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

Abstract

There has been increasing concern over the poor performance and lack of interest in modern language learning among secondary-school students. Although there is some evidence as to the under-achievement of boys in modern languages (ML), there is less information as to the degree to which other factors such as social class, and bilingual or monolingual status play a role; the focus of much ML research being on individual rather than sociocultural differences in language learning. The present study took place in two London schools with 120 students aged 12–13 years learning French. Using multiple regression analysis, it brings together psychological and sociocultural perspectives to examine the role of these factors on performance and motivation. In addition, it explores if these same factors are also significant in terms of students' responses to explicit instruction to teach students the strategies they need to operate autonomously. Findings suggest that at this early stage in their language learning career, there was no significant difference in terms of gender on performance or motivation but all bilingual students, regardless of whether they were in the control or experimental classes, out-performed their monolingual peers in listening comprehension; linguistic features of their home background appeared to provide some explanation. Furthermore, the strategy instruction was also a significant factor in determining progress. The 12–13 age range may be a critical time for students, when teaching them how to learn may reverse an otherwise downward spiral in achievement and motivation.

Keywords:

• data analysis
• learning strategies
• pedagogy
• modern foreign languages

Acknowledgements

We are very grateful for the grant from the Society of Educational Studies which made the study possible. We are also indebted to Mike Griffiths, Goldsmiths College for his considerable 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 the organisation and review of evidence-based work. Its work and publications engage health and education policymakers and practitioners in discussions about how researchers 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 education standards 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 as testing rather than teaching opportunities.

4. It should be noted that the sample sizes do not reach the general guidelines recommended in Tabachnick and Fidell (2007), where m is the number of predictors: 138 (50 + 8m) for the overall model and 115 (104 + m) for individual predictors. This may limit the power of the analysis to find statistically significant effects. On the other hand, no corrections have been made for multiple comparisons, which may inflate significance 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 its interactions.

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 squared simple correlation (otherwise known as the zero-order correlation [representing each factor's total contribution to the outcome]) as well as the squared semi-partial correlation (representing its unique contribution), as in Table 4. An unusual complication that occurs in some studies is that the semi-partial correlation can be higher than the zero-order correlation, or even pull in opposite directions, if other variables in the analysis are acting as ‘suppressor’ variables; that is, if they remove variance from that 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 other exception is that only the semi-partial correlations suggest that students with a more positive attitude from the outset made greater progress.