Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Readers Theater in Virtual Reality

Version 1 : Received: 17 July 2023 / Approved: 17 July 2023 / Online: 18 July 2023 (13:59:59 CEST)

A peer-reviewed article of this Preprint also exists.

Peschke, L.; Kiani, A.; Massler, U.; Müller, W. Readers Theater in Desktop VR: A Pilot Study with Grade Nine Students. Virtual Worlds 2023, 2, 267-289. Peschke, L.; Kiani, A.; Massler, U.; Müller, W. Readers Theater in Desktop VR: A Pilot Study with Grade Nine Students. Virtual Worlds 2023, 2, 267-289.

Abstract

Appropriate techniques for promoting reading fluency are difficult to implement in the classroom. There is little time to provide students with individualized feedback on reading aloud or to moti-vate them to do so. In this context, VR can be beneficial for learning, to provide individualized feedback and for increasing learners' engagement. Studies analyzing established methods of lan-guage learning in school in VR seem to be lacking so far. Therefore, this study project was the first to analyze the acceptance of students towards the implementation of a concept of reading fluency training with students at a secondary school in VR. The study method was developed based on the Technology Acceptance Model. The VR environment developed is web-based and provides indi-vidual and collaborative opportunities for training reading fluency, giving, and receiving feed-back, and deepening content understanding of the reading texts. To analyze the acceptance of the VR environment, 5 guided interviews were conducted. The results show that despite technical challenges with the VR environment, students accepted and appreciated the reading fluency training in VR. The integration of established concepts of reading fluency training in foreign lan-guage classrooms has great potential as additional added value can be created to address the challenges of face-to-face instruction.

Keywords

virtual reality; reading fluency training; language learning; acceptance; students; secondary school

Subject

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

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