10 Fakultät Wirtschafts- und Sozialwissenschaften

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/11

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Author: search.filters.author.Zinn, BerndSubject: search.filters.subject.370

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    Gender differences in the new interdisciplinary subject Informatik, Mathematik, Physik (IMP) - sticking with STEM?
    (2023) Bahr, Tobias; Zinn, Bernd
    The current state of research in computer science education outlines gender differences in motivation, interest, and elective subject decisions in favor of male students. This study takes an exploratory approach to examine the gender differences in the interdisciplinary STEM profile subject Informatik, Mathematik, Physik (in short: subject IMP), which combines the three subjects of computer science, mathematics, and physics. A survey was conducted involving n = 336 (m = 236, f = 88, o = 12) subject IMP students in the 10th grade attending a Gymnasium in Baden-Württemberg, Germany. The deciding factors for choosing the subject, subject interest, motivation, and more were measured using a questionnaire. Overall, the subject IMP is most chosen by male students. For those students choosing the subject IMP, no statistically significant gender differences in subject interest in IMP, mathematics, and the STEM area or in motivation and vocational orientation in natural science and engineering were found in contrast to the state of research. The interdisciplinary character of the subject IMP could be more appealing to girls than computer science by itself. We conclude that, with a higher participation rate of female students, the subject IMP could be a first step in getting more women into STEM fields.
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    Evaluation of an immersive virtual learning environment for operator training in mechanical and plant engineering using video analysis
    (2020) Pletz, Carolin; Zinn, Bernd
    A structural evaluation is imperative for developing an effective virtual learning environment. Understanding the extent to which content that has been learned virtually can be applied practically holds particular importance. A group of persons from the technical field of mechanical and plant engineering (N = 13) participated in a virtual operator training for a case application of additive manufacturing. To evaluate the virtual learning environment the participants answered quantitative questionnaires and were asked to apply what they had learned virtually to the real machine. Both the virtual training and testing phase on the real machine were recorded by video (800 minutes in total). The category system resulting from a structured qualitative video analysis with a total of 568 codes contains design‐, instruction‐ and interaction‐related optimisation potentials for further development of the virtual learning sequence. Mistakes, difficulties and other anomalies during the application on the real machine provide further revision options. The study uses video data for the first time to derive optimisation potentials and to investigate the learning transfer of virtually learned action knowledge to the real‐world activity.