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Self-regulated learning to improve teaching in computer science

A new FAIR project in collaboration with Thomas Zeuma from RUB is investigating formal courses in computer science to improve course quality. Thanks to the successful acquisition of third-party funding from the RC Trust, we are able to carry out the planned data collection and develop targeted interventions to increase learning success.

The aim of FAIR's university intervention research is to improve university teaching. A new FAIR project in collaboration with Thomas Zeuma from the RUB is investigating formal courses in computer science. In order to drive this project forward and improve the quality of the courses, we have successfully acquired third-party funding from the RC Trust (https://rc-trust.ai). As a Research Center for Trusted Data Science and Security, the RC Trust is dedicated to the trustworthiness of intelligent systems in safety-critical applications. The unique, human-centered research approach includes interdisciplinary studies on trustworthy data analysis, explainable machine learning and privacy-oriented algorithms.

With the funds raised amounting to EUR 10,000, we can successfully carry out the planned data collection and pay the test subjects an appropriate salary. In addition, we will be able to finance two positions for student assistants (WHK) for a period of six months.

We are very pleased about the financial support from the RC Trust, which enables us to expand and consolidate intervention research in FAIR. Through targeted data collection and the insights gained from this, we can develop targeted interventions to further increase student learning and satisfaction.

The success of this project is an important step towards further developing teaching in Computer Science and providing our students with optimal learning opportunities. We would like to thank the RC Trust for their support and all those involved who contributed to the acquisition of third-party funding.