Abstract
The Erasmus+ project ‘Virtual Worlds for Learning and Teaching Archeology’ in which the University of Bonn, University of Amsterdam (further UvA), Universitet I Oslo, and the Open Universiteit participate, includes a commitment to organize two Spring schools for students. These Spring schools are part of the activities that the project undertakes to address the horizontal priority ‘Addressing digital transformation through the development of digital readiness, resilience, and capacity’ and the priority of stimulating innovative learning and teaching practices. The general aim of the Spring schools is the development of digital skills and competences of students in the emerging field of 3D technology and virtual worlds and digital education. Furthermore, they offer students an opportunity to actively participate in designing education and learn about educational design and working with the affordances of new digital technologies.
The focus of the first Spring school is on designing learning scenarios by students and the second Spring school will be devoted to the design of virtual reality environments and 3D models.
In 2024 the first Spring school ‘Learning scenarios in virtual worlds’ was organized in Amsterdam, hosted by UvA, with a focus on seamless learning design and virtual environments in teaching.
The focus of the first Spring school is on designing learning scenarios by students and the second Spring school will be devoted to the design of virtual reality environments and 3D models.
In 2024 the first Spring school ‘Learning scenarios in virtual worlds’ was organized in Amsterdam, hosted by UvA, with a focus on seamless learning design and virtual environments in teaching.
Original language | English |
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Commissioning body | DAAD |
Number of pages | 131 |
Publication status | Published - 2024 |
Event | International Spring School in Amsterdam : Learning scenarios in virtual worlds - Bushuis, Amsterdam Duration: 2 Apr 2024 → 5 Apr 2024 |
Keywords
- virtual worlds
- archaeology
- seamless learning
- 3D models
- learning scenarios