An interdisciplinary project seminar on data analysis using Python and machine learning
Current empirical-psychological research requires increasingly sophisticated experimental setups and multi-method research methods. The evaluation of these research results requires above all a competent handling of complex data structures such as the combination of psychometric, electrophysiological and psychophysiological data.
Review and results
The interdisciplinary project seminar for students of computer science and psychology began in the summer semester of 2023 with the aim of addressing the challenges of machine learning in psychology. To this end, the widely applicable programming language Python was taught with an application reference to a psychological question: the students investigated the relationship between music consumption behaviour and mental health. The participants learnt how to formulate their own hypotheses, collect complex data and prepare different types of data for analysis. They recorded their own music consumption behaviour and other relevant data using smartwatches. This also sensitised them to issues of data quality and the data protection-compliant and ethically sensitive handling of personal data. After evaluating the data using suitable machine learning methods, the results were visualised and reflected upon in order to present them publicly at a final event.
The students learnt the necessary basics of the Python programming language with the help of online courses and flipped classroom sessions. The data was analysed using Jupyter notebooks. This resulted in a template that could be used in the long term and adapted for the students’ own research projects.