students at one school), the interaction of each ofthese factors with the SI was also included in the regressions. Theoutcome measures were the students’ gain scores (from autumn tosummer) in the reading and listening test and students’ gain scores in theattitude questionnaire over the same period; the focus being on progressmade rather than on final attainment level.

Regression and correlation analyses were run in Statistical Package forthe Social Sciences (SPSS). The regressions were hierarchical, showingseparately how much of the total variance was explained by theintervention and its interactions; the default ‘Enter’ method was used ateach of the two hierarchical stages. In line with Hatch and Lazaraton’s(1991) guidelines, the linearity of relationships between predictors anddependent variables was examined, co-linearity diagnostics were satisfac-tory and there were no strong indications of heteroscedacity in theresiduals plots.

Results

Selected descriptive statistics are shown in Tables 1 and 2. Numbers ofcases included in each analysis are shown in Table 3.4 Table 4 (column A)

Table 2. Descriptive statistics.

Control groupExperimental

group Overall

n Mean SD n Mean SD n Mean SD

Listening test autumn 48 50 17 52 48 15 100 49 16Listening test summer 48 56 16 52 62 14 100 59 15Listening test change 48 6 12 52 14 14 100 10 14Reading test autumn 47 54 20 60 48 18 107 50 19Reading test summer 47 72 18 60 74 15 107 73 16Reading test change 47 18 17 60 26 18 107 22 18Attitude autumn 53 3.62 0.66 61 3.69 0.75 114 3.66 0.71Attitude summer 46 3.20 0.84 53 3.57 0.74 99 3.39 0.81Attitude change 46 –0.41 0.61 53 –0.16 0.58 99 –0.28 0.60

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136 M. Grenfell and V. Harris

Table

3.

Overalleff

ectsizesofregressionmodels.

Dependentvariable

n

Model

before

includinggroup

Main

effectofgroup

Effectofaddinggroup

andinteractions

Finalmodel

Variance

explained

(R2)

Cohen’sf2

Variance

explained

(R2)

Variance

explained

(R2)

Cohen’s

f2

Variance

explained

(R2)

Cohen’sf2

Listeningchangescore

99

29%

***

0.41

10%

**

18%

**

0.33

47%

***

0.87

Readingchangescore

107

46%

***

0.85

5%

*6%

{0.13

52%

***

1.09

Attitudechangescore

99

6%

***

0.07

4%

*12%

{0.15

18%

***

0.23

Notes:

f2eff

ectsizesof0.02,0.15and

0.35are

considered

small,medium

and

large,

respectively(C

ohen

1988);

{ p5

0.100;*p5

0.050;**p5

0.010;

***p5

0.001.

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The Curriculum Journal 137

Table

4.

Effectofindividualpredictors

intheregressionmodels.

A.Outcome

measure

andsample

size

B.Effectsize

C.Main

effects.Possible

factors

predicting

progress

across

controlandexperim

entalclasses

D.Possible

factors

predictingprogress

within

the

experim

entalclasses;interactionwithexperim

ental

group

Experim

ental

group

Prior

attainment

(autumn

score)

School

Gender

Bilingual

Prior

attitude

Prior

attainment

(autumn

score)

School

Gender

Bilingual

Prior

attitude

Listening

gain

(n¼

99)

Variance

explained:

Zero-order

10%

**

22%

***

8%

**

1%

5%

*1%

0%

4%

*0%

1%

0%

Sem

i-partial

7%

**

20%

**

2%

{0%

4%

*4%

**

0%

5%

**

0%

0%

0%

Beta

0.27

–0.64

0.22

–0.01

0.22

0.24

0.05

–0.33

0.03

0.04

0.03

^Experim

ental

group

^Lower

achievers

Zero-order:

^Westschool

Sem

i-partial:

^Moreton

^Bilingual

^Higher

attitude

^WestSchool

Readinggain

(n¼

107)

Variance

explained:

