Preben Wik

Papers

1

Total Citations

8

H-Index

1

About

Preben Wik is a researcher whose work sits at the intersection of educational technology, human-robot interaction, and second language acquisition. His most-cited study, "The effect of a physical robot on vocabulary learning" (2019, 8 citations), investigates how a physical robot acting as a teacher or exercise partner can enhance language learning. By developing an application that compares three different learning conditions, Wik provides empirical evidence on the role of embodiment and social presence in educational settings. This work contributes to the growing field of robot-assisted language learning, offering insights into how physical robots can support vocabulary acquisition more effectively than digital alternatives. Wik's research is particularly relevant for educators and technologists interested in designing interactive, engaging tools for second language learners. His findings highlight the potential of social robots to serve as motivating and effective learning companions, paving the way for future studies on human-robot collaboration in education.

Research Focus

Key Achievements

1
H-Index
1
Papers
8
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
The effect of a physical robot on vocabulary learning
8 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 3

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago