Bachelor's degree or equivalent

The aim of the course is for the participants to develop basic knowledge about generative AI and how it may affect teaching and examination in higher education today and in the future. Participants are introduced to basic concepts in generative AI, get an overview of the challenges that generative AI poses to higher education, and explore how generative AI can be applied in teaching and examination. Participants are also introduced to ethical and legal aspects related to generative AI.

After completing the course, the participant should be able to:

1. critically review the use of generative AI in higher education based on research-based perspectives and proven experience

2. discuss the legal and ethical implications that the use of generative AI entails for teaching and examination in higher education

3. apply and evaluate generative AI tools for teaching and learning in their own field of knowledge

4. discuss how generative AI may affect the future of higher education

Literature studies are followed by seminars where the course participants are given the opportunity to relate the content of the course to their own work and field of knowledge. Lectures are given and practical exercises are carried out where the themes of the course are developed.

Examination is done through assessment of two individually designed papers.

Exam 1: Paper, 4 credits. In this exam, learning outcomes 1, 2 and 4 are examined.

Exam 2: Paper, 1 credit. In this exam, intended learning outcome 3 is examined.

The grading criteria are announced by the course coordinator at the start of the course.

For all assessments, the basis must be such that individual performance can be distinguished.

Bates, Tony (2022). Teaching in a digital age: Guidelines for designing teaching and learning (Tredje upplagan). Tony Bates Associates Ltd. Kapitel 9.4. (14 pages.)

Dawson, April (2023). Artificial Intelligence and Academic Integrity. Aspen publishing. (88 pages)

Liu, Bosen Lily, Morales, Diana, Roser Chinchilla, Jaime Félix, Sabzalieva, Emma, Valentini, Arianna, Vieira do Nascimento, Daniele & Yerovi, Clarisa (2023). Harnessing the Era of Artificial Intelligence in Higher Education: A Primer for Higher Education Stakeholders. IESALC. (92 pages)

Luckin, Rosemary & Holmes, Wayne (2016). Intelligence Unleashed: An argument for AI in Education. London: UCL Knowledge Lab. (61 pages)

Roumate, Fatima (red.) (2023). Opportunities and challenges and ethics Artificial Intelligence in Higher Education and Scientific Research Future Development. Springer. (152 pages)

Sharples, Mike (2023). Towards social generative AI for education: Theory, practices and ethics. Learning: Research and Practice, 9:2, 159-167, DOI: 10.1080/23735082.2023.2261131. (8 pages)

Stahl, Bernd & Schroeder, Doris & Rodrigues, Rowena (2023). Ethics of Artificial Intelligence: Case Studies and Options for Addressing Ethical Challenges. Springer. (121 pages)

Yee, Kevin, Whittington, Kirby, Doggete, Erin & Uttich, Laurie (2023). Chat GPT Assignments to Use in your Classroom Today. FCTL Press. (145 pages)

Additional literature may be added (maximum 200 pages).

Malmö University provides students who participate in, or who have completed a course, with the opportunity to express their opinions and describe their experiences of the course by completing a course evaluation administered by the University. The University will compile and summarise the results of course evaluations. The University will also inform participants of the results and any decisions relating to measures taken in response to the course evaluations. The results will be made available to the students (HF 1:14).

If a course is no longer offered, or has undergone significant changes, the students must be offered two opportunities for re-examination based on the syllabus that applied at the time of registration, for a period of one year after the changes have been implemented. The syllabus is a translation of a Swedish source text.

If a student has a Learning support decision, the examiner has the right to provide the student with an adapted test, or to allow the student to take the exam in a different format. The syllabus is a translation of a Swedish source text.

Swedish title: Generativ AI i undervisning och examination inom högre utbildning