Zero-order

5%

*36%

***

22%

***

1%

3%

{0%

0%

0%

0%

1%

1%

Sem

i-partial

2%

{20%

**

4%

**

2%

{1%

0%

3%

*0%

0%

0%

1%

Beta

0.13

–0.55

–0.25

0.15

0.11

0.04

–0.21

0.02

0.05

0.08

0.12

^Experim

ental

group

^Lower

achievers

^WestSchool

^Girls

^Bilingual

^Low

autumn

scores

Attitude/

motivation

change

(n¼

99)

Variance

explained:

Zero-order

4%

*1%

0%

0%

5%

*2%

1%

0%

3%

{

Sem

i-partial

5%

*0%

1%

0%

6%

*4%

*0%

1%

1%

Beta

0.24

0.07

0.12

–0.05

–0.27

0.22

–0.03

0.10

–0.13

Lessdeclinein

experim

ental

group

Less

declinefor

lower

prior

attitude

^Moreton

School

Notes:Variancesexplained

are

basedonunadjusted

R2;^indicateswhichgrouporsubgroupmademore

progress;{ p

50.100;*p5

0.050;**p5

0.010;***p5

0.001.

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138 M. Grenfell and V. Harris

lists the measured outcomes in terms of progress in listening andreading comprehension and in positive attitude. Column C indicatesthe relative weight of each of the factors to contributing to thestudents’ progress. Thus, across the control and experimental classes, itshows the contribution of students’ gender to their progress, forexample, as well as of the SI itself. In contrast, Column D, ‘Possiblefactors predicting progress within experimental classes’, does not applyto the control classes and only indicates any differences in response tothe SI according to prior attainment, gender or bilingual status.Significant results are indicated by asterisks, non-significant trends by aplus sign.5

Progress in listening

The MRA model explains 47% of variance in the listening gain score. Inother words, all the factors included in the analysis, such as the SI, genderand prior attainment, account for 47% of the differences between thestudents’ gain scores. In terms of the first research questions as to therelative weight of the factors and their relationship to the SI, Column C inTable 4 shows that the following are significant predictors of the gain inlistening scores in order of effect size, as measured by the zero-ordercorrelation:

(1) Prior attainment (as indicated by the autumn term scores) (22%);low attainers making the most progress over the course of the year

(2) Membership of the experimental group (10%)(3) School attended (8%); West School students gaining more(4) Bilingual status (5%).6

Thus, across control and experimental groups, and regardless of the SI,low attainers made the greatest progress. The higher the score in theautumn term, the less the gain by the summer term; a histogram revealedthat this was not because of a ceiling effect. Socio-economic background,in terms of school attended, was also a significant predictor. Even thoughthe autumn term scores of pupils in West School were below those ofMoreton School, and were still below them in the summer term, theymade significantly more progress. Of further interest is that bilingualstudents (again across both the experimental and control classes) achievedgreater gain scores than their monolingual peers (Figure 1). Finally, thedata in column C also suggest that gender does not play a significant rolein contributing to the gain scores in listening at this stage in the students’language learning career. It is encouraging to note, however, that theintervention was a significant factor in contributing to progress inlistening, with students in the SI group gaining an average of 14%compared with 6% in the control group.

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Turning to the third research question, within the sub-groups of theexperimental classes (Column D), it seems that the listening strategyinstruction benefitted all students regardless of their prior attainment orprior attitude, their gender or bilingual status. Only the school attendedplayed a role. Figure 2 shows that students in the experimental class inWest School made more progress than both those in Moreton School and

Figure 2. Listening test scores by membership of experimental group and schoolattended.

Figure 1. Listening score by bilingual/monolingual status.

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140 M. Grenfell and V. Harris

those in the control classes. It might be assumed that this was becausethere was a larger proportion of bilingual students in West School.However, there were similar numbers of bilingual students in both thecontrol and experimental classes in West School and the MRA indicatesthat there was no significant interaction between group and bilingualism.

