Factors influencing nursing students' intention to accept metaverse-based blended learning nursing anatomy classes based on technology acceptance model 2 in Korea: a cross-sectional study

Purpose: This study aimed to identify the factors influencing nursing students’ intention to use metaverse-based blended learning in nursing anatomy classes by applying the technology acceptance model 2 (TAM 2). Methods: This descriptive survey study included 155 students from a nursing college in Seoul. TAM 2 comprised 25 items measured on a 5-point Likert scale, encompassing subjective norm, image, job relevance, output quality, result demonstrability, perceived ease of use, perceived usefulness, and intention to use. Hierarchical regression analysis was performed to identify factors affecting students’ intention to use metaverse-based learning. Results: In regression model 1, which included general and metaverse education-related characteristics, the factors significantly influencing the intention to use were the perceived necessity of metaverse education (β = .59, p < .001) and having more than three semesters of metaverse experience (β = −.22, p = .010), explaining 41.0% of the variance. When TAM 2 variables were added (model 2), significant predictors included perceived necessity of metaverse education (β = .26, p = .004), perceived ease of use (β = .33, p < .001), and perceived usefulness (β = .48, p < .001), explaining 76.0% of the variance. Conclusion: To promote effective use of the metaverse platform in nursing education, strategies that enhance students’ perceived usefulness and ease of use are essential. Educational interventions should focus on improving familiarity with metaverse technologies to facilitate their integration into nursing curricula.