Actionable companion · Cognitive load & attention
Learning with agency: Virtual vs. standardized patients - a preliminary comparison of advantages and disadvantages of a VR and a conventional learning unit for medical students in child and adolescent psychiatry
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.
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, Higher education. Health-professions learning must be distinguished from K–12 instruction.
Original authors’ abstract, reproduced under the linked source license:
Abstract Background Constructivist learning theories are getting more and more attention in medical education, as generating understanding and knowledge through personal experience seems to be promising. In child and adolescent psychiatry, simulation-based training is challenging, as students’ access to real young patients is limited and there are no standardized patients of that age. Hence, we see Virtual Reality (VR) presenting virtual patients as a means to address these issues. VR enables the standardization of personal encounters in an adaptive learning environment that is cost-effective, scalable and applicable in a standardized way for different learners. Even though virtual patients have become more and more popular in medical education, less studies investigated the strengths and weaknesses of those compared to conventional standardized patients. Methods We present a within-subjects study with 50 students and compare our virtual patient system, a VR application that allows student to engage in a conversation with a virtual patient, with a conventional standardized patient unit. Students participated in small groups of up to five students alternately in the two units and filled out questionnaires regarding the estimated learning success, believability, empathy, and motivation subsequently. One student at a time conducted the interview with the virtual or standardized patient, while the others took on an observational role. Finally, all students were interviewed comparing both experiences. Results Results showed that the standardized patients were rated significantly higher in all dependent variables. Qualitative results highlight an inappropriate speech recognition system as main reason why the virtual patient system proved to be inferior. Furthermore, we identified aspects that demonstrate advantages as well as disadvantages for both units each. Conclusions In its current technical implementation, the virtual patient system could not match standardized patients in interactional and affective dimensions. Nonetheless, we identified several aspects, that could be beneficial over or supplementary to the use of standardized patients. Furthermore, we derived implications for the future design of virtual patient systems and in which situation they should be considered. Supplementary Information The online version contains supplementary material available at 10.1186/s12909-026-08760-4. Keywords: Teaching with technology, Educational intervention, Virtual patients, Emotional virtual agents, Virtual reality
What kind of evidence is this?
Intelligent tutoring & adaptive learning · Qualitative / mixed methods
Stage: Secondary school; 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
To evaluate our approach of using VR and virtual patients, we conducted a study and compared our VR learning unit with a conventional unit, using standardized patients. Thereby, we investigated student’s estimated learning success, believability of and empathy towards the respective patients, as well as students’ motivation during the units. Therefore, we used a mixed-method approach combining quantitative (questionnaires), qualitative (interviews) and objective measurements (interaction logs).
Limitations and uncertainty · source passage
The most significant limitation of our virtual patient system appears to be the insufficient speech recognition preventing the virtual patient from receiving a fair comparison to the standardized patient. The result can be described as the one problem that is most frequently documented in current virtual patient systems [15]. Our objective results align with students’ reports that no real interaction — for example, expressing empathy toward the patient — was possible in the conversations: Most errors appeared due to the system recognizing statements, such as “ehm” or “ok”, to agree with the virtual patient’s answer, already as a new question. The problems with the speech recognition thus led to a lack of conversational flow and interaction between the student and the virtual patient, resulting in a poor evaluation of the conversation in this unit, especially in direct comparison with the standardized patient. It is, therefore, not possible to determine exactly to what extent this problem influenced the overall evaluation of the virtual patient. In a next step, a revision of the speech recognition is, therefore, urgently needed, which could be achieved through the extended integration of AI [33, 34].
Design the system before the pilot
Document the learner model, mastery rule, hint sequence and adaptation signal. Compare adaptive routing with the same content in a non-adaptive sequence. Check whether early errors lead to persistent low-expectation pathways.
- Limit simultaneous instructions and unnecessary dialogue. Compare task performance and a suitable mental-effort measure; easier-feeling work is not automatically better learning.
- Measure engagement separately from achievement. Check whether novelty-driven participation persists and whether it translates to independent performance.
A 90-day district pilot
- 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.
- 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.
- 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.
- 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
Linda Graf; Vera Golz; Sophia Prehn; Maic Masuch; Gertraud Gradl-Dietsch. Virtual vs. standardized patients - a preliminary comparison of advantages and disadvantages of a VR and a conventional learning unit for medical students in child and adolescent psychiatry. BMC Medical Education (2026-02-17). https://doi.org/10.1186/s12909-026-08760-4
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.