Progress in reading

The MRA model explains 52% of variance in the reading gain score. Thefollowing were significant predictors in order of effect size, indicating theirrelative weight in contributing to the progress of these 12–13-year-oldstudents:

(1) Prior attainment, as indicated by the autumn term scores (36%);lower attainers making more progress

(2) School attended (22%); West School pupils gaining more(3) Membership of the experimental group (5%).

Prior attainment and school attended appeared to play a more importantrole in reading gains than in listening gains, and the intervention slightlyless of a role. However, a histogram suggested that a ceiling effect may beinvolved, so some caution must be exercised in interpreting the results.Although data in column C indicate that neither gender nor prior attitudewere significant factors in ML reading progress across the control andexperimental classes, there was a non-significant trend of 3% in favour ofbilingual students. Unlike in listening comprehension, these students didnot start out at a disadvantage in their reading, but they improved morethan their monolingual peers (Figure 3).

Finally, the semi-partial correlations suggest a non-significant trend of2%þ in favour of girls, suggesting that even at this early stage in theirlearning career, they were making more progress, albeit limited, than theboys in reading comprehension.

Within the experimental classes (column D), the reading strategyinstruction benefitted all students regardless of their socio-economicbackground, gender, bilingual status or prior attitude and attainment. Itis only the semi-partial correlation that suggests that students with lowautumn term scores were more likely to benefit from the readinginstruction than high attainers.

Progress in positive attitude

While still significant, only 18% of the variance in the attitude gain scorewas explained by the MRA model (compared with 47% for listening and52% for reading); factors other than social class, gender, bilingual statusor the SI accounted for the remaining 82%. This may reflect the brevity of

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the questions, providing only a crude measure of students’ attitudes, andthe same reason may account for its lack of significance as an independentvariable. Figure 4 shows that the attitudes of all students towards theirlanguage learning were already declining at the end of their second year oflanguage learning, although at this stage neither the students’ socio-economic background, nor their gender, nor bilingual status played a rolein this decline. It is encouraging to note that the attitudes of students in

Figure 3. Reading gain score by monolingual and bilingual status.

Figure 4. Attitude scores by group.

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142 M. Grenfell and V. Harris

the experimental classes are less likely to become negative than those inthe control classes. A histogram suggested that this was not because of afloor effect.

Turning to the responses of the experimental classes to the SI, Figure 5indicates that there was a non-significant trend of 3% for the interactionbetween experimental group and prior attitude. There was thus atendency for students in the experimental classes with very low autumnattitude scores to increase their scores slightly by the summer. In thecontrol group there was no such tendency. The semi-partial correlation of4% in Table 4 column D suggests that students in Moreton School wereless likely to develop negative attitudes than those in West School.

Discussion

The limitations of the present study are apparent. The sample sizes do notquite reach the general guidelines and devising appropriate tests provedchallenging. The ‘Hawthorne effect’ may have had a role to play;involvement in the intervention rather than its particular characteristics

Figure 5. Attitude change by group and prior attitude.

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possibly determining the greater progress of the experimental classes.Nevertheless, the findings suggest some useful avenues for furtherresearch with larger cohorts of students, of varying ages and backgroundsand learning languages other than French. Although the focus of thisarticle is on the psychological and sociocultural aspects of thequantitative data, some reference will be made to the qualitative data,where appropriate.

The results appear promising, at least for this group of students. Thefirst research question set out to explore the potentially powerful factorsthat might make a difference to the level of progress and motivation in12–13-year-old students across the control and experimental classes. Theissue in relation to socio-economic background was its impact specificallyon ML. In spite of the fact that student behaviour in West School is morechallenging than in Moreton School, and that one might surmise thattheir working-class parents might have lower expectations and be lesslikely to take holidays abroad, it was the West School students across thecontrol and experimental classes who made greater gain scores in listening(the possible ceiling effect making it difficult to draw a similar conclusionin relation to reading). The reasons are not apparent and furtherresearch is needed in a range of schools serving different populations.Furthermore, it was low attainers across both schools who made themost progress, suggesting perhaps a need for differentiated approachesto stretch high attainers. Finally, West School students appeared tobenefit more from the listening SI. A possible explanation is offeredwhen comparing the success of the reading and listening SI later in thissection.

