The Future of Education

This study examines how age and prior educational technology experience influence technostress and behavioral intention to adopt Artificial Intelligence tools among educators. Grounded in Person-Environment Fit Theory, survey data from 105 educators participating in AI-integrated professional development revealed a complex, non-linear relationship between age and technology-related stress. Contrary to the prevalent "digital native" assumption, middle-aged educators (40–49) exhibited the highest technology-related stress levels, while both younger (under 30) and older (over 60) educators reported significantly lower stress. Prior EdTech experience was positively associated with technology efficacy and negatively associated with both stress and burnout, suggesting foundational technology skills create a protective buffer against AI adoption challenges. Surprisingly, prior technology experience did not predict behavioral intention toward AI adoption, indicating that willingness to use AI tools may depend on factors beyond traditional digital comfort—possibly including perceived relevance, institutional support, or recognition that AI represents a qualitatively different technological paradigm. These findings have significant implications for teacher professional development: programs must move beyond one-size-fits-all approaches toward age-differentiated strategies, with particular attention to mid-career educators facing unique pressures. The research extends Person-Environment Fit Theory to AI-enhanced educational contexts and provides evidence-based recommendations for supporting sustainable AI integration in education.

Keywords: technostress, AI adoption, teacher professional development, person-environment fit, educational technology, faculty development

REFERENCES

[1] Wang, X., & Li, B. (2019). Technostress among university teachers in higher education: A study using multidimensional person-environment misfit theory. Frontiers in Psychology, 10, 1791.

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