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HBO/WO

MBO

June 17, 2026

AgriLemma 2.0: A serious game for exploring dilemmas in agriculture

In AgriLemma, you are a farmer in Europe managing your own farm across 8 seasons. You grow six types of crops — potatoes, sugar beets, rapeseed, corn, wheat, and chickpeas — each requiring resources such as seeds, water, nutrients, and workers. Players must run, invest in, and improve their farm with sustainable technologies while balancing competing priorities and navigating uncertainties like weather events and pest attacks. The objective is to maximize overall farm health, which is determined by three dimensions: environmental health (positive ecological impact), social health (worker satisfaction), and financial health (farm profitability). Players must strategize across all three dimensions simultaneously — decisions that boost profit may come at an environmental cost, and vice versa. The game makes these trade-offs tangible, encouraging reflection on what sustainable farming really requires. ------------------------------ Learning objectives: · Experiment with different strategies — to operationalize and adapt an approach under pressure, and to reflect on how well it held up. · Expose students to issues of risk management — to plan, control, and explain the reasoning behind in-game choices relating to sustainability, soil conservation practices, integrated crop management, weeding, and pest management, and to learn how to respond when conditions change. · Experience the complexity of decision-making — to take into account weather and policy uncertainties, sustainability pressures, economic realities, and the broader context in which farm decisions are made. --------------------------------Practical information: · Format: Board game (physical/ print-and-play) · Players: 2-4 players (extendable to 8 by playing in teams of 2) · Duration: 3 hours, including onboarding and debrief · Level: Higher education / Stakeholder engagement · Language: English --------------------------------Credits: AgriLemma was originally designed as part of the WATERAGRI project. The second version, including a full redesign of the graphics, was developed with funding support from the TU Delft Open Science Programme course "Civic Engagement in Action: Empowering Researchers and Educators to Make an Impact". Game design: Dr. ir. Aashna Mittal - TU Delft, Faculty of Technology, Policy and Management Graphic design and illustration: Gracia Bovenberg-Murris and Michelle de Smit – TU Delft GameLab Note on image generation: The images in the tech cards and the border of the main game board were created using AI-generated imagery. The constructed wetlands card image is also AI-generated. All other cards and box art are hand-drawn or created in Adobe Illustrator. Note on usability: The print-and-play version of the game has been optimized for office printing.

Document

Aashna Mittal, Gracia Bovenberg-Murris, Michelle de Smit

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

March 15, 2026

Beyond Google Scholar

Students often struggle to find relevant literature for their thesis projects. The main aim of this tutorial is two-fold, namely to teach students (1) how to find relevant literature using various databases and search strategies and (2) how to critically reflect on the role of digital databases and Generative AI tools in their search process. The package includes a lecturer’s manual and two versions of the same tutorial: one with steps in Excel and one without. The tutorial can be delivered as an in-class workshop (2–3 hours) or assigned as a take-home assignment. The databases and tools used in this tutorial include Zotero, Google Scholar, Project MUSE, JSTOR, ChatGPT, and Excel. The tutorial can be used in any higher education classroom and is particularly suitable for courses that prepare students for writing a BA or MA thesis.

Document

Jasmijn van Gorp

September 24, 2025

Amateur Craft as Method-in-the-Making:

This research output documents a pandemic-era experiment in which academic researchers used knitting to record and reflect on their digital screen time, exploring craft as a critical research method and a tool for data sensitisation, feminist activism, and embodied knowledge making. Project Overview: A group of academics and amateur knitters from Maastricht University and partner institutions met online during 2020–2021, using knitting to document their own screen time over a week of lockdown. Their creative outputs—a collection of individually knitted rectangles—were later assembled as a tactile "knitted book" to display in arts and crafts contexts, as well as academic contexts. The project linked technofeminist thinking, craftivism, and artistic research practices, aiming to make visible both quantitative and qualitative aspects of technology use during social isolation. Main Topics and Learning Objectives: • Explore how amateur craftwork (knitting) can act as a research method to sensitise and interpret personal data. • Engage with concepts from technofeminism and critical craft studies to understand the role of tactile, embodied methodologies. • Foster social connection, experimentation, and reflection on digital dependency during the COVID-19 lockdown. • Develop awareness of how materials, technique, and individual interpretation shape both method and outcome in collaborative research. Audience: This work suits students, educators, and researchers interested in qualitative and artistic research methods, feminist theory, science and technology studies (STS), and creative digital-literacy pedagogies. It models interdisciplinary practice and encourages engagement with data, methodology, and making as interconnected experiential processes. Authors and Licensing: Authors: Denise Petzold (first and corresponding author), Laura Barendregt, Ruth Benschop, Anna Harris, Laudy van den Heuvel, Bernike Pasveer, Veerle Spronck, Sally Wyatt, affiliated with Maastricht University, TU Delft, Zuyd University of Applied Sciences, and HKU University of Arts Utrecht. The text is suitable for publication in open educational repositories and supports open, collaborative engagement with academic craftwork. The pictures of the digitised version of the book were taken by Eric Bleize. Suggested Citation: “Amateur Craft as Method-in-the-Making: Experiments in Knitting Screen Time during a Pandemic” by Denise Petzold, Laura Barendregt, Ruth Benschop, Anna Harris, Laudy van den Heuvel, Bernike Pasveer, Veerle Spronck and Sally Wyatt (2025), Maastricht University, is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits reuse, distribution, and adaptation, provided appropriate credit is given.

