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HBO/WO

MBO

1 augustus 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

14 juli 2026

Overzicht Case 2 CARAI

Intro Case 2

Presentatie

Marcel Schmitz

13 juli 2026

Workshop Recognition and Rewards

The interactive workshop Recognition and Rewards focuses on the impact of recognition and rewards on the choices made within research regarding Open Science principles. It is notable that, in the current system, Open Science-related tasks receive less recognition and appreciation than 'traditional' research tasks. The workshop demonstrates how the societal impact of research can change through a cultural shift regarding recognition and rewards for Open Science tasks.

Presentatie

Eef Benthem, Lars Feddema, Emma Mulder, Evelien Terwel, Addy Traficonte

19 juni 2026

Applied research

Wikiwijs

HboDocument

Tim Hageman, Carli Kleijnen, Alen Seuntiëns, Wesley Xu, Job Leenders, Senna van den Nieuwenhof, Daan van den Boomen

16 juni 2026

Open Education menu

We created a ready-to-use menu with 17 different Open Education practices to be implemented in your education. With each practice turned into its own dish and recipe, you can easily see how the practice can be implemented, with its difficulty level and examples. The goal is to provide you with ideas and examples on how to implement Open Science practices into your education. Or use the menu as a starting point for conversations about open educational practices with colleagues! Already an expert? The menu can also be used for a 1-hour workshop on Open Educational practices for others interested in Open Science. Let the participants select a dish from the menu they are interested in, and help them to adapt the dish so they can turn their own ideas into real practices.

Presentatie

Jeroen Bosman, Ilcan Çiftcibaşi, Anneke van der Dussen, Ruud Dielen, Marie-Louise Goudeau, Pim Huijnen, Susanne Kirchhoff, Marc van Mil, Hanne Oberman, Annelies Pieterman-Bos

9 juni 2026

Handout - TR3CA: Evaluation of your (AI-assisted) literature search

These are the Transparency & Reproducibility, Relevancy, Reliability, Coverage, Accuracy (TR3CA) evaluation criteria to evaluate whether results from an (AI-assisted) literature search are trustworthy and appropriate for your research.

Document

Anna-Lena Hoh, Marieke Schor, Floor Ruiter, Candan Yılmaz

5 mei 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

Document

Marjan Wink, Michel Kropman, Valentina Tassone

23 april 2026

Curriculum Support Roadmap

The curriculum roadmap shows how the Teaching and Learning Centre – Project Office Learning Arrangements has visualised the adaptive support service for curriculum redesign. It focuses on the level of a BSc or MSc programme. This visual can be used to inspire a redesign process and to identify major building blocks to consider during this process.

Document

Anne Velthorst, Roos Köhler

8 april 2026

Legal Network Analysis

How can complex legal systems, filled with interconnected cases, statutes, and actors, be understood through data? Legal Network Analysis offers law students and researchers a practical guide to mapping and interpreting relationships in legal data using the tools of network science. Building on the foundations of graph theory, this open textbook shows how relationships between cases, statutes, or states can reveal underlying structures in law that traditional methods often overlook. Whether analysing citation networks, treaties among nations, or the diffusion of legal norms, readers learn to translate legal questions into visual and quantitative insights. Developed by the Law and Tech Lab at Maastricht University, this resource combines conceptual clarity with applied learning. Each chapter blends concise explanations with interactive Jupyter notebooks, allowing readers to reproduce, modify, and experiment with examples in real time. Appendices include step-by-step guidance for data preparation, visualisation, and software setup; making the book equally accessible for newcomers and advanced students. Designed to support the Network Analysis course at Maastricht University, this textbook is also a valuable standalone introduction for anyone exploring the data-driven dimensions of law and policy.

Open (Access) Tekst Boek

Gustavo Arosemena, Gijs van Dijck, Roland Moerland

8 april 2026

ACA-bot

ACA-bot is an engaging chatbot designed for Automated Conversational Assessment (ACA). Drawing inspiration from traditional oral exams, this text-based conversational agent transforms assessment into a dynamic learning experience. It supports both formative and summative evaluation by offering students personalised feedback and guidance at every step of their learning journey. The first ACA-bot prototype focuses on assessing students’ understanding of basic statistical concepts, but its flexible design allows for easy adaptation to a wide range of subjects and learning contexts. Through interactive dialogue, students can practise explaining ideas clearly under exam-like conditions, apply their knowledge to new and challenging questions, and refine their reasoning as they respond to follow-up prompts. They gain valuable insights into their own understanding, identify areas for improvement, and gradually build confidence for both oral and written assessments. For educators, ACA-bot offers a powerful way to scale oral examinations and enhance formative assessment without increasing workload. It automates parts of the assessment process, provides structured and actionable insights into student performance, and opens the door to more personal, interactive feedback at scale. By combining the strengths of conversational AI and educational assessment, ACA-bot turns evaluation into a collaborative, insightful process. It empowers students to think aloud, reason more effectively, and grow, while giving educators a smarter, more innovative way to understand and support learning. ACA-bot is een slimme en inspirerende chatbot die onderwijs en Artificial Intelligence samenbrengt. Geïnspireerd door het klassieke mondelinge examen tilt deze tekstgebaseerde gespreksagent Automated Conversational Assessment naar een nieuw niveau. Studenten krijgen via natuurlijke gesprekken directe, persoonlijke feedback en begeleiding, waardoor leren en toetsen samenvloeien in één boeiende ervaring. Het prototype van ACA-bot is ontwikkeld om kennis over statistiek te beoordelen, maar dankzij het flexibele ontwerp kan het systeem eenvoudig worden aangepast aan andere vakgebieden en toepassingen. Tijdens interactieve dialogen leren studenten helder uitleg geven, hun kennis toepassen op nieuwe vragen en hun redenering aanscherpen. Ze ontdekken waar hun begrip nog verdiept kan worden en groeien zichtbaar in zelfvertrouwen — waardevolle voorbereiding op zowel mondelinge als schriftelijke examens. Ook voor docenten biedt ACA-bot een slimme oplossing. Het maakt mondelinge toetsing schaalbaar, ondersteunt formatieve beoordeling via gesprek, en vermindert de werkdruk door delen van het beoordelingsproces te automatiseren. Bovendien geeft het gestructureerde inzichten in de voortgang en denkwijze van studenten, waardoor elke dialoog bijdraagt aan beter onderwijs. ACA-bot laat zien hoe Automated Conversational Assessment het leren persoonlijker, interactiever en effectiever maakt. Studenten denken hardop, verkennen hun eigen begrip, en verbeteren met vertrouwen — terwijl docenten op een innovatieve, datagedreven manier inzicht krijgen in hoe kennis werkelijk wordt begrepen.

App

Aki Härmä, Julie Bauer