2024-03-20, Jeitziner, Loris Tizian, Paneth, Lisa, Rack, Oliver, Zahn, Carmen, Wulff, Dirk

Collaborative group engagement is a key factor of success in learning groups. This work explores the development of an innovative natural language processing method for predicting collaborative group engagement. To this end, we identified linguistic markers based on an established observation-based scheme for rating collaborative group engagement, such as, semantic similarity to task instructions, verbal mimicry, sentiment, and use of jargon. We evaluated the predictive power of the linguistic markers on the data of an observational study in which 38 learning groups were instructed to perform a collaborative learning task. Overall, the data consisted of 2588 expert ratings on collaborative group engagement. We relied on machine learning to the predict collaborative group engagement ratings using informative subsets of linguistic markers. The results showed above-baseline predictive accuracy for all four dimensions of collaborative group engagement. Moreover, the analysis of feature importance points to quantity of utterances, responsiveness and uniformity of participation as the most important markers for collaborative group engagement. By harnessing natural language processing, this work extends traditional qualitative analysis and delivers nuanced quantitative metrics suitable for capturing the complexity and dynamics of contemporary Computer Supported Collaborative Learning (CSCL) environments. Thereby, it contributes to the evolving landscape of CSCL research and demonstrates the potential of novel analytic techniques to support and enrich qualitative analysis in multiple domains.

2023-06, Roos, Anna-Lena, Jeitziner, Loris Tizian, Zahn, Carmen

2022-07-22, Rack, Oliver, Paneth, Lisa, Jeitziner, Loris Tizian, Zahn, Carmen

In an explorative field study, we investigated nonverbal behavior and collaborative group engagement (QCGE) in online learning groups. Participants in small groups performed a hidden profile task. Results suggests differences within and between groups in their nonverbal behavior. We expect that nonverbal behaviors relate to QCGE in online learning groups.

2023-12-31, Jeitziner, Loris Tizian, Frick, Andrea, Paneth, Lisa, Zahn, Carmen

2022-11-17, Schwaninger, Adrian, Sterchi, Yanik, Wäfler, Toni, Renggli, Philipp, Rack, Oliver, Bleisch, Susanne, Paneth, Lisa, Jeitziner, Loris Tizian, Gasparik, Matus, Zahn, Carmen

2022-06, Jeitziner, Loris Tizian, Roos, Anna-Lena, Ruf, Alessia, Zahn, Carmen

The pandemic has forced higher education to shift from onsite to online environments. This novel situation may increase students’ exam stress and induce new stressors. In the present study, we identified stressors in online exams by conducting an exploratory factor analysis of a novel questionnaire. The analysis revealed five factors that categorize students’ experience of stress. Preliminary descriptive results suggest that possible system failures and social pressures cause the highest stress for students.

2023-06, Roos, Anna-Lena, Jeitziner, Loris Tizian, Bäuerlein, Kerstin, Mahler, Sara, Ruf, Alessia

2022-11-08, Roos, Anna-Lena, Jeitziner, Loris Tizian

Synchron hybride Lernszenarien, bei denen ein Teil der Teilnehmenden vor Ort anwesend ist und gleichzeitig andere Teilnehmende online zugeschaltet sind, ermöglichen mehr Flexibilität und Anpassung an individuelle Lebenssituationen und können somit einen grossen Mehrwert für Lernende bieten. Dies gilt auch für virtuelle Lernräume, im Sinne kollaborativ nutzbarer 3D-Umgebungen. Damit hybride und virtuelle Lernszenarien erfolgreich sind, müssen sie jedoch methodisch-didaktisch und technisch sinnvoll geplant, vorbereitet und umgesetzt werden. Dr. Anna-Lena Roos und Loris Jeitziner geben in dieser Veranstaltung Einblicke in Ihre Erfahrungen bei der Konzeption und Umsetzung solcher Szenarien.