A sociotechnical typology of AI use in educational information practices under conditions of war
DOI:
https://doi.org/10.47989/ir31263119Keywords:
artificial intelligence, information literacy, educational information practices, sociotechnical approach, AI use in education, critical reflection, automation and control, information risk, high-risk information environments, wartime educationAbstract
Introduction. In the era of generative AI, information literacy increasingly depends on how educators integrate AI into educational information practices. In high-risk contexts, such as war, where informational uncertainty and manipulation intensify, distinguishing between critically reflective modes of AI use and instrumental-operational or control-oriented modes becomes particularly important.
Method. This study draws on a survey of 208 educators from frontline regions of Ukraine. Educational information practices were operationalised through two composite indices: one capturing critically reflective AI use and the other capturing instrumental-operational and control-oriented uses of AI. A 2×2 typology was constructed using median splits and validated through k-means clustering (k = 5), with silhouette scores indicating moderate but meaningful cluster separation.
Analysis. AI use practices were operationalised through two composite indices: critically reflective use (CR_index; α = 0.868; ω = 0.869) and instrumental-operational and control-automation use (Control_index; α = 0.769; ω = 0.789). A 2×2 typology of models (CR × Control) was constructed using median splits and its robustness was tested via k-means clustering (k = 5). Associations between models and respondent characteristics were assessed using χ² tests with Cramér’s V.
Results. Four models of AI use were identified: critically reflective (14.4%), hybrid (36.1%), instrumental–control (17.3%), and low integration (32.2%). Results showed that critically reflective and operational uses frequently coexist, particularly in the dominant hybrid model. Robustness checks (clustering and rank correlations) confirmed the stability of the identified configurations.
Conclusion. The findings demonstrated that AI integration in education is shaped by a sociotechnical tension between critical engagement and operational efficiency and control. In wartime conditions, critically reflective practices function as mechanisms of epistemic security. The study contributes an empirically grounded typology that can inform institutional policy and professional development in high-risk information environments.References
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