Generative AI · Education leadership

Actionable companion · Staff capability and AI literacy

From evidence to district action: From Adoption to Continuance: A Longitudinal Qualitative Exploration of University EFL Teachers’ Motivation for Continued Use of GenAI Based on Self-Determination Theory

AI-assisted editorial implementation guide. The district actions are proposed applications, not findings or recommendations attributed to the original authors. No additional peer review is asserted.

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Evidence and context

Confirm the study population, setting and task before applying its findings to your district.

Original authors’ abstract, reproduced under the linked source license:

Generative artificial intelligence (GenAI) has been rapidly integrated into higher education, yet current studies largely rely on quantitative frameworks that capture initial adoption, leaving university EFL teachers’ motivational evolution for continued use of GenAI underexplored. To address this gap, this longitudinal qualitative study explores the motivational evolution and psychological need experience of 15 university EFL teachers’continued use of GenAI grounded in Self-Determination Theory (SDT). Data were collected through two rounds of semi-structured interviews over one year and analyzed in NVivo 11 PLUS. Our findings reveal a dynamic evolution of motivation from external regulation to value identification and professional identity integration. Crucially, need satisfaction and need frustration provide important psychological foundations for teachers’ motivation internalization. Notably, while need satisfaction directly facilitates university EFL teachers’ continued use of GenAI, need frustration can actually act as a potential catalyst that facilitates EFL teachers to form long-term continued use of GenAI through iterative reflection and instructional adjustment. This study extends the application of SDT within the GenAI education context, indicating that university EFL teachers’ continued use of GenAI is not merely a process of technology adoption, but also a process of professional growth and professional identity integration. The results provided preliminary implications for teacher professional development, GenAI design and education policy.

A 90-day district pilot

  1. Days 1–15 · Appraise. Have the curriculum lead and a teacher read the methods and limitations. Record the study design, sample, comparator, outcomes and evidence gaps. Define a local question that the study can help inform.
  2. Days 16–30 · Design. Run a staff workshop using three authentic lesson-planning tasks. Ask participants to identify hallucinations, revise outputs and document when they reject the tool. Name an accountable owner and set the baseline, success threshold and budget before implementation.
  3. Days 31–60 · Test. Start with a small voluntary cohort, preserve an accessible non-AI route and require teacher review. Use synthetic or de-identified examples; approve data handling and tool terms through district processes.
  4. Days 61–90 · Decide. Measure error-detection accuracy before and after training, preparation time and the quality of the final lesson plans. Compare with baseline, document uncertainty and stop or revise if learning worsens, access is unequal or critical errors persist.

The board decision brief

Report the learning problem, evidence quality, participating population, total cost including review time, measured benefit, errors, access differences and remaining uncertainties. Make a dated recommendation to stop, revise or expand. A positive perception survey alone does not establish learning improvement.

Attribution and reuse

Chunhua Mao; Yonghong Zeng. From Adoption to Continuance: A Longitudinal Qualitative Exploration of University EFL Teachers’ Motivation for Continued Use of GenAI Based on Self-Determination Theory. Behavioral Sciences (2026-08-14). https://doi.org/10.3390/bs16081396

Companion prepared 2026-10-30. Original authorship and DOI are preserved. The abstract is an attributed source extract; the implementation plan is new AI-assisted editorial material, offered under the same CC BY 4.0 license. This guide has not undergone independent peer review.