While mathematical ability has long been implicated as crucial for learning chemistry, language ability remains largely uninvestigated. This contribution explores correlations between language comprehension and performance in general chemistry, as well as how general chemistry students interact with text-based learning materials. Structure Building, a model that describes how linguistic information is incorporated into one’s existing knowledge base, guides our work. We demonstrate that comprehension ability correlates strongly with chemistry course performance. An examination of variables predicted to interact by the Structure Building Framework suggests that high comprehension ability may be sufficient to compensate for low prior knowledge. We also report the design and analysis of a multiple-testing intervention strategy that differentially aids those of low comprehension ability. The effect of question type (multiple choice versus elaborative interrogation) on this multiple-quizzing strategy has also been investigated. With regard to text-based learning materials, we carried out linguistic analyses of popular general chemistry texts, the results of which suggest that these materials are appropriate for only low-knowledge students. Further studies probing the extent to which students benefit from reading texts on chemical bonding and redox concepts revealed an expertise reversal effect, corroborating these textual analyses.














Sam Pazicni (University of New Hampshire)