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HBO/WO

MBO

August 1, 2026

Introduction to data management as part of Open Science

Data management is part of the research cycle. It is crucial to think about it in the design phase of any experiment. This self-study module gives you hands on advice on what to do (and what NOT) with research data. It is not about (statistical) data analysis. This self-study module helps students get familiar with setting up their data management plan. As it’s an introduction to this topic, it is for students at beginner level. After completing this self-study module, you should be able to answer the following questions: What do I store? Where do I store? How can others understand what I stored? Why should I care?

Website

Susanne Kirchhoff

July 21, 2026

Introduction to Stochastic Hydrology

Hydrologic systems are both complex and extremely heterogeneous in time and space. As hydrological models are simplified versions of reality, their predictions are by definition subject to uncertainty. The field of stochastic hydrology focuses on quantifying this uncertainty along with prediction. This book aims to present an overview of the field of stochastic hydrology at an introductory level. A wide range of topics and methods will be treated, while each topic and method is only treated at a basic level: descriptive statistics; probability and random variables; hydrological statistics and extremes; random functions; time series analysis; geostatistics; forward stochastic modeling; and state prediction and Kalman filtering. The book can be used for a 10-15-week course at third-year undergraduate or first-year graduate level.

Document

Marc F.P. Bierkens

May 5, 2026

Collaboration and Personal Development

In this reader, a teaching programme (assignments, underlying models and theories) is described to develop collaborative skills in a transdisciplinary-oriented educational context in between science and society. The focus lies on creating awareness about mechamisms that promote pleasurability, effectiveness and responsibility in professional collaborative practices. The MSc course for which it was created, is called Academic Consultancy Training, taught at Wageningen University and Research

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Marjan Wink, Michel Kropman, Valentina Tassone

September 1, 2025

Economics in the Digital Age: Insights and Applications

This book serves as an essential resource for both undergraduate and graduate programs due to its comprehensive approach to digital economics: Theoretical Integration: It integrates classical economic theories with the digital economy, demonstrating how traditional principles apply to new digital realities. Practical Frameworks: It provides actionable insights for analyzing digital market trends and monetization strategies, relevant for students, managers, and business professionals alike. Case Studies and Real-World Applications offer concrete examples of digital transformations, making complex concepts more accessible and useful for research and coursework. Advanced Analytical Tools: The book helps students develop the analytical skills needed to evaluate digital business strategies, market dynamics, and the broader economic impact of digital technologies. For professionals, this book provides strategic guidance on navigating the challenges and opportunities of the digital economy. By understanding the core economic principles behind digital business models, managers can make informed decisions on everything from digital marketing to product development, all while anticipating and mitigating risks like cybersecurity threats or regulatory changes.

Open (Access) Text Book

Shilpa Samplonius-Raut

June 6, 2025

How To Write A Quantitative Research Paper

So, you need to write a ‘quantitative’ research paper, and you want to know: what is the correct way of writing such a paper? The answer is, unfortunately: it depends … For one, there is no universally accepted, ‘correct’ way of writing any paper in the social sciences in general. Moreover, even just within the so-called ‘quantitative’ research tradition specifically, there exist different viewpoints on what makes for a good research paper. To muddy things up even further, how to write a paper will also depend on the specific research question(s) that it addresses. Hence, even the same scientist might opt for varying approaches in different papers. Having said that, it is possible to identify some common rules and practices that are often followed, as well as a number of practices that should generally be avoided. Based on these common rules and practices, this document is meant to help you on your way with writing a ‘quantitative’ research paper by offering a number of tips, tricks and rules-of-thumb. None of these rules and practices are set in stone, and you (or your teacher/supervisor) may have excellent arguments to deviate from them. However, in general, following them will greatly increase the quality of your paper.

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Alex Lehr, Roderick Sluiter

June 1, 2025

Week 6: Storytelling

Around an engaging video, a lesson has been built with specific learning objectives, activities, and supporting materials for students. They learn how to harness the power of storytelling to enhance their case presentations. The instructors explain why storytelling is an essential skill for structuring and communicating insights effectively. They introduce the “Red Line” method for creating a logical flow from problem to solution and share tips for creating visually compelling presentations. Key advice includes using simple, branded slides, focusing on visuals over text, and maintaining a clear structure. This lesson will guide students in using storytelling to create presentations that are not only informative but also engaging and memorable.

