AI training

What is it about?

In this event, we will introduce you to the topic of AI and a selection of different AI tools based on our "Prompting Station" project.
You will learn to familiarize yourself with these tools and try out possible application scenarios. Here is a brief insight into what we will be working with: Leonardo AI, Keenious, Perplexity AI and others.

It is also important to us that we continue AI training as practical as possible We would be happy to discuss questions and ideas from specific areas of work with you, with the opportunity to share these with each other. You are welcome to bring along specific questions or didactic scenarios that are of interest to you in your day-to-day teaching.

Learning objectives:

The participants

• understand the basics of AI and get to know tools such as Leonardo AI, Keenious and Perplexity AI.
• learn the basic operation and functions of the AI tools presented.
• try out application scenarios of the AI tools and work on them practically to consolidate what they have learned.
• develop solutions for didactic use
• of AI tools in their own teaching or work context.

Speaker:

• Ludwig Lorenz

Registration:

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What is it about?

This part of the AI training course introduces the possibilities of artificial intelligence (AI) in the design of formative examination formats. The focus is on how AI can help to improve formative tasks, align learning objectives and examination tasks and systematically classify the level of difficulty. Participants will analyze their own examples and develop them further in a targeted manner. The workshop combines brief input, exchange of experience and practical exercises.

Learning objectives
At the end of the event, participants can:

• Optimize exam tasks and solutions: analyze existing tasks with AI and improve them in terms of quality and accuracy of fit.
• Adapt tasks to learning objectives: Align learning objectives and examination tasks with AI support so that the examination covers the intended competencies.
• Classify tasks: Classify tasks into a suitable taxonomy and manage the cognitive challenge in a targeted manner.

Necessary prior knowledge: Basic knowledge of generative AI is required. This can be acquired in the first session of the series.

Speaker:

Uwe Cämmerer-Seibel

Registration:

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What is it about?

Artificial intelligence often appears invisible, neutral and efficient - but its use is never detached from social, political and ecological framework conditions. How sustainable and ethical is the development and use of AI?

In this workshop, you will deal with key issues relating to bias in training data, the role of invisible data workers, the power of data monopolies and the resource consumption of AI systems. The aim is to develop a critical awareness of the conditions, limits and consequences of AI-supported technologies.

Learning objectives

• Prejudices and bias

• Data Workers

• Data sovereignty and data monopolies

• Resource consumption and sustainability

• testing together

• Open discussion and questions

Necessary prior knowledge: Basic knowledge of generative AI is required. This can be acquired in the first session of the series.

Speaker:

Ludwig Lorenz

Registration:

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What is it about?

The workshop provides a practical introduction to accessibility in the university context and highlights the use of artificial intelligence to reduce barriers in studying and teaching. In addition to the preparation of teaching materials, other possible applications of AI will be considered, for example in the areas of language, access to digital content and participation. Using open source models from the eTeach model workshop, participants will also try out live how content can be made more accessible in a data protection-friendly way.

Learning objectives

• Overview of possible uses of AI to promote accessibility in the university context

• Application of open source AI models to improve the accessibility of content

• Critical evaluation of the potential and limitations of AI-supported processes

Necessary prior knowledge: Basic knowledge of generative AI is required. This can be acquired in the first session of the series.

Speakers

Ludwig Lorenz,
Salma Pethö-Zayed

Registration:

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What is it about?

This event will provide you with a comprehensive overview of the far-reaching changes brought about by the application of AI in the university context.

We shed light on the adaptation of learning content and didactics, the changing roles of teachers and students and the implications for higher education policy. We will also introduce you to support services.

After the potentials and challenges of AI in teaching are worked out, you will gain initial insights into teaching and learning methods and learn how you can use AI to contribute to the individualization of learning, for example. Ethical and social issues will also be briefly examined.

The aim of the event is to provide you with orientation in this rapid transformation process and to give you an overview of how AI can be successfully integrated into your own teaching and learning practice.

Learning objectives:

At the end of the event, participants can...

