July 27, 2026
The Index of Medieval Art houses, contextualizes, and presents images and information relating to the iconographic traditions of the medieval world. Founded in 1917 and maintained by a specialized staff of art historians, it serves iconographic researchers through both its physical archive on the Princeton University campus and an expanding online database. Its ongoing program of conferences and publications provides opportunities for continuing scholarly and public discourse about the visual culture of the Middle Ages. Once a subscription service, the online database has been freely available to the public since 2023. Online holdings comprise 177, 306 (to date) online records of works of art from early apostolic times to ca. 1600. While western European and Byzantine Christian art remain most heavily represented, secular, Jewish, and Islamic art is also being added.
The Trustees of Princeton University
July 23, 2026
How to do literature research.
Rian Kriesels, Kim Dibbets, Linda Schoonmade, Emma Besijn, Sebastien Valkenberg, Arjan De Rooy, Ruben Wiering, Michèle Meijer, Anouk Nuijten, Rick Vermunt, Marijn de Groote, Harm le Grand (Kennisnet), Linde Voorend
March 15, 2026
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.
Jasmijn van Gorp
March 10, 2026
This manual describes how to use the 'selection models' of the Open3DModel to create 'sub models'. Sub models are 3D models of the Open3DModel that contain only a limited number of structures and are aimed to view or demonstrate a specific anatomical topic, e.g. what is the spatial interrelation of structures a, b and c. They are meant to allow easily viewing or demonstrating of a specific (anatomical) topic. The sub models are collected at https://anatomytool.org/open3dmodel-learn.
Open 3DModel
February 2, 2026
Deze collectie bestaat uit verschillende materialen van het scholingstraject AI-geletterdheid. De doelgroep van dit specifieke traject is medewerkers bij de Universiteitsbibliotheek VU. Je kan het materiaal ook met eventueel wat aanpassingen ook voor andere doelgroepen gebruiken. Het scholingstraject bestaat uit 4 sessies: Introductie in AI Toelichting: Algemene introductie over wat AI is. Welke begrippen moet je weet van hebben? Wat kan een taalmodel? Etc. Verder diende deze sessie om het beginniveau van collega’s te bepalen, zodat wij hier rekening mee konden houden voor de opvolgende sessies. Effectief prompten Toelichting: Dit is een praktisch onderdeel, met als doel op een effectieve manier te leren prompten om de juiste informatie te verkrijgen. Verantwoord & kritisch omgaan met AI Toelichting: Dit is een meer theoretisch onderdeel met veel ruimte voor gesprek en discussie, over onderwerpen als: duurzaamheid, big tech, etc. AI-tools & werk Toelichting: In deze sessie nodigden wij 3 collega’s uit om hun ervaringen te delen en een demo te geven hoe zij AI gebruiken in hun werk. In deze collectie vind je de slides met inhoudelijke stof en interactieve opdrachten, inclusief een PDF voor de gebruikte exit ticket en toetsmatrijs (met leerdoelen gekoppeld aan de taxonomie van Bloom). Verder is ook een link naar de e-learning ‘AI-geletterdheid voor UB-medewerkers’ opgenomen. Deze werd gebruikt als aanvulling (voor- en/of nabereiding) op de fysieke sessies. Als laatste is een eindopdracht toegevoegd met bijbehorende rubric.
Kim Dibbets, Jordy Gevers
September 25, 2025
With this e-learning course, students develop a basic level of information literacy. The module is designed for first-year students who want to master the basics of information literacy. The module is divided into five steps: orientation and specification, planning and searching, critical evaluation, organization and processing, and publishing and communication.
Bibliotheek Hogeschool Arnhem Nijmegen
September 14, 2025
These PowerPoints are designed to provide teachers the means to improve their students' AI literacy. The presentation is divided into seven themes: 1: What is Generative AI? 2: How does Generative AI work? 3: Prompting 4: GenAI and hallucinations (in development) 5: GenAI and bias 6: GenAI and sustainability 7: Gen AI and privacy/ bias Each topic includes a section focusing on traditional knowledgetransfer and a simple, active learning method. This material is licensed under CC BY-NC-SA 4.0. Created by the Teaching and Learning Centre (TLC) of UvA Centraal in collaboration with the TLC of the Faculty of Medicine.
Jesper Pool, Remco Jongkind, Sophie van Dijke, Job Radelaar, Frans Aris, Bjarne de Beer, Palina Vasilyeva, Ivar Kolvoort
September 11, 2025
How to do literature research for first year bachelor students.
September 8, 2025
September 1, 2025
This class pursues a twofold goal of making students both think about the use of AI in recidivism prediction/social benefits allocation and reflect on the possible use of AI for making evaluative, moral judgments. To do so, students are first presented with contextual information about recidivism prediction and social benefits allocation controversies before the class through mandatory reading. During the class, students are divided into four groups that take contrasting positions on these two issues (recidivism prediction and social benefits allocation) and are asked to suggest (counter-)arguments for the position that they have been assigned in a debate-style manner, following academic argumentative norms. Later, students use ChatGPT/GPT3 or an alternative LLM with a chat interface to prompt it about arguments and counter-arguments pertaining to their position. As a result, students compare and discuss the answers they have come up with and those offered by ChatGPT, both within the groups and with the whole class, exploring different dimensions of using AI for evaluative moral judgments
Olya Kudina, Dmitry Muravyov