Current Focus

Dominik focuses on exploring the role of artificial intelligence tools within academic practice. He provides training and consultancy on navigating the current AI landscape with special focus on using generative AI tools in research.

Background and Research

Dominik has been involved in computational linguistics and natural language processing since the 1990s. His academic interests are in linguistics, language education, metaphor, and discourse analysis. He has published in academic journals, edited academic volumes and translated both academic and non-academic texts between Czech and English.

Previously, he worked as the Education and Technology Specialist for Dyslexia Action where he designed and ran a MOOC on Inclusive Technologies for Reading. He has also worked as a language and culture training advisor for the US Peace Corps in over 15 countries.

At Oxford, he started as Learning Technologist at Saïd Business School (2017-2021), then became Assistive Technology Officer at the Centre for Teaching and Learning (2021-2024). In 2021, he founded the Reading and Writing Innovation Lab, which explored academic reading and writing in the digital context and developed resources to support accessible documents.

Current Work

He is the author of the Oxford report "Beyond ChatGPT: State of AI in Education 2023" and created an AI Task Evaluation framework to help people understand how to use AI tools in schools and universities. He publishes the AI in Academic Practice Newsletter on LinkedIn and speaks at conferences about AI in education.

Dominik is a founding member of the AI Thought Exchange, an international group of scholars exploring the impact of generative AI on higher education. He also advises on education and AI as a member of the Higher Education Editorial Advisory Board for McGraw Hill and the Bett UK Advisory Board.

Areas of Consultation

Staff and departments can consult Dominik on:

AI Implementation Strategy: Evaluating and deploying generative AI tools for research, teaching, and administrative workflows while ensuring appropriate security and ethical considerations.

Large Language Model Applications: Understanding capabilities and limitations of LLMs for text analysis, content generation, and semantic processing in academic contexts.

Digital Scholarship Methods: Integrating AI tools into humanities and social sciences research methodologies, including corpus analysis and text processing techniques.

AI Literacy Development: Designing training programmes and frameworks to build institutional capacity for responsible AI adoption across diverse academic disciplines.

Academic Productivity Technologies: Optimizing digital workflows for reading, writing, and research tasks using AI-enhanced tools and platforms.

Assessment and Evaluation Frameworks: Developing methodologies to evaluate AI tool effectiveness and measure impact on academic practice and learning outcomes.