While there is much focus on interventions to foster ethical reflection in the design process of AI, there is less focus on fostering ethical reflection for (end)users. Yet, with the rise of genAI, AI technologies are no longer confined to expert users; non-experts are widely using these technologies. In this case study in a governmental organization in the Netherlands, we investigated a bottom-up approach to foster ethical reflection on the use of genAI tools. An approach of guided experimentation, including an intervention with a serious game, allowed civil servants to experiment, to understand the technology and its associated risks. The case study demonstrates that this approach enhances the awareness of possibilities and limitations, and the ethical considerations, of genAI usage. By analyzing usage statistics, we estimated the organization’s energy consumption.
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Students often struggle with constructing models of system behaviour, particularly in open modelling tasks where there is no single correct answer. The challenge lies in providing effective support that helps students develop high quality models while maintaining their autonomy in the modelling process. This study presents a procedure for assessing the quality of student-generated qualitative models in open modelling tasks, based on three characteristics: correctness, parsimony, and completeness. The procedure was developed and refined using student-generated models from two secondary school tasks on thermoregulation and sound properties. The findings contribute to the development of automated support systems that guide students through open modelling tasks by focusing on quality characteristics rather than adherence to a predefined norm model.
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