The course aims to strengthen the role of the teacher in higher education in light of the ongoing technological developments surrounding generative AI and related technologies. These developments will influence how higher education can be meaningfully conducted. The main themes of the course are:

• An introduction to and basic technical overview of generative AI, from a higher education pedagogy and ethical perspective

• AI literacy: the ability to create, evaluate, and improve learning materials generated by generative AI tools

• Learning with and from AI – how AI can be used to promote learning

• Assessment and examination in relation to generative AI

The course aims to provide teachers with a research-informed, practical, and ethically grounded understanding of generative AI in higher education. Participants develop AI literacy (the ability to create, evaluate, and improve AI-generated material) and learn how to design learning activities and assessments for an anticipated future in which generative AI is widely available.

After completing the course, participants should be able to:

1. discuss and critically examine the use of generative AI tools to support student learning within their own subject area, drawing on educational research and/or subject didactics

2. reflect on pedagogical advantages and disadvantages, as well as the risks and opportunities associated with generative AI in higher education, and use generative AI tools to develop learning resources within their own subject area

3. relate to legislation and guidelines, and reflect on ethical aspects of their own use of AI when designing and implementing teaching activities that involve AI tools

4. discuss and critically examine the use of generative AI tools in the design and implementation of assessment and examination within their own subject area

The pedagogical approach emphasized in this course is based on the concepts of establishing and sustaining a collegial community around generative AI in education. We, the teachers, see ourselves as your guides and facilitators in our joint journey towards gaining further insights in how to deal with this new technology and what it will entail in the future. We therefore look forward to engaging with you in this inquiry process. We will provide activities, materials, etc. as a point of departure for us to build upon together in collegial discussions.

In turn, to be successful in the course it is important that you as a participant take responsibility for your own involvement with the course. For example, make sure that you actually have time to participate in the course, direct your own learning, and engage with the content, us teachers and your peers.

The course consists of four parts:
Part 1: Generative AI as your course assistant in course development.
Part 2: Fair and ethical use, and students' learning 
Part 3: Assessment validity under generative AI
Part 4: Responding to future AI tools? 

For each part there is one seminar and one assignment, which are mandatory to pass the course. The exception is part 4 where the assignment is optional and followed up by an optional seminar. The assignment for each part is to be handed in before the seminar, where we have activities where we follow up on the result of your assignments.

The course is 3.0 ECTS credits. This corresponds to 10 working days in total and gives an average of 2.5 working days per module. The course design has been done with the intention to keep your workload as even as possible. That said, depending on your previous experiences, some parts of the course might be easier achievable than others. It is advised that you, as a participant, book time in your own calendar of 2 days per part to have enough time to read/view the material and complete the assignments.

The course literature consists of research papers, book chapters, webpages, and videos. Everything is digital and available either through Canvas, as open access, or thru the KTH library subscription. For each part of the course, the material is listed in Canvas as either mandatory or optional. The course literature for each part can be updated until the module starts.

A computer with internet access of high quality, along with a webcam and headset is needed for the online meetings in the course. 

To participate in the course, you need to ensure that you have access to a text-based generative AI, a so-called AI chatbot. There are many different AI chatbots available online that you can use directly in your web browser. For example, ChatGPT, Claude, or Gemini work well for the course content and structure.

KTH provides Microsoft copilot to faculty, more info here.

Students at KTH with a permanent disability can get support during studies from Funka:

Funka - compensatory support for students with disabilities

• LEXA - Continuous assessment, 2.0 credits, grading scale: P, F
• SEM1 - Seminars, 1.0 credits, grading scale: P, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability. The examiner may apply another examination format when re-examining individual students. If the course is discontinued, students may request to be examined during the following two academic years.

LEXA - Continuous assessment, 2.0 credits

Consists of three assignments. All assignments need to be passed in order to pass PROA.

SEM1 - Seminars, 1.0 credits

Consists of active participation in the non-optional course seminars. 

• All members of a group are responsible for the group's work.
• In any assessment, every student shall honestly disclose any help received and sources used.
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.