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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

21 juli 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

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

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

18 maart 2026

Improving Health Care with Clinical Prediction Models

Clinical prediction models are increasingly used to support health care decisions, helping clinicians estimate disease risk, guide treatment choices, and tailor care to individual patients. At the same time, advances in data science and artificial intelligence have led to a rapid expansion of prediction modelling research. Yet despite this growth, only a small proportion of published models ever reach clinical practice. Improving Health Care with Clinical Prediction Models – From Idea to Impact shows how you can bridge this gap. The book guides readers through the full pathway of prediction modelling in health care: from defining a meaningful clinical problem and identifying existing models to developing, validating, evaluating, and implementing prediction model–based innovations. Combining methodological guidance with real-world clinical examples, the book explains not only how to build robust prediction models but also how to ensure they become useful tools in everyday care. Written in an accessible style and requiring only a basic understanding of statistical modelling, it provides students, researchers, and clinicians with a practical roadmap for turning prediction models into innovations that are useful, usable, and used. What this book helps you do This book takes you through the complete process of clinical prediction modelling, from the first idea for a model to its implementation in health care practice. Along the way, readers learn how to: Define a meaningful clinical problem and identify where prediction models can improve health care Find and critically evaluate existing prediction models before deciding to develop a new one Handle missing data using methods such as multiple imputation Develop and validate prediction models using established regression approaches Apply advanced regression and artificial intelligence methods for clinical prediction modelling Select models with real-world impact potential and translate them into practical decision tools Evaluate the impact of prediction model–based innovations using decision modelling and empirical studies Implement prediction model–based innovations in clinical practice and new health care settings

Open (Access) Tekst Boek

Luc Smits, Sander van Kuijk, Laure Wynants

3 maart 2026

Crash course SPSS syntax

Standalone assignment. A very basic, step-by-step introduction to SPSS and SPSS syntax. Uses data from the European Social Survey as example.

Document

Alex Lehr

3 maart 2026

Quick and dirty reliability and factor analysis with SPSS syntax assignment

SPSS syntax assignment for teaching the basics of reliability and factor analysis. For when you need to teach or learn the basics but don't have a lot of time for it. Covers inter-item correlations, Cronbach's alpha, and factor analysis (unrotated, varimax and oblimin rotation). Uses European Social Survey data. Includes questions and some basic explanations. Intended to be used in conjunction with a preceeding lecture.

Document

Alex Lehr

17 december 2025

Onderwijs & AI Module voor Docenten

Generative Artificial Intelligence (genAI), ofwel generatieve kunstmatige intelligentie, maakt een snelle groei door. De nieuwste generatie genAI tools is zo goed dat het steeds moeilijker wordt te onderscheiden of een tekst door een mens of AI is geschreven. De ontwikkeling van genAI heeft dan ook een grote impact op de maatschappij en daarmee ook op het onderwijs. Daarnaast kan genAI onderdeel uit gaan maken van de toekomstige werkpraktijk van vele studenten. De realiteit is dat deze technologie er is en we zullen ons ertoe moeten verhouden. Hoewel de eindverantwoordelijkheid voor het gebruik van genAI ligt bij de student zelf, hebben wij de verantwoordelijkheid om hen te helpen hier op een verantwoorde manier mee om te gaan. Deze module beoogt hierbij te ondersteunen. Na het doorlopen van deze module ben je bekend met: Wat genAI is. Wat de impact van genAI is op onze wereld. De juridische kaders van genAI. De relatie tussen genAI en academische waarden en integriteit. De manieren waarop studenten genAI kunnen gebruiken en wat dat kan betekenen voor academisch onderwijs. De impact die genAI kan hebben op jouw onderwijs. Elk van de bovenstaande leerdoelen hoort bij één hoofdstuk van deze module. Deze module is gebaseerd op de module AI geletterdheid van de Rijksuniversiteit Groningen. De module is zowel in het Nederlands als het Engels beschikbaar en wordt hier aangeboden als Brightspace package. Dit zou ook in Canvas geïmporteerd kunnen worden.

Document

Steven Trooster, Max Moeskops

6 december 2025

Novel Switchable Glazing Assemblies for Privacy & Glare Control in a Mediterranean Climate

In this recorded presentation from glasstec 2024, Etienne Magri details a research study investigating the combination of PDLC and SPD adaptive glazing technologies to enhance glare control in buildings, using Malta's subtropical climate as a case study. The project involved testing individual and combined laminates within a scale model, evaluating visual appearance and glare using DGP metrics. Results demonstrated that the combined technologies achieved near-complete blackout, effectively eliminating solar glare while maintaining privacy, and successfully transformed static facades into dynamic systems with adjustable transparency. The video was produced by the Open GLASSroom project. Special thanks to Etienne Magri for contributing to the Open GLASSroom OER collection. The creation of these resources has been (partially) funded by the ERASMUS+ grant program of the European Union under grant no. 2022-1-DE01-KA220-HED-000089750. Neither the European Commission nor the project's national funding agency DAAD are responsible for the content or liable for any losses or damage resulting of the use of these resources.

Video

Etienne Magri

30 oktober 2025

Programming Foundations

This introductory programming book offers a hands-on approach to learning Python, designed specifically for students of natural sciences who wish to enter the world of coding. Covering fundamental programming concepts - from variables and data types to functions and loops - the book presents examples and exercises rooted in applications across biology, physics, and mathematics. In addition to Python fundamentals, readers also build good practices of programming and working with computers, such as using the terminal, navigating an integrated development environment, tracking changes with Git, and writing pseudocode. Moreover, the book addresses how to usage generative AI tools effectively when learning the basics of programming. Through hands-on learning, each chapter builds both confidence and competence, guiding students from simple scripts to more complex code. By the end of the book, students will not only understand Python’s core principles but also have the skills and tools to tackle real coding challenges within their scientific disciplines in the age of AI.

Open (Access) Tekst Boek

Nikolina Šoštarić