Generative AI Student Tutorial for the Graduate School of Life Sciences University Medical Centre Utrecht Netherlands
Creators: name: Fox, Christine Merie
name: Boelen, Fleur
Publisher: name: Zenodo
Year: 2024
Subjects: subject: Generative AI
subject: E-Learning Modules
subject: Education, Graduate
subject: Life science

description: As part of our commitment to innovation in research and education, the Graduate School of Life Sciences (GSLS) at University Medical Centre Utrecht has begun integrating the use of Large Language Models (LLMs) into our educational framework. The GSLS is renowned for its interdisciplinary approach, with 16 master’s programmes and a diverse community of 1,500 master’s students. One of our goals is to foster a collaborative and dynamic learning environment that prepares students for the challenges they may face in a modern life sciences career. In line with this mission, we recognise the growing influence of LLMs in academic research and education. To ensure that our graduates and staff can effectively navigate and utilise these tools, we have developed a tutorial designed to provide both the technical knowledge and ethical framework necessary for responsible use. This tutorial, which was launched in February 2024 alongside our new Master’s Student Guidelines, aims to assist students in the ethical and responsible integration of LLMs into their work while maintaining the highest standards of academic integrity and scientific rigour. The principal focus of the tutorial is fostering a human-centred approach to LLMs. At the GSLS, we view LLMs as tools to support human abilities, not as replacements for critical thinking or ethical judgment. Our goal is to ensure AI is integrated in a way that enhances, rather than diminishes, the essential human qualities of creativity, empathy, and critical reasoning in life sciences education and research. By embracing a thoughtful and balanced approach to AI, we reflect our core values of responsible research and open science, while empowering our academic community to innovate with integrity.

Attribution:

This tutorial is part of the GSLS GenAI resources developed by Christine Fox with the valuable contribution of Fleur Boelen and ChatGPT. We encourage educators and students to adapt and use this material in their learning and teaching processes, ensuring that any adaptations or shared versions are credited back to the original creators. We thank you in advance for respecting our efforts and contributions to the field of educational technology.

We would like to thank Karin van Es, Marie-Louise Goudeau, and Davitze Könning for their constructive feedback. Additionally, we thank Laura Huiscamp, Shirrinka Goubitz, Marit de Kort, Zoë de Wit, and Harold van Rijen for their reviewing, minor editing, and feedback. Finally, we extend our gratitude to Ruud Dielen for his publishing assistance.





Tutorial Table of Contents 




1.0 Master’s Student Tutorial 




             1.1 Guidelines for the use of GenAI: Possibilities & limitations 




             1.2 Learning Goals 




             1.3 Transparency & Responsible Usage: How to disclose your use of GenAI 




2.0 Introduction to Generative AI 




             2.1 Types of AI 




             2.2 Large Language Models (LLMs) 




             2.3 Transformers: The Engine Behind LLMs 




             2.4 Tokenisation 




             2.5 Prediction, Not Common Sense 




             2.6 Tapestry of Data 





             2.7 Biases 




             2.8 The Black Box 




             2.9 Hallucinations 




             2.10 Data Sharing and Privacy 




             2.11 (E)nvironmental (S)ocial (G)overnance 




             2.12 Enhancing Education and Reasearch 




             2.13 Equity in Education 




 3.0 Crafting Effective Prompts 




             3.1 Introduction to Writing Effective Prompts 




             3.2 BRAVE(R) for Learning Assistance 




             3.3 BRAVE(R) for Image Creation 




             3.4 BRAVE(R) for Coding 




             3.5 Overloading Prompts and Factored Cognition 




             3.6 Simple Tasks 




             3.7 Reverse Prompting 




             3.8 Personalising your ChatGPT 




 4.0 Critical Evaluation 




            4.1 Evaluating and Critically Assessing GenAI Responses (FACTS) 




            4.2 Practice Activity: Critically Assessing GenAI 




 5.0 Key take-aways 




           5.1 Key take-aways 




           5.2 Free GenAI tools  




 6.0 Activity: Get Prompting 




           6.1 Activity: Test your Prompting Knowledge