Exploring the public's beliefs, emotions and sentiments towards the adoption of the metaverse in education: A qualitative inquiry using big data

Abstract

The metaverse is rapidly reshaping our understanding of education, yet identifying the public's beliefs, emotions and sentiments towards its adoption in education remains largely uncharted empirically. Grounded in the Technology Acceptance Model (TAM) and Digital Diffusion Theory (DOI), this paper aims to fill this gap using a big-data approach and machine learning to scrape comments made by social media users on recent popular posts or videos related to adopting the metaverse in education from three prominent social media platforms. The cleaning process narrowed down 11,024 comments to 4277, then analysed them using thematic, emotion and sentiment analysis techniques. The thematic analysis revealed that adopting the metaverse in education evokes a complex range of public beliefs: (1) innovative learning methods; (2) accessibility and inclusion; (3) concerns about quality and effectiveness; (4) technological challenges and the digital divide; (5) the future of work and skills; and (6) privacy and security concerns. Integrating these themes with emotion and sentiment analyses reveals a landscape of a significant portion of neutral sentiments that corroborates enthusiasm attenuated by caution. This careful consideration stresses the urgent need for a balanced approach to adopting the metaverse in education to ensure that resulting educational advancements benefit all learners equitably. As one of the first studies to offer a multidimensional view of the public's beliefs about metaverse education using big data, this research not only contributes to TAM and DOI but also provides critical insights that could inform policy, enhance educational practices and guide future scholarship in this emerging field.