Quest-Career-COVID-19: Designing, implementing, & analyzing online questionnaires on career

In the winter semester 2021, we organize a blended hands-on course. Students learn the basics of how to (1) design, (2) implement, and (3) analyze new online questionnaires. These new questionnaires assess the career development of healthcare professionals during the COVID-19 pandemic. Activity 1 “design:” Students and lecturers design a new questionnaire aimed at assessing how other students estimate their career development in general and during/after the COVID-19 pandemic. Both PIs in Heidelberg have expertise with questionnaires about career development (FB) and the COVID-19 pandemic (CK). Students adapt existing qualitative questionnaires into a quantitative questionnaire. Students translate the questionnaire into their respective languages and adapt it for organizational particularities of their countries. Educational outcome: Learning to design empirical experiments that answer scientific questions. Activity 2 “implementation:” Students and lecturers (a) implement the questionnaire into online platforms (soscisurvey, limesurvey; PIs and partners have experience with these platforms), (b) identify online platforms and associations for recruiting participants. Outcome: Experience with online data acquisition and research in education. Activity 3 “analysis:” Students and lecturers analyze previously acquired data (i.e., data preprocessing, calculating statistical measures such as averages, standard deviations, regressions, robustness checks, testing for differences between countries, etc). Outcome: Learning to use statistical software (R, Python). Reasons for sustainability: First, the project can be easily adapted for new questionnaires and complex online experiments including “gamification.” Second, varying the complexity of the questionnaire allows adaptation for BA, MA, and PhD students. Third, lecturers from all sites and from different disciplines can contribute their scientific expertise—and use the collected data for their own research, which may enhance long-term motivation for cooperation. In the summer semester 2022, we organize a blended hands-on course, which students and lecturers from Paris and Milan attend in person. The general outline and the activities are very similar to the procedure for the winter semester detailed above. The crucial novelty is that we broaden the topic to the wider field of “computational psychiatry” with a specific focus on reinforcement learning models regarding social learning.