Introduction to Artificial Intelligence for Educators in the Natural Sciences

5 credits

Syllabus, Bachelor's level, 1FA043

A revised version of the syllabus is available.
Code
1FA043
Education cycle
First cycle
Main field(s) of study and in-depth level
Physics G2F
Grading system
Pass with distinction (5), Pass with credit (4), Pass (3), Fail (U)
Finalised by
The Faculty Board of Science and Technology, 26 February 2025
Responsible department
Department of Physics and Astronomy

Entry requirements

60 credits in science, mathematics, engineering. Proficiency in English equivalent to the Swedish upper secondary course English 6.

Learning outcomes

On completion of the course, the student should be able to:

  • explain and discuss the key historical developments of AI and its applications,
  • explain and discuss qualitatively the basic mechanisms of machine learning,
  • explain and discuss qualitatively the basic mechanisms at work in large-language models - LLMs (such as ChatGPT),
  • apply the knowledge of LLMs in educational settings and synthesize this knowledge with the knowledge in their subject domain to support learning in their subject domain,
  • identify and evaluate possible ethical and societal issues arising from AI use in education and more broadly.

Content

The course is primarily intended for pre-service and in-service teachers of natural science and technology subjects. It will introduce teachers to the topic of AI in a way that is relevant for their profession, with the purpose of increasing the teachers' AI literacy. The course is an introduction to the topic of AI for an audience without pre-existing technical knowledge of machine learning and without advanced knowledge of programming. The content of the course includes (1) an overview of AI's history and its current applications, (2) basics of machine learning, (3) a closer look at large language models (LLMs) and their functioning, (4) using LLMs effectively in the teachers' different subject domains, (5) critical thinking, societal and ethical issues related to AI use and proliferation. 

Instruction

Asynchronous independent online studies, video-conference seminars with compulsory attendance. 

Assessment

Oral/written reports of hand-in exercises and project. Active participation in online seminars. Online quizzes.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

No reading list found.

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