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Hans van Oudheusden, Britta Stoelinga

June 1, 2025

Week 4: Creating an Implementation Plan

Around an engaging video, a lesson has been built with specific learning objectives, activities, and supporting materials for students. The focus is on a key phase in the case-solving cycle: turning strategy into action through effective implementation. The instructors introduce a six-step framework that guides students in building a clear, realistic plan to bring strategic solutions to life. From setting SMART goals and allocating resources (using the MMM framework) to creating timelines, assigning responsibilities, and assessing risks, this lesson shows how to structure implementation at different levels. Using a case example, students see how thoughtful planning ensures feasibility and alignment across business functions. By the end of the lesson, students are equipped to translate ideas into impact with a well-structured roadmap.

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Hans van Oudheusden, Britta Stoelinga

May 13, 2025

Werboek inhoudsanalyse

Werkboek Inhoudsanalyse is een praktische handleiding om te leren hoe je op een betrouwbare en verantwoordelijke manier kunt analyseren hoe mensen met elkaar communiceren. Dit boek richt zich op het ontwerpen en uitvoeren van studies die gebruik maken van kwantitatieve inhoudsanalyse als onderzoeksmethode. Deze eerste editie is ontwikkeld in het kader van de opleiding Communicatie- en Informatiewetenschappen (CIW) van Tilburg University. Binnen één semester schrijven studenten een onderzoeksvoorstel en voeren ze het voorstel vervolgens ook uit. Deze groepsopdracht is volledig uitgewerkt in de bijlagen van het boek.

Open (Access) Text Book

Emiel van Miltenburg

January 1, 2025

A very short introduction to R

Being able to use a programming environment such as R is a valuable skill for our students. R provides opportunities for using larger and more complex datasets in practicals, case studies and theses. Compared to other programming languages, it is relatively easy to learn, which makes it suitable for education. Because R is open access, graduates can keep using it when they can no longer use the university’s software licences. “A (very) short introduction to R” teaches the basics in 1-2 hours with explanations and short exercises. This tutorial is used by lecturers worldwide. We expanded this tutorial to a series of self-study modules of 1-2 hours each. The modules can be used by: Lecturers who would like to use R in their computer practicals, but are afraid that learning R will consume time from the course content. The self-study modules enable these lecturers to use R with little time investment, since they can simply assign students to do (some of) the modules as preparation for their own computer practical. Students who lag behind in programming skills. The background of students in courses becomes increasingly diverse, which sometimes leads to discontent between advanced and less advanced students. With these modules the less advanced students can mend their deficits independently before they come to class, thereby levelling the differences between students and improving the learning experience of all. Students who are writing their BSc, MSc or PhD thesis. Without programming skills, students often fall back on Excel for processing and analysing data (which is often not suitable for the task) and their supervisors spend much time teaching them how to deal with the data. With the self-study modules, the supervisor’s time can be used more effectively to interact with the student about the scientific question to be tackled. Researchers and professionals who want to start using R. The modules are short and free of charge, which lowers the threshold for beginners.

Website

Claudia Brauer

September 1, 2024

Critical AI Literacy e-learning course

Update May 12, 2025: The Critical AI module has been faithfully remade in Wikiwijs to be openly available to those who cannot access the University of Groningen's Brightspace. The form is identical to the Brightspace version, and as such can be used as an example for those looking to remake the module in their own online learning environment/LMS. The Wikiwijs module can be found by following the link. This is a collection of relevant files for the first version of the University of Groningen's Critical Ai Literacy e-learning course. This e-learning course was implemented in the university's LMS Brightspace, and is aimed at both students and teachers who want learn more about the fundamentals of Text-based Generative AI models such as ChatGPT. The course tackles five topics: What is AI? How do you Generative AI models work? What are the limitations of Generative AI models? What ethical implications are associated with Generative AI models? What are some applications and considerations for using Generative AI models. Each section tries to explain its content in relatively simple terms, so that anyone regardless of educational background can gain a working understanding of Generative AI Models. Consequently, some of the information may be heavily simplified or does not fully extent to the finer details of AI technologies. As a simple introduction to Generative AI models, this e-learning can be followed on its own, or it can be implemented in other courses focusing on topics such as Academic Skills or Information Literacy. There are three kinds of files available: Word documents that have all the texts and images for each section (5 sections, each tackling one of the topics, an introduction section, and a references and future readings section), video files for introductory videos as well as supplemental animations (the word documents refer to these videos), and powerpoints that are the basis for the animations. For reuse, we recommend using these files to build the e-learning in your institution's own e-learning platform or LMS.

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Lilian Tabois, Alicia Streppel, Rob Nijenkamp, Martijn Blikmans-Middel, Yvonne de Jong