A Meta-Analysis of Linguistic Modifications in Science Texts Aimed at Increasing Comprehension (Poster 1)

• In Event: AERA Poster Session Eight
  In Poster Session: Literacy Poster Session Three

Abstract

Texts are a central component of Science, Technology, Engineering and Mathematics (STEM) education (van den Broek, 2010). Texts in STEM domains are often difficult to comprehend (Best et al., 2005). Among other factors, text comprehension is influenced by linguistic features of the text (McNamara & Magliano, 2009) and STEM texts include many challenging linguistic features (Best et al., 2005). Previous research modified lingusitic features of STEM texts and investigated effects on learning outcomes. However results are somewhat inconclusive. We adressed this by conducting a meta-analysis. By simultaniously including several linguistic modifications in a meta-regressional approach, we were able to isolate the unique contributions of each modification. An overall effect could be found, meanwhile not all modifications added up to it.

Authors

• Hendrik Härtig, University of Duisburg-Essen
  Presenting Author

• Anselm Robert Strohmaier, Technical University of Munich
  Non-Presenting Author

• Dominik Leiss, Leuphana University - Lueneburg
  Non-Presenting Author

• Timo Ehmke, Leuphana University - Lueneburg
  Non-Presenting Author