Actionable companion · Assessment and evidence of learning

From evidence to district action: Toward sustainable aesthetic education: exploring the impact of GenAl collaboration on students’ critical thinking disposition

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.

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 Artificial intelligence (AI)-enabled tools have increasingly influenced artistic creation processes in aesthetic education. However, empirical evidence regarding their impact on students’ critical thinking disposition remains limited. This study examined whether integrating Generative Artificial Intelligence (GenAI) tools into an aesthetic learning workshop could enhance undergraduate students’ critical thinking disposition and explored the underlying mechanisms. Methods A mixed-methods design was employed. Sixty-three undergraduate arts and design students were randomly assigned to an experimental group (n = 31) or a control group (n = 32). Both groups participated in a two-week structured landscape sketching workshop, while only the experimental group was permitted to use GenAI tools, including image generation models and large language models, to support idea generation, visual experimentation, and iterative refinement. Critical thinking disposition was measured before and after the intervention using a standardized scale. Quantitative analyses included independent-samples tests and ANCOVA, while qualitative data were analyzed to identify learning mechanisms associated with GenAI use. Results The experimental group demonstrated significantly greater improvement in critical thinking disposition than the control group (p < 0.01, Cohen’s d = 0.70). Dimension-level analyses and ANCOVA further confirmed that these gains remained significant across multiple dimensions of critical thinking after controlling for baseline differences. Qualitative findings revealed three interrelated mechanisms contributing to these improvements: perceptual-conceptual alignment, iterative visual experimentation, and AI-mediated reflective structuring. Discussion The findings suggest that GenAI tools can function as cognitive amplifiers in aesthetic learning by promoting more analytical, iterative, and reflective creative practices. This study provides empirical support for the integration of AI tools in design education and offers practical implications for fostering higher-order thinking skills in workshop-based learning environments. Keywords: aesthetic education, critical thinking disposition, generative artificial intelligence, randomized controlled trial, thematic analysis

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

Huiying Liu; Tianyue Niu; Chen Shengyan; Patrick Pang; Ting Liu; Yiming Taclis Luo. Toward sustainable aesthetic education: exploring the impact of GenAl collaboration on students’ critical thinking disposition. Frontiers in Psychology (2026-06-17). https://doi.org/10.3389/fpsyg.2026.1852109

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.