Dissertation project Thomas Dickmann

Predictors of visual model comprehension in chemistry

This project deals with the question, how visual model comprehension can explain academic success in degree courses and it is part of the large ALSTER-project (academic learning and study success in the entry phase of science and technology study programs). Within this research group it is attempted to analyse the high dropout rates in STEM courses. The research group focusses on the following two questions: Which requirements does the university course put on the students and which qualifications do the students hold during their studies? At this point my project is embedded.
In research it is consensus that model comprehension in chemistry is a crucial component for learning. This is confirmed by the use of diverse models in chemistry textbooks. At the same time the frequent use of visual models raises the question how visual models can support learning. There are three basic models, the cognitive load theory (Sweller, van Merrienboër & Paas), the integrated model of text-picture comprehension (Schnotz, 2005) and the cognitive theory of multimedia learning (Mayer, 2009). Every single model underlines (emphasizes) that the instructional design of learning material and the individual learner qualifications are important to conceptual thinking and learning.
Because of these considerations visual model comprehension is investigated. On the one hand we focus on the visualizations (iconic vs. symbolic) and on the other hand on the individual qualifications (prior knowledge, visual-spatial thinking, etc.). First, a research gap is closed by analyzing textbooks. We examine, which types of visualization and in which number visualizations are used in textbooks.
Second, the focus is on the students and their use of visualizations. The project is a longitudinal study, in which first year students are tested before the start of the chemistry degree course (10/2016), half a year into the course (02/2017) and at the end of their first year (07/2017).
Focusing on the visual model comprehension makes it necessary to develop a test, which queries this ability. This developed visual model comprehension test is used at all three points of measurement. Thus, the items of the test do not change. Further individual qualifications and ability data is collected by other associated projects allowing the visual model comprehension to be embedded in a broader model.