Pre-Service Science Teachers' Development and Use of Multiple Levels of Representation and Written Arguments in General Chemistry Laboratory Courses


RESEARCH IN SCIENCE EDUCATION, vol.50, no.6, pp.2331-2362, 2020 (Journal Indexed in SSCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 50 Issue: 6
  • Publication Date: 2020
  • Doi Number: 10.1007/s11165-018-9781-0
  • Page Numbers: pp.2331-2362


The purpose of this study was to examine pre-service science teachers' (PSTs) development of multiple levels of representation and written arguments using an immersive approach to argument, the science writing heuristic, in general chemistry laboratory I and II courses. Fifty PSTs participated the study, 20 experiments were performed, and 976 samples were collected over two semesters. A case study design was used. The data were evaluated in three ways: the first was to examine the total number of representations used and connectedness of these representations, the second was to use analytical and holistic frameworks to evaluate PSTs' written argument, and the third was to use a Wilcoxon Signed-Rank test to compare the scores gathered from the representations and argumentation. The results showed that PSTs' holistic argument and multiple levels of representation increased over time, they showed parallel patterns, and the increasing quality of argument and use of representations were intertwined. The results also indicated that PSTs predominantly used the symbolic level of representation and used it as a mediator between the macroscopic, microscopic, and algebraic levels. The argument components of evidence and reflection appear to be critical areas in which the PSTs used more connected levels of representations, and PSTs were selective in using representations. The results of this study suggest that students should be provided with opportunities to use, generate, interpret, and reflect on these representational levels through the use of writing and negotiation activities as part of being involved in an argument-based laboratory environment.