Like socio-economic background, assumptions about the role of genderare also challenged, since across control and experimental groups these 12–13-year-old girls did not make more progress than boys in listening and therewas only a non-significant trend in the semi-partial correlation for reading.Further studies are needed to establish whether, at this relatively early stagein their language learning, factors such as social class and gender have not yetsignificantly impacted on students’ progress and are more likely to come intoplay when students reach the 13–14 age range.

Turning to the bilingual students, the study confirms other investiga-tions indicating that knowing several languages can be an asset not aproblem. It could be argued that students should have been utilising theirheightened awareness to achieve more than their monolingual peersalready in Year 7, particularly in terms of their listening skills. However,the limited level of ML classroom language in that initial year may be toosimple for them to make the connections to rich exposure in the homeenvironment. Over the course of the following year, even withoutdeliberately realising it, they may have started to transfer their listeningstrategies to the classroom. The non-significant trend in relation to their

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144 M. Grenfell and V. Harris

reading progress (3%), compared with the significant correlation inlistening (5%) would appear to support the connections with the auralskills developed in the home environment, since, as Anderson (2008, 80)points out: ‘ . . . although comprehension skills may be well developed incertain contexts, this does not necessarily imply confidence in speaking orindeed literacy skills’.

The interviews with the bilingual case-study students highlight theimpact of the home environment (for a detailed description see Grenfelland Harris [2007]). For example, Martelle talked about how she infersmeaning:

I use the words that I do know, and the words that I don’t, I put the‘something’ there instead of it. Like if they were saying ‘I work in’, I wouldthink of what sort of person they are, what their job could be, or I close myeyes, and sort of bring my spirit out, and get myself into that word, what itcan mean.

Asked how she learned to use this strategy, she explains how her mothertold her what to do if she did not understand what she was saying inPatois: ‘Well I just picked it up, ’cause my mum always said to me, if youjust think of all the different possibilities it could be, jumble them up, andthat’s what I done’.

The home environment then means that bilingual students may befaced with more exposure to working out meanings than theirmonolingual peers (Grenfell and Harris 2007). This may be one reasonunderlying the significant difference between monolinguals and bilingualsin the present MRA results.

With regard to the second and third research questions regarding therelative weight of the SI, and whether it benefitted all students, it isencouraging that it had a significant impact on both reading and listeningperformance, for boys as well as girls, and for bilingual as well asmonolingual students. Qualitative data shed some light when comparingthe impact of the SI across the two skill areas. While both of the variancesexplained are slight, the relative weight of the intervention differs;listening (10%) being slightly greater than reading (5%). The reasons areunclear, especially since a questionnaire for the experimental classes(Harris 2007) indicates that 30 pupils (55%) reported that the reading SIhad helped them most, compared with 10 (19%) reporting that thelistening SI had helped most, and 14 (26%) indicating they had helped‘the same’. However, the listening SI may have made more of an impactas both teachers and students were more attuned to it, having alreadyengaged in the reading SI prior to the listening SI. A further reason maybe that students found listening more difficult than reading and hencehaving explicit instruction on how to tackle listening texts was more

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useful, even if many of the students were not themselves aware of it. Asone student commented: ‘listening strategies helped me not to panic’. Thismay explain why West School students appeared to have gained more interms of listening than Moreton School. Possibly, students from themiddle-class background are more exposed to complex language in theirL1, developing valuable inferencing strategies which they transfer to theirsecond language. One student, for example, referred to being obliged tosit and watch the news with his parents and listening to their subsequentdiscussion over dinner: ‘There are words and stuff I don’t understand butI kinda figure it out from the pictures on TV and the way my Dad isalways on about the same things’.

