David Johannes Hauck ¹ Andreas Steffen ^2* Insa Melle ^1*

• ¹ Faculty of Chemistry and Chemical Biology, Chair of Chemistry Education, Technical University Dortmund, Dortmund, Germany
• ² Faculty of Chemistry and Chemical Biology, Chair of Inorganic Chemistry, Technical University Dortmund, Dortmund, Germany

During the COVID-19 pandemic, digital video conferencing formats temporarily became the new norm at universities. Due to social distancing, these environments were often the only way for students to work together. In the present study, we investigated how first-semester chemistry students dealt with new, challenging content, i. e., quantum theories of chemical bonding such as molecular orbital (MO) theory, in such an unfamiliar collaboration environment. Studies in the field of Computer-Supported Collaborative Learning (CSCL) suggest that small groups working on complex tasks are particularly effective when students actively build on the ideas and reasoning of their peers, i.e., when they engage in transactive talk and when they structure their work on a metacognitive level by following typical problem-solving patterns. To operationalize these constructs, we developed a coding manual through quantitative content analysis, that we used to analyze a total of N = 77 students working together in 21 small groups on two consecutive tasks: the creation of glossaries and the construction of concept maps on MO theory. Our manual showed very good characteristics in terms of internal consistency and intercoder reliability. Based on the data obtained, it was possible to not only describe the student's transactive communication and problem-solving activities, but to correlate it with other variables such as knowledge development in MO theory, which allowed us to compare the two different collaborative phases as well as different treatment groups. Students showed a higher proportion of transactivity and problem-solving activities when constructing the concept maps than when creating glossaries. In terms of knowledge gains, a multiple linear regression analysis revealed that students in groups that derived consequences from their collaborative work showed greater improvements than students who did not, although the students' prior knowledge remained the most influential factor. As for the different treatments, our data did not reveal any noticeable difference when students from a small group worked with either complementary or identical material before collaboration, neither in terms of transactive talk nor problem-solving patterns. All in all, we were able to develop and test a powerful tool to quantify transactive communication and problem-solving activities in a collaborative context.