Evaluating metaverse-based library orientation with Roblox for first-year students

This study investigates the comparative effectiveness of metaverse-based and traditional library orientations for first-year university students, focusing on user engagement, library-related anxiety, knowledge acquisition, and overall suitability. A quasi-experimental design was employed, with participants assigned to either a physical library tour or a gamified orientation developed on the Roblox platform. Quantitative results revealed that the traditional format produced higher scores in focused attention and perceived usability, while the metaverse-based approach yielded greater intrinsic rewards. Both formats significantly reduced library anxiety, although the traditional method was more effective in fostering interpersonal comfort, whereas the metaverse-based orientation better addressed affective and cognitive dimensions. Both groups significantly improved knowledge acquisition, with the traditional tour showing marginally higher gains. Qualitative feedback highlighted differing preferences and suggested improvements for both formats. The study concludes that while traditional orientations remain effective, metaverse-based platforms offer scalable, engaging alternatives. Implications for hybrid orientation models and future use of generative AI in virtual environments are discussed.

Authors

Institutions

Publication Details

Journal
The Journal of Academic Librarianship
Published
2025-12-24
DOI
https://doi.org/10.1016/j.acalib.2025.103187
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluating metaverse-based library orientation with Roblox for first-year students

Kannikar Intawong, Kitti Puritat, Songpon Khanchai, Sumalee Sangamuang et al.
The Journal of Academic Librarianship
Virtual Reality Applications and Impacts
article

Evaluating metaverse-based library orientation with Roblox for first-year students

Kannikar Intawong, Kitti Puritat, Songpon Khanchai, Sumalee Sangamuang, Pakinee Ariya
article en

Abstract

This study investigates the comparative effectiveness of metaverse-based and traditional library orientations for first-year university students, focusing on user engagement, library-related anxiety, knowledge acquisition, and overall suitability. A quasi-experimental design was employed, with participants assigned to either a physical library tour or a gamified orientation developed on the Roblox platform. Quantitative results revealed that the traditional format produced higher scores in focused attention and perceived usability, while the metaverse-based approach yielded greater intrinsic rewards. Both formats significantly reduced library anxiety, although the traditional method was more effective in fostering interpersonal comfort, whereas the metaverse-based orientation better addressed affective and cognitive dimensions. Both groups significantly improved knowledge acquisition, with the traditional tour showing marginally higher gains. Qualitative feedback highlighted differing preferences and suggested improvements for both formats. The study concludes that while traditional orientations remain effective, metaverse-based platforms offer scalable, engaging alternatives. Implications for hybrid orientation models and future use of generative AI in virtual environments are discussed.

The Journal of Academic LibrarianshipVol. 52(1)
Chiang Mai University (TH)
Quality Education
Openalex Percentile: Top 35%
Virtual Reality Applications and Impacts
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.