Session Information
31 SES 07 B, Linguistic Aspects of Subject Learning
Paper Session
Contribution
This presentation is based on parts of a larger study of language use, where each sub-study is investigating different aspects of language use in the Swedish version of TIMSS 2011. A prominent aspect of a subject specific language is the vocabulary, and this presentation concerns differences between vocabularies used in TIMSS science questions in the subjects biology, chemistry, earth science and physics.
When assessing students’ knowledge through written tests, it is important to know whether a student’s incorrect response is caused by a lack of knowledge or a misunderstanding of the question itself. Student related issues such as misinterpretations, linguistic inadequacy (e.g. poor reading skills or lack of vocabulary), unconscious adding or omissions of words can cause incorrect responses. Item related issues can be that the question is too linguistically complex for the students level, is ambiguously formulated, or typographically, grammatically or semantically erroneous allowing for other interpretations than the intended (Clerk & Rutherford, 2000; Harlow & Jones, 2004). When using international tests, inadequate translations also open for other interpretations. Translated items can be unintentionally altered, due to linguistic differences between languages and cultural influences on interpretations of words (Oakland & Lane, 2004).
Claims have been made that science could not function without its specialized terms (Wellington & Osborne, 2001), but scientific texts with a high ratios of technical terms can be difficult to understand for students (Fang & Schleppegrell, 2008). The vast majority of technical terms in science is nouns, but can also occur when describing objects or processes with more unusual adjectives or verbs that are linked to unique activities, although technical verbs are both rare and seldom used (Martin, 1993). Swedish science textbooks have a lot of content specific technical vocabulary, thus distinguishing them from the language used in social science textbooks, which have a vocabulary similar to the colloquial language found in newspapers and novels (Ribeck, 2015). Studying Swedish school textbook excerpts from science, social science and Swedish language, Edling (2006) found that science texts contained more abstract and generalizing nouns and less concrete nouns than the other subjects and also that the student encounters higher levels of abstraction and generalizations in all subjects as the student moves through the school system.
A characteristic of scientific vocabulary is abstraction, mainly achieved by nominalizations; the changing of verbs or adjectives into nouns (Fang & Schleppegrell, 2008). However, scientific texts in Scandinavian languages more often use compound words instead of nominalizations than corresponding English texts (Ekvall, 2011). Although the main words are easily recognized in Swedish compound words (Holmegaard, 2007), low frequent compound words might be an additional complication for Swedish students. Investigating students understanding of Swedish extra-long words (>13 letters) from the social sciences, it was found that the extra-long words -often nouns requiring a sociocultural understanding- was difficult to understand for students (Holmegaard, 2007).
The aim of this study is to investigate the vocabulary used in subject separated science items from the Swedish version of TIMSS 2011, with a focus on the low frequency words, as they are a significant limiting factor in text comprehension (Graesser, et al., 2011). The research questions are:
- How does the language used in TIMSS 2011 science items correspond with the language used in Swedish school textbooks?
- How are the low-frequency words used in TIMSS 2011 distributed, in terms of parts of speech, nominalisations and made up-, extra-long- and compound words?
- How are the low-frequency nouns used in TIMSS 2011 distributed, when described in terms of being abstract, generalizing or concrete?
- Are there differences between the scientific subjects in TIMSS 2011 regarding how they use different categories of low frequency words?
Method
Expected Outcomes
References
Clerk, D. & Rutherford, M. (2000). Language as a Confounding Variable in the Diagnosis of Misconceptions. In International Journal of Science Education, 22, pp.703-17. Edling, Agnes (2006). Abstraction and authority in textbooks. Studia Linguistica Upsaliensia 2. Acta Universitatis Upsaliensis. Ekvall, U. (2011). Enhetligt på den finska sidan men varierat på den svenska. Om kemiböcker i svenska och finlandssvenska klassrum. In I. Eriksson (Ed.). Kemiundervisning och textbruk i finlandssvenska och svenska skolor – en komparativ tvärvetenskaplig studie. Stockholm: Stockholms Universitets förlag. Fang, Zhihui & Schleppegrell Mary J. (2008). Reading in secondary content areas: A language-based pedagogy. Ann Arbor: University of Michigan Press. Graesser, A. C., McNamara, D. S. & Kulikowich, J. M. (2011). Coh-Metrix: Providing Multilevel Analyses of Text Characteristics. In Educational Researcher, 40, pp.223-234. Harlow, A. & Jones, A. (2004). Why Students Answer TIMSS Science Test Items the Way They Do. In Research in Science Education, 34, pp.221-238. Heimann Mühlenbock, K. (2013). I see what you mean: assessing readability for specific target groups. Data linguistica. 24, Institutionen för svenska språket, Göteborgs universitet. Holmegaard, Margareta (2007). Långa ord - en svårighet för flerspråkiga studerande? In Lindberg, I. & Johansson Kokkinakis, S. (Eds). OrdiL: en korpusbaserad kartläggning av ordförrådet i läromedel för grundskolans senare år. Institutet för svenska som andraspråk, Göteborgs universitet. Johansson Kokkinakis, Sofie (2007). Språkteknologiskt arbete i OrdiL-projektet. In Lindberg, I. & Johansson Kokkinakis, S. (Eds). OrdiL: en korpusbaserad kartläggning av ordförrådet i läromedel för grundskolans senare år. Institutet för svenska som andraspråk, Göteborgs universitet. Kanebrant, E., Heimann Mühlenbock, K., Johansson Kokkinakis, S., Jönsson, A., Liberg, C., af Geijerstam, Å., Folkeryd, J. & Falkenjack, J. (2015). T-MASTER A tool for assessing students' reading abilities. In Proceedings of the 7th International Conference on Computer Supported Education. http://dx.doi.org/10.13140/RG.2.1.1135.0241 (17-12-2015) Martin, J.R. (1993). Technicality and Abstraction: Language for the Creation of Specialized Texts. In M. A. K. Halliday & J. R. Martin. Writing science: literacy and discursive power, Falmer, London. Oakland, T. & Lane, H. B. (2004). Language, Reading, and Readability Formulas: Implications for Developing and Adapting Tests. In International Journal of Testing, 4, pp.239-252. Ribeck, Judy (2015). Steg för steg. Data linguistica. 28, Institutionen för svenska språket, Göteborgs universitet. Stockholm University (2014). SUC, Stockholm-Umeå corpus. http://www.ling.su.se/english/nlp/corpora-and-resources/suc/stockholm-ume%C3%A5-corpus-suc-1.14045 (17-12-2015) SAOL (2006). http://www.svenskaakademien.se/svenska-spraket/svenska-akademiens-ordlista-saol/saol-13-pa-natet/sok-i-ordlistan (17-12-2015) Wellington, J. & Osborne, J. (2001). Language and literacy in science education, Buckingham, Open University Press.
Search the ECER Programme
- Search for keywords and phrases in "Text Search"
- Restrict in which part of the abstracts to search in "Where to search"
- Search for authors and in the respective field.
- For planning your conference attendance you may want to use the conference app, which will be issued some weeks before the conference
- If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.