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Technology integration in higher education has been widely recognised for its multifarious benefits. Nevertheless, arising from various factors, the prevalence of technostress poses a substantial impediment to learning effectiveness. In response, this study employs visualisation analysis and systematic review techniques to formulate a comprehensive model that encompasses variables related to technostress. Based on a systematic selection from 1,861 publications, 83 publications were included to model predictors and outcomes of higher-education students' technostress. Our findings reveal that the COVID-19 pandemic has spurred growing academic interest in technostress, owing to concerns about the stressful and anxious nature of remote learning. Existing research on this topic predominantly relies on technology acceptance models and theories, with ongoing expansions incorporating variables from multiple research domains. In particular, external factors assume pivotal roles as predictors of technostress, along with subdimensions related to technostress. The impact of technostress can be observed in various aspects, such as learning experiences and performance outcomes. The findings of this study provide valuable insights for future research endeavours, facilitating further exploration and informing technology-enhanced teaching practice.
Yu-peng et al. (Mon,) studied this question.