CAS in Artificial Intelligence for Teachers

In recent years, schools and teachers have been confronted with the situation that AI tools are fundamentally challenging established pedagogical and didactic settings. Large Language Models (LLMs) have reached a level that enables learners and teachers to generate, correct and summarise texts and even create planning documents that are close to or sometimes even above the standard of average work results. The skillful use of common AI tools increases the efficiency of many tasks, so that today both teachers and students feel compelled to use these tools for certain tasks. The question arises: Does this accelerated work serve the main purpose of school - education - or does the use of AI in schools hinder educational processes?

The CAS AI4T course has two objectives. The first is to gain an in-depth insight into the technology of LLMs. In this part, participants create simple language models ‘from scratch’ with the aim of understanding the mechanisms of the system. In the second part of the course, the focus is on the meaningful use of existing ‘state of the art’ LLMs in a school context with the aim of fostering educational processes.

The CAS AI4T is divided into six modules and runs over 20 course days from August to January. It is aimed at teachers at baccalaureate schools and lower secondary level, lecturers in teacher training and those responsible for education, as well as anyone interested in the topic of digitalisation in education. The teaching and learning approaches are geared towards teamwork and discussion and aim to develop practical skills, whereby they are orientated towards the participants' main professional activities. The final block concludes with an individual/team project work.

Before the start of the CAS, crash courses on Python and on basic mathematical concepts for machine learning are offered at the University of Bern.

Objectives

Course competence is developed throughout six modules. Upon completion, graduates will:

• be familiar with the history and present of technological aids in pedagogy and didactics and can critically assess their influence on learners, teachers and society
• have a fundamental understanding of common self-adaptive algorithms, their design, training and evaluation
• be able to carry out basic language processing and train and use generative algorithms
• be able to use AI to plan, diagnose and evaluate learning processes in a responsible and targeted manner
• understand how bias arises, know the legal basis and the ethical and sociopolitical aspects of the use of AI in learning processes, in particular possible negative effects on learners and teachers
• be familiar with current debates and tools on the use of AI in pedagogy and didactics
• be able to critically develop, run and communicate an AI project for learning processes.

If there are free places, modules can be attended individually.

Module 1: History and Present of Technology in Teaching
In this module we review the history and present of technological aids in pedagogy to critically assess their influence on learners, teachers and society.

Module 2: Technical Foundations 1 – Machine Learning (Lead Unibe)
In this module we learn about common machine learning algorithms, how to train, fine-tune and assess them.

Module 3: Technical Foundations 2 – NLP and Generative Models (Lead Unibe)
In this module we learn common techniques for natural language processing and how to build, train, fine-tune and assess generative models.

Module 4: AI in Education 1 – Planning, Diagnostics and Assessment (Lead PHBern)
This module critically studies the use of AI algorithms for planning, diagnostics and assessment in education. Current solutions serve as exemplification and inspiration.

Module 5: AI in Education 2 – Ethical, legal and sociopolitical Aspects (Lead PHBern)
In this module we learn and discuss about ethical aspects of supporting educational processes with AI, about the legal framework that applies to the use of AI in education, and finally, about the social and professional impacts regarding the use of AI in educational processes.

Module 6: AI in Education 3 – Selected Topics (Lead PHBern)
In this module we learn and discuss about important past and present topics and tools related to AI in educational processes.

All modules
The duration of all modules corresponds to approximately 20 classroom hours each and a module work (of an expected workload 30 hours), with each complete module qualifying for 2 ECTS points. Each module has a half-day assessment that is not included in the schedule. The expected workload for the CAS final Project is 120 hours equivalent to 4CTS. The main tools and languages used are Python and libraries such as TensorFlow and PyTorch. Other tools may be used with limited support from the teaching staff. Computational resources are at disposal if necessary.

Information Events

Learn everything you need to know about the CAS AICP. One introduction is mandatory, remote participation is possible. 

Voluntary introductionary courses

Prepare yourself for the CAS Modules. We offer the following introductionary courses for free to update your knowledge.

Modules

All Information about Modules 1-6. 

Course materials are accessed via the Ilias Learning Platform. The Link to the course content will appear in the table below. 

Events and other important dates

The Certificate of Advanced Studies (CAS) in Artificial Intelligence for Teachers (AI4T) is offered by the Mathematical Institute of the University of Bern and the University of Teacher Education Bern.

Program management

• PD Dr. Sigve Haug (Director of Studies) (Unibe MAI)
• Prof. Dr. Christiane Tretter (Chair) (Unibe MAI)
• Prof. Dr. Thomas Wihler (Unibe MAI)
• Prof. Dr. Dr. Marc Eyer (PH Bern)

Lecturers

Lecturers include

• PD Dr. Sigve Haug (Unibe MAI)
• Dr. Mykhailo Vladimirov (Unibe MAI)
• Dr. Guillame Witz (Unibe MAI)
• Dr. Kinga Sipos (Unibe MAI)
• Dr. Sukanya Nath (Unibe MAI)
• Prof. Dr. Dr. Marc Eyer (PH Bern)
• Dr. Wolfgang Spahn (PH Bern)

Target groups

Aimed at students and professionals from the public and private sector who hold a degree from a university, university of teacher education or university of applied sciences (e.g. BA, BFA, MA, MFA, BSc, MSc, PhD).

Admission requirements:

• A degree from a university of arts or sciences.
• Exceptions to the admission requirements can be approved by the program management “sur Dossier”.
• Interested parties who only wish to take part in individual modules may be admitted, if places are available.

The program management decides on admission to the program. There is no entitlement to admission.

Registered participants will receive acceptance confirmation by email and will be invited to one of the next information events. Attendance to one information event is mandatory. Participants can cancel their registration free of charge up to the registration deadline. After the deadline, the regulations apply. Individual modules and electives can be attended before the registration.

Registration opens in November and a maximum of 20 registrations per year can be accepted. Applications are processed in the order of arrival. The CAS can only be offered if sufficient applications are received by the application deadline.

Deadline: 2025-08-01

Per year there are 20 places. Registrations are accepted in the order of arrival. A waiting list is maintained.

Program fees

• Regular CAS program: CHF 9’600.
• Employees & Students of University of Bern and the University of Teacher Bern: CHF 5’600.
• Payment in installments is possible.
• Inclusive of all modules, performance assessments, certificates, materials & teaching platforms, coffee breaks, full hotel pension (Module 3), full hotel pension (Module 6) and diploma reception.
• Participants must bring their own laptops.

lf places are available, modules can be attended individually. Prices are CHF 300 per half day. Individual modules are accredited with certificates that are cumulative for the full CAS AI4T.