•  ...name potentials and challenges of AI in university teaching.
•  ...to find suitable offers of help with AI.
•  ...distinguish between the two dimensions of AI as learning content and AI as a didactic tool.
•  ...to summarize changes in the understanding of roles and university didactics.
•  ...explain the principles of transparency and personal responsibility and transfer them to their context with the help of an application exercise.

Necessary prior knowledge: Basic knowledge of generative AI is required. This can be acquired in the first session of the series.

Speaker:

Dr. Nicole Baron

Registration:

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What is it about?

More and more teaching projects that test, scrutinize and promote the use of generative AI in teaching are emerging at Thuringian universities.

In this special event of the KI@eTeach series, the eTeach Network Thuringia invites you to an online meeting where teachers can present current projects or ideas and explore opportunities for cooperation.

The meeting will focus on a moderated exchange of experiences on topics such as AI and university didactics, writing/citing with AI and AI as a learning buddy.

Learning objectives:

In this event, participants will...

- ... get to know other lecturers and teaching support staff who work with or support AI in university teaching.

- ... get to know practical examples of AI in university teaching.

- ... exchange best practices.

- ... get to know potential cooperation partners.

- ... get to know suitable support services for AI in teaching.

Necessary prior knowledge: In principle, no prior knowledge is required. However, in order to be able to participate in the exchange in a targeted manner, it is advisable to have your own experience with AI in teaching situations or basic knowledge of AI.

Speakers:

Martin Backhaus and
Dr. Nicole Baron

More detailed information here: AI networking meeting - eTeach Network Thuringia

Registration:

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What is it about?

What possible applications do writing tools based on generative AI - in this case on large language models - offer and how can they be used for academic writing in a meaningful and reflective way? The workshop revolves around these two questions. First, it will be shown how corresponding tools, of which ChatGPT and DeepL Write are only the best known, can be used for scientific text production and text revision. We will then show how this use can be demonstrated and documented by the students. Last but not least, we will share our experiences, questions, perspectives and concerns.

Learning objectives:

At the end of the event, participants can...

•   ... participants will have basic knowledge of the use of generative writing tools for text production and revision.

•   ... the participants know the offers for data-compliant pools that are available within the university context.

• ... the participants developed ideas on how they can integrate generative writing tools into their lessons.

•   ... participants will know how students can demonstrate and document the use of generative writing tools. 

Necessary prior knowledge: Basic knowledge of generative AI is required. This can be acquired in the first session of the series.

Speaker:

Prof. Dr. Peter Braun

Registration:

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What is it about?

In this session, you will learn how AI can serve as a transformative tool for course and lesson planning. Participants will learn about AI platforms already in use by the eTeach network and how they can streamline the course and lesson planning process.

Using practical examples and exercises, participants will explore these tools and develop their own course modules and lesson plans, including Strategies such as curriculum adaptation, writing lesson objectives, personalization, activity suggestions and planning templates integrate. They will reflect on the process and evaluate the impact of AI on their own teaching and learning context.

Learning objectives

After completing the course, participants will be able to

• Recognize AI tools that support the course and lesson planning process.
• Implement AI-based strategies to create course modules and lesson plans.
• Evaluate the benefits and challenges of integrating AI into course and lesson planning.
• explore opportunities for the further integration of AI technologies in their own teaching and learning context.

Speaker:

Larissa Barth

Registration:

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 What is it about?

This part of the AI training course offers an insight into the legal basis in the use of generative AI in university teaching.

Learning objectives:

The aim is to sensitize participants to legal grey areas and to show them legally compliant solutions for the creation and subsequent use of AI-generated content using practical application examples (ChatGPT).

Speaker:

Martin Backhaus

Registration:

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What is it about?

The event is aimed at teachers and offers a Insight into the challenges of audit law in the admission or integration of generative AI in university examinations.

Contents:

• Raising awareness of audit law principles in the context of generative AI
• Identification of legally compliant implementation options and framework conditions
• Options for labeling and documenting generative AI in tests
• Discussion Dealing with suspected cases

Learning objectives

The aim is to raise participants' awareness and impart knowledge on the legally compliant design of the audit framework for all participants.

Speaker:

Martin Backhaus

Registration:

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