From technology adoption to curricular coherence: technology-enhanced simulation as a bridge in health professions education

Synthesis: Herrera Alcaíno (2026) reframes the central question of Simulation in health professions education: not which technology to adopt, but how a sequence of simulated experiences is positioned so that foundational knowledge becomes knowledge-in-use, reasoning is tested across contexts, and performance accumulates toward professional practice. The study is a narrative review with structured literature identification rather than a systematic review, and its output is an author-derived framework — the Curricular Bridge Model — pitched at the meso level between single-scenario research and whole-program Curriculum Design. Its components are borrowed from Experiential Learning, deliberate practice, Feedback and programmatic Assessment scholarship; the claimed contribution is relational, specifying how preparation, varied performance, debriefing, renewed practice and bounded evidence connect over time. Technology, from extended reality to AI-enabled case generation, is treated as an amplifier of an identified pedagogical function and never as a source of value in itself, which is why instructional design carries the argument rather than the device list.

Key Findings

1. The review is a narrative synthesis, not a systematic one: identification ran May 2026 across PubMed/MEDLINE, Scopus, Web of Science, ERIC and Google Scholar, updated on 16 August 2026, with no record counts reported.
2. The gap is meso-level: scenario research asks how one simulated encounter should be designed, curriculum models ask how programs are built, and neither explains how multiple simulation experiences are intentionally connected across a trajectory.
3. Curricular purpose precedes technology selection. Alignment between an identified educational function and what a tool can do determines value more plausibly than sophistication, fidelity or immersion, which are not proxies for learning.
4. Repetition requires variation. Because clinical reasoning is context-sensitive, rehearsing one case builds fluency under those conditions rather than transferable competence, so sequences must vary presentation, cues, uncertainty, team configuration and constraints.
5. Simulation-generated evidence is bounded and complementary: performance under simulated conditions is evidence about those conditions, not generalized competence, and performing an entrustable professional activity in simulation is not entrustment to perform it unsupervised.
6. Implementation conditions are constitutive: equity, faculty capability, governance, infrastructure, scalability and sustainability decide whether the intended relationships occur at all, and the model states these as seven propositions awaiting external scrutiny.

Repetition without variation teaches fluency, not adaptation

Deliberate practice and Mastery Learning supply the most mature evidence base in the review, and both depend on performance standards, specific feedback, correction and renewed attempts. The review then imports context-specificity findings to bound that logic: reasoning varies when patient, clinician, environmental or situational features change, and context can be constitutive of how a situation is represented rather than noise around a stable skill. Repeating an identical scenario rehearses that scenario, not the reasoning behind it. Meaningful variation — presentation, cues, uncertainty, competing priorities, team composition, management constraints — is what forces reconsideration of what transfers and what must be adapted. That is the mechanism behind the claim that a connected sequence produces something a series of isolated events cannot, and it is why Transfer of Learning is treated as an open question rather than a by-product of repetition.

What simulation evidence can and cannot carry

The review is unusually careful about the assessment claim. Simulation can sample technical execution, reasoning, communication and responses to uncommon events under controlled conditions, and standardization improves comparability. It cannot reproduce clinical responsibility, consequences, organizational pressure or the relational texture of workplace practice. Programmatic assessment supplies the logic for interpreting multiple data points over time; simulation supplies some of those data points, not the verdict, and Assessment Validity has to be argued for the intended inference rather than assumed from consistency. The same caution applies to interprofessional work, where team performance emerges from interaction and cannot be decomposed into individual scores, and to automated assessment, where output does not become valid because it is reproducible. The worked example is a Canadian emergency medicine study in which competency standards were used to map scenarios to required experiences while participants worried that growing assessment functions could erode the psychological safety the same simulations were meant to protect.

Technology as amplifier, and the conditions that decide

Across modalities the review applies one test: does the tool create the conditions the targeted learning requires? Virtual patients extend access to repeated, standardized encounters, but the category spans branching cases and conversational agents whose designs differ too much to generalize across. Extended reality supports spatial, perceptual and psychomotor learning where representation or immersion does necessary work, and systematic reviews do not support the assumption that more immersion yields more learning. AI extends possibility through responsiveness and generativity, yet evidence remains thin: a 2025 systematic review found measurable outcome evidence limited and heterogeneous, and a scoping review of AI-supported debriefing identified seven studies published between 2023 and 2026, mostly reporting feasibility, usability and perceived value, with AI positioned as an adjunct to human facilitation. The conditions are equally unsentimental: equity as a design condition rather than an afterthought, faculty capability as ongoing institutional capacity, and governance specified down to expert review of generated cases before learner exposure.

What this means for practice

• Instructors. Audit a simulation you already run and name the educational function it serves before defending the equipment; then check whether the debrief produced a changed next attempt rather than a satisfying conversation.
• Curriculum designers. Map where simulation sits across the program and hunt for missing links: preparation that never connects to practice, repeated cases that never vary, evidence that never reaches a progression decision.
• Faculty developers. Treat facilitation, psychological safety, observation and evidence interpretation as continuing institutional capability rather than a prerequisite ticked once at hiring, since technologies redistribute rather than remove the need for expertise.
• Administrators. Fund the unglamorous conditions — accessibility, maintenance, licensing, faculty time and governance — because a coherent sequence that is inaccessible, fragile or ungoverned cannot function as curricular infrastructure.

Limitations

• The review is a narrative synthesis by a single author, without independent duplicate screening or charting, and no formal risk-of-bias instrument was applied across its heterogeneous sources.
• The original search was not kept as a deduplicated corpus and preserved neither day-level timestamps nor complete database strings for the May 2026 searches, which is why no screening counts appear.
• The Curricular Bridge Model is unvalidated; the author states that the seven propositions make it examinable and that plausibility of components is not evidence of effectiveness.
• Generative AI was used during manuscript development for language refinement, editorial organization, literature-mapping support and draft figures, and framing influence on salience cannot be excluded.

Citation

Herrera Alcaíno, Á. A. (2026). From technology adoption to curricular coherence: technology-enhanced simulation as a bridge in health professions education. Frontiers in Education.