Examining the interdependence in the growth of students' language and argument competencies in replicative and generative learning environments

Cikmaz A., Fulmer G., YAMAN F., Hand B.

JOURNAL OF RESEARCH IN SCIENCE TEACHING, vol.58, no.10, pp.1457-1488, 2021 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 58 Issue: 10
  • Publication Date: 2021
  • Doi Number: 10.1002/tea.21715
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, ASSIA, IBZ Online, Periodicals Index Online, Applied Science & Technology Source, Compendex, EBSCO Education Source, Education Abstracts, Educational research abstracts (ERA), ERIC (Education Resources Information Center), Psycinfo
  • Page Numbers: pp.1457-1488
  • Keywords: argumentation, epistemic tools, language, linear mixed-effects regression, longitudinal growth modeling, SCIENTIFIC ARGUMENTATION, SCIENCE-EDUCATION, INQUIRY, LITERACY, SENSE, REPRESENTATIONS, PERFORMANCE, COMMUNITY, IMPACT, KAPPA
  • Yozgat Bozok University Affiliated: Yes


Language and argument are epistemic tools that learners can use to help them generate and validate knowledge for themselves, as emphasized in NGSS and previous NRC reports. Not all learning environments elicit or support the use of these epistemic tools equally, thus affecting how students grow in competence in relation to their use. The present study examined growth in students' competencies in language and argument during one semester, with a comparison of two learning environments-replicative versus generative-using students' lab reports. It also examined interdependence between these growth patterns. The participants (n = 30) were simultaneously enrolled in two required introductory-level science lab courses-Chemistry-I Lab (generative) and Physics-I Lab (replicative)-taken during the first fall semester at the university. The students' written reports for each weekly lab (n = 490) were collected at the end of the semester and scored to quantify students' quality of argument (as holistic argument) and language use (as multimodal representation). This growth was modeled using linear mixed-effects regression for each competence and each environment. Quadratic modeling was also used to show whether the trend of the growth demonstrated constant increase or a leveling off. Findings provide evidence that students showed higher growth in language and argument competencies in their lab reports for the generative learning environment than in their lab reports for the replicative learning environment. The findings also suggest that there is marked interdependence between the growth patterns of the argument and language competencies. Implications are discussed for learning environments to promote language and argument development. The interdependence of argument and language growth highlights that encouraging language use in a generative manner can be a promising direction for improving argumentation and, by extension, science learning in science classrooms.