Utilizing Augmented Reality to Support Internal Model Representation in Organic Chemistry

• Applicant: Professor Dr. Sebastian Habig
• Subject Area: General and Domain-Specific Teaching and Learning
• Term: from 2018 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 415026237

Handling and interpreting visualizatons is crucial for understanding scientific topics and for developing conceptional knowledge in science domains (Coll & Lajium, 2011; Harrison & Treagust, 2000; Ramadas, 2009). In the particular field of chemistry and especially its sub-domain organic chemistry a large number of different visualizations are used to illustrate molecular geometries or electron probability densities, for example.From a cognitive perspective, learners have to process visual spatial information and integrate them into their learning process when confronted with instructional visualizations. Especially for novices in a particular scientific domain this is of high cognitive demand and may lead to cognitive overload. Based on Schnotz’ (2014) integrated model of text and picture comprehension, supporting students to translate an external model into an internal mental model should have positive effects on the learning process of students, because of reduced cognitive load. Traditional two-dimensional figures are limited in their potential to visualize three-dimensional information and hence may not be the best option to visualize complex three-dimensional structures.One possibility to support students in translating external models into internal mental models is provided by the augmented reality (AR) technology. AR makes it possible to add virtual, three-dimensional objects on real-word environments (e. g. Herber, 2012). Although AR is already used in many different areas to visualize complex three-dimensional models and first AR approaches for educational fields are developed, there is little research on the effectiveness of AR-based learning environments. Referring to this research gap, this project deals with AR-based learning materials for organic chemistry at the university level and their effects on students’ cognitive and affective learning outcomes. In addition, a moderation analysis will be conducted to test conditional effects of the students’ spatial ability when learning with the mentioned material.For answering the guiding research questions of this project, two experimental studies in a pre/post design will be conducted by comparing AR-based learning material with rather traditional forms of presentation.

• DFG Programme: Research Grants
• Co-Investigators: Professor Dr. Detlev Leutner; Professor Dr. Stefan Rumann; Professor Dr. Carsten Schmuck (†)