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Data Snack - Teach Data, Teach Better: Enhancing University Teaching with Research Data

de Vogel, Susanne; Richter, Franziska

Abstract

Using real research data in teaching can help students develop data literacy skills and better understand academic research processes. In this Data Snack, we offer a first glimpse into an upcoming collaboration between the DSC and the University of Bremen’s Office for Higher Education Didactics (Hochschuldidaktik) that will focus on reflecting data literacy aspects of your teaching and teaching with data. In this session, we will talk about how research data can enrich university teaching, provide some examples, highlight the benefits this holds not only for students, but also for teachers and researchers (e.g. showcasing own research, research-based learning), and from a research ethics perspective (e.g. transparency, sustainable data use). We will also address key challenges (e.g. data protection) and hint at possible strategies to deal with them. We are also eager to hear from you: What types of data – qualitative, quantitative, your own, or from repositories – would you like to use more in your teaching? What experience do you have with (re)using research data in the classroom? Are the students in your degree program trained in data literacy? What would your students need regarding data literacy? And what support would you need from a future workshop? Join us for a short input and open discussion on opportunities and needs in teaching and learning with real research data.

Full text

Teach Data, Teach Better: 30 October 2025 CONTACT Dr. Susanne de Vogel Data Scientist @ DSC UB [email protected] Franziska Richter Advisor @ Teaching and Learning UB [email protected] Enhancing University Teaching with Research Data 2 DATA… … are omnipresent (→Datafication) … form the basis for gaining knowledge … enable better decisions Mai 2017 July 2021 2 Why are data skills so important? Data… Data hold enormous potential for science, economy, and society, but challenges with data management exist! 2025 175 ZB 2021 64 ZB Modified from: The digitization of the world from edge to core –IDC whitepaper; Rydning et al., 2017 1 ZB = 1,000,000,000,000 GB 3 Science as all other sectors needs good ways to save and manage its data! Why are data skills so important? From Reuters Why are data skills so important? From Phenomena for NGSS From BBC BITESIZE From Encyclopedia of the Environment To gain wisdom, we have to be able to connect data in a meaningful way. 5 Data literacy is the ability to collect, manage, evaluate and apply data in a critical and responsible manner (Schüller, 2023). This includes skills in •Research Data Management •Data Science (incl. the use of artificial intelligence techniques) •Critical Thinking •Ethical, Legal, and Social Aspects (ELSA) Data Life Cycle Planning Acquisition Analysis Archiving Access Reuse What is data literacy? Why are data skills so important? 6 Why are data skills so important? Using real research data in teaching can help students develop data literacy skills and better understand academic research processes. Images created with ChatGPT (OpenAI, 2025) Sources of Research Data for Teaching 7 Where can your teaching data come from? Data from students Data from lecturers/researchers Data from external sources Data collected by students themselves as part of coursework, methods training or theses. →Small-scale surveys or polls →Interviews or focus groups →Field observations →Experiments →(Sensoror app-based) data collection →Code, software or prototypes Data that has been collected in the lecturer’s own academic research. →Ongoing or completed research →Research projects →Publications Data obtained from research repositories, public archives, or open data portals. →Research data repositories: PANGAEA, Qualiservice, Zenodo →Statistical offices and regional data: Destatis, Metaver →Other: Journals, Github, OSM, Kaggle, Huggingface Applications of Teaching with Research Data 8 What can you teach with your research data? Data from students Data from lecturers/researchers Data from external sources Learning by doing •Study design •Data collection •Data cleaning •Data analysis •Writing reports and present findings •Organizing and managing research data •Reflecting on ethics •Data publication and open science Teaching through own research Learning with open data •find and access existing datasets •assess data quality and licensing •secondary analysis •integrate multiple data sources •visualize and communicate results •connect data to societal questions •Linking theory and empirical research •Structure and documentation of real research data •Replication of published analyses (reproducibility) •Analysis techniques •Data visualization and storytelling •Critical discussion of study design and limitations Images created with ChatGPT (OpenAI, 2025) Benefits of learning with data 9 What’s the gain? •Learn to think critically •Understand research processes and gain hands-on experience with real-world data •Develop necessary skills for their bachelor-/master theses •Experience a more engaging and interactive form of learning than traditional lectures •Build transferable skills for academia and the job market •Link teaching and research in a meaningful way •Motivated students •Showcase own research and increase visibility •Benefit from synergies when integrating students into ongoing research (delegate selected tasks, gain new perspectives) •Promotes public understanding of evidence-based reasoning •Strengthens trust in science and institutions •Supports open science and transparency •Contributes to sustainable use of research resources Images created with ChatGPT (OpenAI, 2025)