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HBO/WO

MBO

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

April 8, 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

September 1, 2025

A virtual research cruise to characterise the North Sea water system

In this assignment you will learn to set up your own virtual research cruise, during which you will ‘measure’ biophysical oceanographic properties and analyse them. The ocean is not an easy place to perform measurements. It covers a vast area, is not always easy to access (think about the deep ocean), and measuring comes with obstacles. We’re bound by shiptime (which is expensive), the types of instruments that are available (they may break), the weather (storms), sea-ice, seasickness… As research cruises are time consuming and costly, it is important to plan very well. One tool that can help scientists in planning their cruise is VirtualShip. In this assignment, you will use VirtualShip and design a measurement campaign in the North-West European Shelf region, aimed at measuring a cross-section from the open ocean, via the North Sea, towards the coast of Zeeland in the south-west of the Netherlands. Included is a rubric for grading the student reports.

Document

Emma Daniels, Aimee Slangen, Jamie Atkins, Jana Cox

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.

Document

Alex Lehr, Roderick Sluiter

June 20, 2024

Testing theory: an introduction

These lecture notes are a follow up on Adjustment theory. Adjustment theory deals with the optimal combination of redundant measurements together with the estimation of unknown parameters. There are two main reasons for performing redundant measurements. First, the wish to increase the accuracy of the results computed. Second, the requirement to be able to check for mistakes or errors. The present book addresses this second topic. Although one always will try one's best to avoid making mistakes, they can and will occasionally happen. It is therefore of importance to have ways of detecting and identifying such mistakes. Mistakes or errors can come in many different guises. They could be caused by mistakes made by the observer, or by the fact that defective instruments are used, or by wrong assumptions about the functional relations between the observables. When passed unnoticed, these errors will deteriorate the final results. The goal of this introductory course on testing theory is therefore to convey the necessary knowledge for testing the validity of both the measurements and the mathematical model. Typical questions that will be addressed are: 'How to check the validity of the mathematical model? How to search for certain mistakes or errors? How well can errors be traced? And how do undetected errors affect the final results?' The theory is worked out in detail for the important case of linear(ized) models. Both the parametric form (observation equations) and the implicit form (condition equations) of linear models are treated. As an additional aid in understanding the basic principles involved, a geometric interpretation is given throughout. Attention is also paid to the performance of the testing procedures. The closely related concept of reliability is introduced and diagnostic measures are given to determine the size of the minimal detectable biases. In this introductory text the methodology of testing is emphasized, although various examples are given to illustrate the theory. The methods discussed form the basis for geodetic quality control and they provide the ingredients for the formulation of guidelines for the reliable design of measurement set-ups.

Open (Access) Text Book

Peter Teunissen

2024

How to design open inquiry labs

In this article we show how student “open inquiries” in undergraduate labs can be powerful teaching and assessment methods. In such open inquiries it is the students who define the question they want to answer, formulate the hypothesis, search for information, design and carry out experiments to reach their goal, and share their ideas, needs, and results with others. This student agency afforded by open inquiry trains critical thinking, teaches students to learn from failure, and requires effective science communication in authentic contexts. Adapting open inquiry methods for the first time can be especially daunting for instructors who have no examples to draw upon. To address this challenge we explain the findings of a diverse group of five lab instructors and an educational researcher who have compared open inquiry practices in different contexts. As a group, we formed a Community of Practice dedicated to “Supporting students’ scientific Open Inquiries in Labs” (aka SssOIL). The commonalities across our diverse project team suggest some defining features and best practices. By sharing our findings and example course designs and materials, we hope to aid instructors in adapting more open inquiry teaching methods in their own lab courses. Any questions about this article can be addressed to Forrest via: forrestbradbury@gmail.com or to our team via: S3OIL@outlook.com

Document

Forrest Bradbury, Simone Mesman, Morten Stromme, Paul Logman

August 23, 2023

Lecture: The Data Analysis Process

To be able to demonstrate knowledge of the data analysis process To understand differences between methodologies and standards

Website

HCAIM Consortium

August 23, 2023

Lecture: Hyperparameter tuning

Investigate effects on capacity and depth Experient with varying epochs and batch sizes Trial different activation functions and learning rates

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HCAIM Consortium

August 23, 2023

Practical: Natural Language Processing

Student will understand the basics of the core NLP techniques Student gets familiar with the use of a Naive Bayes Classifier

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HCAIM Consortium