ArticlePloS one2026
Expert consensus on designing a metaverse supported blended EFL module in chinese higher education: A Fuzzy Delphi method.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 authors.
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Abstract
Metaverse technologies can provide immersive, interaction-rich experiences for English as a Foreign Language (EFL) learning, yet curriculum-level design principles and implementation guidance remain limited. This study developed, through expert consensus, a ranked blueprint for a metaverse-supported blended learning module for undergraduate EFL learners in Chinese higher education. Using an exploratory design, Phase 1 elicited candidate elements through semi-structured interviews with EFL instructors (n = 5), and Phase 2 applied the Fuzzy Delphi Method (FDM) with a 12-expert panel using a five-point Likert scale. Items were retained only if they met all prespecified criteria (Agreement ≥ 75%, interquartile range [IQR] ≤ 1.0, and fuzzy distance [d] ≤ 0.20). Retained items were prioritized by defuzzified value (DV), with ties resolved by IQR, then d, then Agreement. Actionable consensus was reached across six domains: learning objectives, learning content, instructional strategies, learning activities, assessment methods, and learning resources. Resampling-based stability checks (leave-one-out and bootstrap) supported the robustness of the induced priority ordering. Kendall's W indicated limited overall concordance across heterogeneous items; accordingly, item inclusion relied on the prespecified thresholds. The study contributes a replicable, ranked blueprint that embeds constructive alignment in immersive EFL contexts and provides an implementation-ready specification to support staged adoption and subsequent validation in higher education.
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