Beyond Textbooks: A Study on Supporting Learning of Molecule Naming in a Virtual Reality Environment

Leonie Disch, Sebastian Überreiter, Viktoria Pammer-Schindler

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandBegutachtung

Abstract

Virtual reality (VR) applications promise to enhance learning experiences, with literature emphasizing game-based components, immersiveness, and exploration of inaccessible scenarios. However, effective learning through VR applications depends on technology design. This within-subjects study investigates a VR application targeted to learning molecule naming, following design principles for VR and knowledge construction. Our results show that participants (n=20) had a positive direct learning effect, as they scored significantly better in a knowledge test on molecule naming directly after the intervention compared to before. Further, a sustainable learning effect could be shown, as scores in the knowledge test after three weeks were significantly better than those before the intervention but did not differ from those directly after the intervention. Our contribution is demonstrating design guidelines for learning and knowledge construction in VR, specifically for chemistry, and showing that following such guidelines leads to an application that effectively supports learning.

Originalspracheenglisch
TitelMuC 2024 - Proceedings of the 2024 Mensch und Computer
Herausgeber (Verlag)Association of Computing Machinery
Seiten310-322
Seitenumfang13
ISBN (elektronisch)9798400709982
DOIs
PublikationsstatusVeröffentlicht - 1 Sept. 2024
Veranstaltung2024 Mensch und Computer, MuC 2024 - Karlsruhe, Deutschland
Dauer: 1 Sept. 20244 Sept. 2024

Publikationsreihe

NameACM International Conference Proceeding Series

Konferenz

Konferenz2024 Mensch und Computer, MuC 2024
KurztitelMuC 2024
Land/GebietDeutschland
OrtKarlsruhe
Zeitraum1/09/244/09/24

ASJC Scopus subject areas

  • Human-computer interaction
  • Computernetzwerke und -kommunikation
  • Maschinelles Sehen und Mustererkennung
  • Software

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