Agentic education · Learning science

Actionable companion · Self-regulation & metacognition

Learning with agency: Online tool for adolescents' self-control practice: a pilot study

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): Secondary school. Verify the participant population and task before transferring the findings.

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

Self-control is essential for youth navigating today’s technological and lifestyle challenges. Artificial intelligence (AI) offers scalable, personalized approaches to improve self-regulation through medical and educational interventions. This pilot research was conducted over a period of five months and structured into two studies, each comprising four phases. The first study included 180 adolescents, divided into two equal samples, to examine whether impulsivity varies according to high school profile. One group was drawn from Grigore Moisil Informatics College (theoretical high school), and the other from the National College of Arts Dinu Lipatti (vocational arts high school). Impulsivity was initially assessed using the Barratt Impulsiveness Scale (BIS). Drama students showed significantly higher levels of impulsivity, guiding the development of a targeted AI-driven (neural network-based) self-control intervention. The second study focused on the drama student cohort. Over the course of three months, the group participated in an online, AI-guided self-control education program. BIS was re-administered at the end of the intervention to measure changes. Pre-intervention data confirmed significantly higher impulsivity among drama students. Following the AI-based intervention, the group showed statistically significant improvements in self-control. The findings support the effectiveness of AI tools in fostering self-regulatory skills among adolescents and highlight their potential in health education and mental wellness, especially for anxiety, behavioral issues, and mild depression. The AI-guided, game-based cognitive training significantly reduced impulsivity in drama students, demonstrating its promise as a tool for improving adolescent self-control and psychological resilience.

What kind of evidence is this?

Supporting AI learning science · Design requires full-text appraisal

Stage: Secondary school. 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

The study sample consisted of 180 adolescents aged between 14 and 17 years, with an equal gender distribution (1:1 ratio). Of these, 90 participants were first-year high school students enrolled in the dramatic arts program at the National College of Arts Dinu Lipatti, while the remaining 90 were students at the Grigore Moisil Informatics College, both located in Bucharest, Romania. Participant selection was based on voluntary enrollment.

Limitations and uncertainty · source passage

While the findings offer positive insights into the potential of AI-supported cognitive training for reducing impulsivity in adolescents, several limitations should be noted. First, the absence of a control group limits the ability to fully distinguish the specific effects of the intervention from natural developmental changes or external influences.

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. Ask learners to attempt a problem unaided, compare an agent hint, explain a revision and verify the final reasoning against a trusted source. Make the permitted use explicit for each assignment. 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 unaided transfer and delayed retention, calibration of confidence and the ability to identify an incorrect AI explanation. Record whether help-seeking becomes answer copying. 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

Alina Mihaela Munteanu; Teodor-Cristian Radoi; Adina Baciu; Cristiana Susana Glavce; Suzana Turcu. Online tool for adolescents' self-control practice: a pilot study. Journal of Medicine and Life (2025-09-01). https://doi.org/10.25122/jml-2025-0115

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.