Document

Denise Petzold, Laura Barendregt, Ruth Benschop, Anna Harris, Laudy van den Heuvel, Bernike Pasveer, Veerle Spronck, Sally Wyatt

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

September 1, 2025

Responsible Anticipation and Visioneering

This exercise targets the development of students' capacities to critically analyze existing technological visions and enables them to create their own responsible socio-technical visions. Through group work and discussions, students examine technological promises embedded in anticipation discourses, uncover hidden values and assumptions, and develop alternative narratives that can guide engineering practice and policy decisions

Document

Martin Sand

August 21, 2025

Collage-making for self-discovery in engineering ethics

This creative exercise enables students to discover, reflect and express their emotions in relation to engineering. In this way, the exercise enables self-understanding through an encounter with one’s own feelings and intuitions and serves as a starting point for better ethical deliberation and well-being. Learning goals: • Expanding moral sensibility (being aware of their own emotions, values and norms) • Stimulating moral creativity and imagination

Document

Aafke Fraaije

July 1, 2025

AI as a science - course manual

AI as a Science aims to highlight how research involving “artificial intelligence” can be considered scientific, and what that means for us as scholars engaged in this — and related — areas of study. During the course, we will explore answers to questions such as: What is AI? What role do scientists play in the development of AI? And vice versa: what role do AI researchers play in the scientific investigations of computation, artificial intelligence, and intelligence more broadly? Do such roles come with responsibilities and ethical duties? We will explore these questions dialogically (i.e., through dialogue, discussions, and presentations), as well as through lectures. Perspectives will include critical, historical, sociological, and philosophical angles. We will touch on: The history of AI, going as far back as ancient Chinese and Greek civilizations; future projections, including the possibility of another "AI winter." Ultimately, you will aim to answer for yourselves: Is AI a science? Can it be? Will it be? The course will be examined through: Group presentation – You will be split into teams to create a presentation (see Presentation). The presentation combines: Group collaboration, An individual (or more than one person’s) presentation (10 minutes max). Final essay – You may choose a topic related to the course and aligned with your background or interests (see Essay). The essay will take the form of a literature review or journal-style article, aiming to: Deepen and/or broaden your knowledge on one or more topics from the course, Allow you to zoom in or out and develop your own unique perspective. Learning Goals: AI as a Science aims to teach you — and for you to teach yourselves — how to: Define science and AI, critically and in your own words. Understand the historical context of AI: When did AI or AI-like disciplines and ideas emerge? Understand the current state of AI and explore possible futures: Is time a flat circle when it comes to recurring “AI winters”?

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Olivia Guest

June 6, 2025

Multilevel modeling for social scientists

The course builds on the knowledge and skills acquired in the previous methods courses. The course will introduce students to multivariate analyses of nested data using multilevel modeling techniques. The course focuses on the theory and application of fixed and, in particular, random effects models. Using data from the European Social Survey, the students will learn how to estimate and interpret such as models using Stata.

Document

Alex Lehr

June 1, 2025

Week 3: Creating and Selecting Options

Around this video, a lesson has been built with specific learning objectives, activities, and supporting materials for students. The next steps in the case-solving cycle are being explained: generating and selecting solutions. Students explore ideation techniques like brainwriting and mind mapping to develop creative, practical ideas. Ground rules help keep the process focused, collaborative, and open. To evaluate ideas, the SFA framework (Suitability, Feasibility, Acceptability) is used to shortlist the most promising options. A real-world example shows how these tools lead to well-founded decisions. Finally, students learn to apply a decision-making matrix to compare options using relevant criteria. This lesson helps students move from insights to action by developing structured, team-driven solutions.

Document

Hans van Oudheusden, Britta Stoelinga