What Role Does The Home Language Play In Science Achievement?: A Multilevel Approach
Author(s):
Evelien Van Laere (presenting / submitting) Johan van Braak
Conference:
ECER 2014
Format:
Paper

Session Information

31 SES 03, Language and Science Education

Paper Session

Time:
2014-09-02
17:15-18:45
Room:
B006 Anfiteatro
Chair:
Ana Sofia Pinho

Contribution

Science plays a central role in industrialized as well as industrializing countries. It is not only one of the catalysts for the development of society, it also has a major part in its culture. This implies that an understanding of scientific phenomena is necessary to participate fully in society1. Therefore, science achievement is an important outcome of schooling. However, the focus of research in academic achievement is mostly on literacy and numeracy and much less on other cognitive outcomes, such as sciences2,3.

Research has already shown that different factors, such as gender4, grade retention5, and family’s socioeconomic status (SES)6, are related to science achievement. However, special attention should also be given to the role of literacy in science education7. Indeed, students need to acquire knowledge and skills through a decontextualized language, which is derived from the language of scientists and characterized by a specific vocabulary, a high level of abstraction and the description of phenomena with limited contextual support8. This is linked to the distinction between ‘basic interpersonal communicative skills’ (BICS) on the one hand and ‘cognitive academic language proficiency’ (CALP) on the other hand9. While BICS deals with the social use of language in daily activities (e.g. conversations), CALP refers to the decontextualized school language, which is a more complex and cognitively demanding language variant. Science education is one of the learning domains in which this language is most prominent because the focus lies on the understanding of concepts and the analysis, organization, synthesis and evaluation of information. Therefore, the decontextualized school language can be considered as the key to scientific understanding8.

To develop this decontextualized language and thereby learning to think in a complex way, students already need to have reached a certain proficiency level in the language of instruction. Moreover, language minority (LMi) students (i.e. students whose home language is not the same as the language of instruction) are faced with a double challenge: they have to acquire academic knowledge and skills through this decontextualized school language but they have to do this in the language of instruction, which they have not yet mastered fully10. This can lead to a situation in which language becomes a barrier to achieve a high level in science performance11. Especially in light of the growing cultural and linguistic diversity classrooms are faced with today, it is vital to gain a better understanding of the role the home language plays in science achievement.

Finally, it is necessary to broaden educational research with studies incorporating a multilevel approach. In this way, not only student characteristics are taken into account but also the influence school characteristics have on student outcomes. Indeed, students attending the same school have more in common than students going to another school, due to selection procedures and students’ shared experiences by being part of the same group12.

In this study, we take on a multilevel approach with the focus on the following research question:

How are both student and school characteristics associated with fourth grade students’ science achievement in primary schools with a diverse cultural and linguistic background?

In line with the European strategy for multilingualism13, which emphasizes promoting linguistic diversity in society, special attention is given to the role of having another home language than the language of instruction.

Method

Data were collected from 1,761 fourth grade students (median age=9) in a sample of 67 primary schools in Flanders, the Dutch-speaking part of Belgium. Therefore, multistage sampling was conducted. All participating schools were visited by a team of two researchers who took a test from all fourth grade students during regular class periods. The test consisted of three components: a paper-and-pencil questionnaire concerning student background characteristics, a reading comprehension test and a science achievement test. The dependent variable science achievement was measured by means of a test consisting of 34 items with a multiple choice format. The items were based on the released 2003 science items from The International Mathematics and Science Study (TIMSS). The independent variables at student level consisted of student background characteristics (namely gender, grade retention, and SES), student characteristics with regard to proficiency in the language of instruction (namely self-assessed proficiency in the language of instruction and reading achievement through a reading comprehension test) and the student characteristic of speaking another language at home than the language of instruction. With regard to the independent variables at school level, information about the general school characteristics school size and SES composition as well as the school characteristic that is related to the home language, namely the school proportion of LMi students, was obtained. The data used in this study have a clear hierarchical structure: 1,761 students (level 1) are nested within 67 schools (level 2). Therefore, the relationship of student and school level characteristics with students’ science achievement was analyzed by means of multilevel modeling based on hierarchical regression (MLwiN 2.29). First, a fully unconditional two-level null random intercepts model was tested, in which the variances at both the school level (σ2u0=6.93, χ2=26.93, df=1, p<.001) and the student level (σ2e0=17.57, χ2=843.13, df=1, p<.001) were significantly different from zero, justifying a multilevel approach over a single-level regression analysis. In consecutive steps, the student background characteristics, the student characteristics regarding the proficiency in the language of instruction, the student level characteristic with regard to the home language, the general school characteristics and the school characteristic with regard to the school proportion of LMi students were added to the model. On the basis of the deviance, the model fit for every subsequent model was determined, thereby checking the additional value of each subset of variables. Before a next subset of variables was added, the non-significant factors were deleted.

