AI for non-programmers: Applied AI in the lectures for students without programming skills
<|reference_start|>AI for non-programmers: Applied AI in the lectures for students without programming skills: Applications such as ChatGPT and WOMBO Dream make it easy to inspire students without programming knowledge to use artificial intelligence (AI). Therefore, given the increasing importance of AI in all disciplines, innovative strategies are needed to educate students in AI without programming knowledge so that AI can be integrated into their study modules as a future skill. This work presents a didactic planning script for applied AI. The didactic planning script is based on the AI application pipeline and links AI concepts with study-relevant topics. These linkages open up a new solution space and promote students' interest in and understanding of the potentials and risks of AI. An example lecture series for master students in energy management shows how AI can be seamlessly integrated into discipline-specific lectures. To this end, the planning script for applied AI is adapted to fit the study programs' topic. This specific teaching scenario enables students to solve a discipline-specific task step by step using the AI application pipeline. Thus, the application of the didactic planning script for applied AI shows the practical implementation of the theoretical concepts of AI. In addition, a checklist is presented that can be used to assess whether AI can be used in the discipline-specific lecture. AI as a future skill must be learned by students based on use cases that are relevant to the course of studies. For this reason, AI education should fit seamlessly into various curricula, even if the students do not have a programming background due to their field of study.<|reference_end|>
@article{schöning2024ai,
    title={AI for non-programmers: Applied AI in the lectures for students without
  programming skills},
    author={Julius Sch"oning and Tim Wawer and Kai-Michael Griese},
    journal={Voneinander Lehren lernen (5) (2024)},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.05547},
    primaryClass={cs.CY cs.AI cs.LG}
}