
This presentation was created for an online workshop on practical data protection in research, which took place on 20 November 2025 as part of the RDMTraining4NFDI hybrid event’s interactive workshop series. The published materials also include the accompanying workshop Pad Template, available at https://pad.carpentries.org/Workshop-Motivation-and-didactics.The description provided to participants is given below. Effective teaching goes beyond delivering content. It’s about creating a learning environment that supports understanding, motivation, and engagement. This module explores how didactic design and motivational strategies can help trainers in research data management (RDM) create meaningful learning experiences. Drawing on principles from The Carpentries and evidence-based pedagogy, participants will learn how to manage cognitive load, use formative assessment to identify misconceptions, and adapt instruction to the learners’ level of expertise. The module also emphasizes the importance of maintaining motivation - both for learners and trainers - and of using positive, inclusive language that fosters participation and confidence. By reflecting on their own teaching practices and engaging in practical exercises, participants will develop a deeper understanding of how to make RDM training sessions more effective, learner-centered, and enjoyable. In this module, you will: Explore the relationship between expertise and teaching Identify and apply strategies to manage cognitive load Use formative assessments to support learning Recognize and address motivational factors in learners Create a positive and inclusive learning environment Instructor notes are available at https://carpentries.github.io/instructor-training/.
Didactics, train the trainer
Didactics, train the trainer
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
