Agentic education · Learning science

Actionable companion · Self-regulation & metacognition

Learning with agency: Effects of an AI-enhanced BOPPPS teaching model in nursing courses: a meta-analysis of randomized controlled trials

AI-assisted editorial implementation guide, separate from the original research. Proposed actions are not claims or recommendations attributed to the source authors. No independent peer review of this guide is asserted.

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Evidence and context

Title and abstract screening; stage labels describe reported settings, not verified numerical ages. Design labels require full-text appraisal. Reported stage(s): Higher education. Health-professions learning must be distinguished from K–12 instruction.

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

Aim To evaluate the effectiveness of an artificial intelligence (AI)–enhanced BOPPPS teaching model in nursing courses, with a focus on academic performance, self-directed learning ability, and teaching satisfaction. Design Systematic review and meta-analysis of randomized controlled trials (RCTs) conducted in accordance with PRISMA and registered in INPLASY (INPLASY202590123). Methods Chinese- and English-language databases were searched for eligible RCTs comparing AI-enhanced BOPPPS with traditional teaching (or BOPPPS alone). Data extraction and risk-of-bias assessment followed Cochrane guidance. Pooled analyses were performed using standardized mean difference (SMD) for continuous outcomes and risk ratio (RR) for dichotomous outcomes, with heterogeneity assessed using I2. Results Four RCTs involving 459 nursing students were included. Academic performance showed a significant improvement in the AI-enhanced BOPPPS group (SMD = 1.06, 95% CI 0.63–1.48; p < 0.05), with substantial heterogeneity. With substantial heterogeneity. Self-directed learning ability (3 studies; “excellent” category) was significantly improved in the AI-enhanced BOPPPS group (RR = 3.28, 95% CI 2.14–5.02; p < 0.001) with no heterogeneity. Teaching satisfaction was also significantly higher with AI-enhanced BOPPPS (RR = 1.80, 95% CI 1.27–2.55; p < 0.001), with low-to-moderate heterogeneity. Conclusion AI-enhanced BOPPPS teaching demonstrates consistent benefits in improving nursing students’ academic performance, self-directed learning ability and teaching satisfaction, these findings support the potential value of integrating AI into structured instructional design to enhance learning processes and student experience in nursing education. Systematic review registration https://inplasy.com/inplasy-2026-2-0026/, Identifier: INPLASY202620026.

What kind of evidence is this?

Supporting AI learning science · Evidence synthesis

Stage: Higher education. Screening labels describe reported context and study-design language. They are not a risk-of-bias rating or proof of effectiveness for an age band.

Study methods · source passage

This systematic review and meta-analysis was conducted in strict accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (10). PRISMA provides an evidence-based minimum set of reporting standards for systematic reviews and meta-analyses. The complete PRISMA checklist has been submitted as Supplementary material.

Limitations and uncertainty · source passage

Although the findings of this study offer meaningful insights, the current evidence should be interpreted with caution due to several limitations. First, the number of included studies was small, and most were single-center trials, which may limit the generalizability of the results. Second, there is no standardized approach to AI integration across studies; differences in the intensity and depth of the intervention, instructors’ technical proficiency, and classroom contexts may have contributed to variability in outcomes. Third, most studies evaluated only short-term interventions and lacked follow-up on long-term learning trajectories, clinical internship performance, critical thinking, and clinical competence—outcomes that are central to nursing education. In addition, blinding was inadequately implemented in some trials, which may have introduced observer bias. These issues highlight the need for more rigorous study designs in future research.

Design the system before the pilot

Use this study to inform a learning mechanism or implementation question. It is not direct evidence that autonomous agents improve learning. Keep the proposed agent behavior separate from what the source actually tested.

  • Use plan–attempt–check–reflect prompts and compare confidence with actual performance. Keep learner choice and reflection visible.
  • Use common rubrics, blind scoring where feasible and a fresh unaided reasoning task. Document permissible assistance and avoid treating AI-detector scores as proof of misconduct.

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. Choose one disciplinary task. Require a first attempt, a documented AI consultation, a critique of the output and an independent explanation. Align the comparison group and scoring rubric with the same objective. 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 and accuracy on a new task without AI. Distinguish model examination scores, student perceptions and actual learner gains; only the last directly tests educational benefit. 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

Huiling Zhang; Zheyuan Xia; Yahui Meng; Shuang Yu; Hui Shi. Effects of an AI-enhanced BOPPPS teaching model in nursing courses: a meta-analysis of randomized controlled trials. Frontiers in Medicine (2026-02-18). https://doi.org/10.3389/fmed.2026.1767911

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.