# Teaching

Canonical page: https://dominiklukes.net/teaching

Courses and workshops on AI, learning technology and language teaching, and a set of hands-on activities that anyone can run.

## Courses and workshops

- [Exploring the relationship of AI and human intelligence](https://dominiklukes.net/teaching/ai-history-workshops): AI Exploration Week, Oxford, 6-10 July 2026, 4 sessions, The Walter Room, Kellogg College.
- [AI for Research(ers): Principles, Context, and Tools](https://semanticmachines.fyi/workshops/ai-for-researchers-workshop): A hands-on workshop designed to move researchers from basic principles to practical application of Large Language Models. This session covers the cognitive baseline of LLMs, the nuances of context management, and the creation of custom research tools.
- [Vibecoding for Language Teachers: Making apps for language learning with AI](https://dominiklukes.net/speaking/vibecoding-language-teachers): AULC 2026, Rewley House · Oxford · 9 January 2026.

## Hands-on activities

- [Building a Simple App](https://semanticmachines.fyi/activities/act-building-app): Define the tool.
- [Cognitive Baseline: Calibrating your Mental Model](https://semanticmachines.fyi/activities/cognitive-baseline): Test the model's ability to generate text and then critique its own output.
- [Comparing Model Knowledge](https://semanticmachines.fyi/activities/act-model-knowledge): Test Gemini tiers.
- [Context & Retrieval: Handling Information](https://semanticmachines.fyi/activities/context-retrieval-activity): Test retrieval accuracy with a large document.
- [Data Analysis with Code Execution](https://semanticmachines.fyi/activities/act-data-analysis): Create a dataset.
- [Deep Research: Comparing 5 Leading Tools](https://semanticmachines.fyi/activities/deep-research): Understanding the shift from conversational AI to agentic research.
- [Developing a vocabulary for thinking about AI](https://semanticmachines.fyi/activities/vocab-thinking): Foundational Concepts LLM (Large Language Model) Outputs of Neural Networks trained on extremely large amounts of data to understand and generate human-like text.
- [Exploring image and multimedia generation](https://semanticmachines.fyi/activities/image-generation): The Challenge Most LLMs do not generate images directly; they call other models.
- [Exploring Model Performance with MPI Explorer](https://semanticmachines.fyi/activities/act-mpi-explorer): Access the MPI Explorer tool.
- [Exploring Small/Local Models](https://semanticmachines.fyi/activities/act-small-models): Open comparison interface.
- [Literature Search Comparison](https://semanticmachines.fyi/activities/act-lit-search-comparison): Select a query.
- [Long Context Window](https://semanticmachines.fyi/activities/act-long-context): Fill the context window.
- [Multimodal Conversation](https://semanticmachines.fyi/activities/act-multimodal): Provide visual context.
- [Reflections on academic writing in the age of LLMs](https://semanticmachines.fyi/activities/academic-writing): Why we need reflection To stop assuming answers are obvious and investigate gaps in knowledge regarding AI in academia.
- [Search Grounding](https://semanticmachines.fyi/activities/act-search-grounding): Test cutoff date.
- [Specialized Research Tools](https://semanticmachines.fyi/activities/act-specialized-tools): Use a specialized tool.
- [Testing Reasoning Capabilities](https://semanticmachines.fyi/activities/act-reasoning): Prepare a complex query.
- [Testing the Semantic Baseline](https://semanticmachines.fyi/activities/act-semantic-baseline): We will be using Google AI Studio
- [Tool Use: Counting & Math](https://semanticmachines.fyi/activities/act-tool-use-math): Demonstrate the limitation.
- [Visualizing Context](https://semanticmachines.fyi/activities/act-visualizing-context): Access the visualization tool.