It is interesting to note that there was no significant difference instudents’ responses to the SI according to gender. The girls’ higher level ofmotivation in language learning may have been counterbalanced by theboys’ appreciation of the explicit nature of the instruction, like those inthe research of Jones and Jones (2001). However, it is also possible thatthe general decline in motivation becomes more marked for boys than forgirls from the age of 13 onwards. Given that the SI appears to reduce thisdecline, integrating it into the curriculum throughout the entire span of astudent’s education might contribute to reversing the achievement gapbetween boys and girls. Such a move may also be of benefit to lowattainers, since they, like high attainers, were able to access the SI. Indeed,the significant semi-partial correlation for reading would suggest that lowattainers in particular benefitted from the SI, and it appeared to have hada particularly positive impact on their attitudes. Understanding exactlyhow to go about their language learning may have, as Rubin (1990)suggested, served to demystify the process.

Conclusion

In bringing together both psychological and sociocultural perspectives,the present study contributes not only to an understanding of the impactof SI but also of other factors influencing the progress of 12–13-year-oldstudents learning French. At this early stage in their learning, genderappears to be less influential than expected. In contrast, being bilingualmay be an advantage that has not yet been fully recognised. One strandwithin more recent LLS research notes that being a ‘good languagelearner’ is not sufficient; there must be opportunities to deploy thestrategies (Norton and Toohey 2001). If bilinguals’ ‘good’ languagelearning skills are not valued in school, then they may not fulfil their truepotential. It is promising that SI appears to play a significant role indetermining the progress of young school students aged 12–13 learning aML. Given the high rate at which students in England are opting out ofML after age 14, it appears that there is all to play for in the preceding two

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146 M. Grenfell and V. Harris

years. Learning how to learn languages may be one pedagogical approachthat is effective with all students and may contribute to encouraging themto continue their ML studies.

Acknowledgements

We are very grateful for the grant from the Society of Educational Studies which made thestudy possible. We are also indebted to Mike Griffiths, Goldsmiths College for his con-siderable expertise in the field of statistics and his patient but rigorous support throughout.

Notes

1. The EPPI-Centre was established to develop a systematic approach to theorganisation and review of evidence-based work. Its work and publications engagehealth and education policymakers and practitioners in discussions about howresearchers can make their work more relevant and how to use research findings.

2. Ofsted is the main inspection agency in the UK and is charged with raising educationstandards through its activities: http://www.ofsted.gov.uk/

3. Explicit reference to strategies is unusual in textbooks at this level in England.Rather, both textbooks and teachers see reading and listening activities essentially astesting rather than teaching opportunities.

4. It should be noted that the sample sizes do not reach the general guidelinesrecommended in Tabachnick and Fidell (2007), where m is the number of predictors:138 (50þ 8m) for the overall model and 115 (104þm) for individual predictors. Thismay limit the power of the analysis to find statistically significant effects. On the otherhand, no corrections have been made for multiple comparisons, which may inflatesignificance levels. Table 3 also shows the variance explained by each of the models,and how much of this is explained by being in the experimental group and/or by itsinteractions.

5. Multiple regression comparison can be misleading if factors correlate with each other(Tabachnick and Fidell 2007). It can be useful if studies indicate both the squaredsimple correlation (otherwise known as the zero-order correlation [representing eachfactor’s total contribution to the outcome]) as well as the squared semi-partialcorrelation (representing its unique contribution), as in Table 4. An unusual com-plication that occurs in some studies is that the semi-partial correlation can be higherthan the zero-order correlation, or even pull in opposite directions, if other variables inthe analysis are acting as ‘suppressor’ variables; that is, if they remove variance fromthat predictor which is unrelated to the outcome (Tabachnick and Fidell 2007).

6. With the exception of ‘school’, representing socio-economic background, the semi-partial correlations indicate a similar relative weighting of the factors. The otherexception is that only the semi-partial correlations suggest that students with a morepositive attitude from the outset made greater progress.

