Generative AI · Education leadership

Actionable companion · Assessment and evidence of learning

From evidence to district action: Pre-service mathematics teachers' use of artificial intelligence: an extended technology acceptance model with self-efficacy (the case of ChatGPT)

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:

Abstract Introduction This study examines pre-service mathematics teachers' use of ChatGPT in instructional processes within the framework of the Technology Acceptance Model (TAM), extended with pedagogical AI self-efficacy. The study investigates the relationships among perceived ease of use, perceived usefulness, attitudes toward use, actual use, and self-efficacy regarding the use of ChatGPT in mathematics teaching. Methods The study was conducted with 167 pre-service mathematics teachers. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results The findings revealed that perceived ease of use significantly predicted perceived usefulness (β = 0.648, p < 0.001) and directly influenced actual use (β = 0.311, p < 0.001). Perceived usefulness significantly predicted attitudes toward use (β = 0.638, p < 0.001), while attitudes toward use significantly affected actual use (β = 0.399, p < 0.001). In addition, pedagogical AI self-efficacy strongly predicted perceived ease of use (β = 0.647, p < 0.001) and indirectly contributed to technology acceptance. Discussion The findings confirm the explanatory power of TAM in the context of generative AI tools and highlight the critical role of self-efficacy in shaping pre-service teachers' acceptance of ChatGPT. The study provides important implications for the integration of AI tools into mathematics teacher education and supports the pedagogically grounded use of generative AI in teaching practices. Keywords: artificial intelligence, ChatGPT, pre-service mathematics teachers, self-efficacy, technology acceptance model

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. Redesign one low-stakes assessment: require a first attempt, an AI-assisted revision, a source-check log and a short oral explanation. Use the same rubric for the comparison task. 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. Blind-score reasoning, factual accuracy and unaided transfer on a fresh task. Record suspected misconduct separately from demonstrated evidence. 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

Baris Demir. Pre-service mathematics teachers' use of artificial intelligence: an extended technology acceptance model with self-efficacy (the case of ChatGPT). Frontiers in Psychology (2026-05-28). https://doi.org/10.3389/fpsyg.2026.1826980

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.