Expected Outcomes

The consecutive testing of the different models resulting in the final significant model (χ2=10.639, df=1, p<.01) showed that especially student characteristics are significantly related to science achievement. In line with previous research(3), boys tend to attain a higher performance level in science than girls, just like students from families with a higher SES(14). Although grade retention was initially negatively related to science achievement, this influence disappeared when proficiency in the language of instruction and reading performance were accounted for, which were positively associated with science achievement(15). Regarding the role of the home language in science achievement, especially LMi students seem to face a great challenge in performing high on science topics. This result illustrates the double challenge LMi students experience(10). Moreover, this study indicates that when students attend schools with a large proportion of linguistically diverse students, this can also be less advantageous for their science achievement. Although previous research indicated that school size as well as SES school composition can have an impact on student achievement, this was not confirmed in this study. This study adds to the research about what factors can have an impact on primary school students’ science achievement: it reveals the importance of taking into account students’ home language and it gives indications for school composition effects related to the school population’s linguistic diversity. As LMi students experience a great challenge in reaching a high level for science achievement, future research should look for alternatives to support them in their learning process. Although initiatives focusing on the language of instruction seem the most obvious choice, the home language can also be brought into the learning process as a scaffold(16). Especially in light of the European strategy for multilingualism(13), it should be considered to value all the languages students bring to the classroom.

References

(1)Woodgate, D., & Stanton Fraser, D. (2007). Workshop of Emerging Technologies for Inquiry-Based Learning in Science. Supplementary Proceedings of the 13th International Conference of Artificial Intelligence in Education. Retrieved from http://aied.inf.ed.ac.uk/AIED2007/InquiryBasedLearning.pdf (2)Bellens, K., & De Fraine, B. (2012). Wat werkt? Kenmerken van effectief basisonderwijs [What works? Characteristics of effective primary education]. Leuven: Acco. (3)Maerten-Rivera, J., Myers, N., Lee, O., & Penfield, R. (2010). Student and school predictors of high-stakes assessment in science. Science Education, 94, 937-962. (4)Organisation for Economic Cooperation and Development (OECD). (2007). PISA 2006 Science competencies for tomorrow’s world – Volume 1: Analysis. Paris: OECD Publications. (5)Janssen, R., & Crauwels, M. (2011). Content and student factors in mastering environmental studies – nature in primary education: evidence from a national assessment in Flanders (Belgium). Journal of Biological Education, 45(1), 20-28. (6)Von Secker, C. (2004). Science achievement in social contexts: Analysis from national assessment of educational progress. The Journal of Educational Research, 98, 67-78. (7)Wellington, J., & Osborne, J. (2001). Language and literacy in science education. Buckingham: Open University Press. (8)Van den Branden, K. (2010). Handboek taalbeleid basisonderwijs [Handbook language policy primary education]. Leuven: Acco. (9)Cummins, J. (2008). BICS and CALP: Empirical and theoretical status of the distinction. In B. Street & N.H. Hornberger (Eds.), Encyclopedia of Language and Education, 2nd Edition, Volume 2: Literacy (pp. 71-83). New York: Springer Science + Business Media LLC. (10)Goldenberg, C. (2008). Teaching English Language Learners: What the research does – and does not – say. American Educator, 32, 8-44. (11)Organisation for Economic Cooperation and Development (OECD). (2006). Where immigrant students succeed – A comparative review of performance and engagement in PISA 2003. Paris: OECD. (12)Hox, J.J. (1995). Applied multilevel analysis. Amsterdam: TT-Publikaties. (13)Council of the European Union (2008, 21 november). Council Resolution of 21 November 2008 on a European strategy for multilingualism. Official Journal C320, 16/12/2008, 0001-0003. (14)Duncan, G. J., Yeung, W. J., Brooks-Gunn, J., & Smith, J. R. (1998). How much does childhood poverty affect the life chances of children? American Sociological Review, 63, 406-423. (15)O'Reilly, T., & McNamara, D. S. (2007). The impact of science knowledge, reading skill, and reading strategy knowledge on more traditional "high-stakes" measures of high school students' science achievement. American Educational Research Journal, 44, 161-196. (16)Clark, D. B., Touchman, S., Martinez-Garza, M., Ramirez-Marin, F., & Drews, T. S. (2012). Bilingual language supports in online science inquiry environments. Computers & Education, 58, 1207-1224.

Author Information

Evelien Van Laere (presenting / submitting)
Ghent University
Educational Studies
Ghent
Ghent University, Belgium

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