Notes on contributors

Michael Grenfell is Professor of Education at Trinity College, University of Dublin, Ireland.He is currently Head of School. He has a long association with educational research, as well asinvolvement in policy forums. He is also author of Modern Language Across the Curriculum(2002), (with V. Harris) Learning Strategies and Modern Languages (Routledge, 1999), andClassroom Language Ethnography (Routledge, 2011). He edited a special series on languagelearning and teaching – Modern Languages in Practice – for Multilingual Matters, whichincludes some 15 titles. He has edited a number of volumes, both books and journals, and is afrequent peer reviewer for a wide range of international academic journals. He was Chair ofUCET Research Committee and Executive member. He was commissioned to write support

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articles for the Key Stage 3 Strategy for Modern Foreign Languages in UK secondary schools.He also convenes UKPOLLS: a UK-based group working on language learner strategies andthe links between research and policy (http://www.ukpolls.net/index.html).

Vee Harris was Senior Lecturer at Goldsmiths College for many years and has publishedextensively on Learner Strategies. A particular area of interest has been the impact of strategyinstruction on younger students.

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Before reading1. I work out from the layout what I am reading; e.g. if it’s instructions, or a

short paragraph or a letter, or even an advert or a brochure2. I try to get clues from any pictures and the title to help me guess what it

will be about3. I try to predict all the words and information that I might find in the text

While reading1. I don’t panic and switch off but I just tell myself it’s OK and keep reading

even if it is hard2. I just try to get the main ideas first and then read it again for the details3. I skip over words that I do not understand4. I try to spot familiar words that I do understand from when we learned

them in class5. I look out for cognates6. I look out for the names of people or places and for punctuation clues7. I think about all the possible things it could mean8. If I don’t understand, I use my common sense to guess the meaning from

the rest of the words in the sentence and what I have worked out so far9. I say the difficult bits out loud or in my own head10. I say in English what I have worked out so far in the sentence and

substitute ‘something’ for the words I don’t know11. I break the word or sentence up into bits that I may recognise12. If I don’t understand one bit, I go back to it and read it over several times

slowly13. I try to use grammar clues to spot what kind of a word it is – a noun, a verb

etc.

After reading1. I try to remember everything that I have read and then fit it altogether so

that it makes sense2. I check back to see if my first guesses still make sense

Appendix 1. Reading strategy checklist

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Appendix 2. Listening strategy checklistWhen I am listening to the CD (or to the teacher talking in French):

Before listening1. I work out from the layout (pictures and instructions) what I will hear; a

conversation, directions round town, a railway announcement2. I try to predict all the words and information that I might hear3. I decide on the key words to listen out for

While listening1. I don’t panic and switch off but I just tell myself it’s OK and keep listening

even if they do talk fast2. I just try to get the main ideas, when the tape is first played, and then I

listen again for details3. I try to get clues from the tone of voice (questions? feelings?) and from

gestures or background sounds4. I skip over words that I do not understand so that I don’t miss what is said

next5. I don’t try to write and listen at the same time6. I make pictures in my head of what is said7. I try to spot familiar words that I do understand from when the teacher

said them in class8. I listen out for possible cognates and think about how they may sound

different in French9. I listen out for the names of people or places and think about how they may

sound different in French10. I break the sounds down into possible words and try writing them down to

see if I can recognise them11. I think about all the possible words it could be and things it could mean12. I double-check words because a word may sound like English but not mean

the same thing at all13. If I don’t understand, I use my common sense to guess the meaning from

the rest of the words in the sentence and what I have worked out so far14. I say in English what I have worked out so far and substitute ‘something’

for the words I don’t know15. If I don’t understand one bit, I listen out for it when the tape is played

again16. I try to use grammatical clues to spot what kind of a word it is – a noun,

verb etc.

After listening1. I try to remember everything I have heard and then fit it all together so

that it makes sense2. I check back to see if my first guesses still make sense

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