Research on Artificial intelligence in education (AIED), is an emerging field with a rapidly increasing number of publications after the release of ChatGPT. Two frequently studied themes in this research have been 1) The opportunities and challenges of involving AI in education, and 2) The need for educating the educators on AI and AIED. Studies on opportunities often bring up the benefits of using Generative AI (GenAI) for planning and brainstorming sessions. Regarding the challenges many studies have discussed issues in assessment and ethical aspects. This paper describes and discusses the planning and implementation of a university course on AIED at a department of education.

The research questions that the study was built around were:
1) "How could GenAI partly be used in learning and teaching activities on AIED?", and
2) "How could assignments be designed to provide fair assessment? ".

The overall approach was to use the Design science framework with the initial phases of:
1) Explicating the problem,
2) Defining the requirements,
3) Designing and developing the artefact,
4) Demonstrating the artefact, and
5) Evaluating the artefact.

The artefact in the study is the course with its syllabus, course content, activities and assignments, and the study focus has mainly been on the design and the development of the artefact. As demonstration the course has been given once during the 2024 autumn semester, with a questionnaire evaluation distributed to course participants.

Findings show that the multimodal design where GenAI not only has been part of the course as generation of textual output was appreciated. In practical concrete activities GenAI tools for music and image generation were used to get a more complete picture of opportunities and challenges with GenAI, and to illustrate the issue of so called deepfakes. Moreover, the initial module with a presentation of the AI history satisfied the students, with an overview of the AI techniques that existed before ChatGPT. However, as most student groups, this group showed a heterogeneous mix where AIED shows different opportunities and challenges for different educational contexts.

Keywords: Artificial intelligence, AI, AIED, Course design, Instructional design, Design science.