Problem-Based Learning Tops the Ranking When Anesthesiology Faculty Weigh How to Teach

Choosing how to teach anesthesiology is not a trivial decision. The specialty demands rapid decision-making under pressure, flawless teamwork in the operating room, and the ability to solve clinical problems that rarely arrive in tidy textbook form. Yet medical schools around the world continue to divide their teaching hours among three very different methods: the traditional lecture, the flipped classroom in which students study content before class and spend contact time applying it, and problem-based learning, which anchors the entire learning experience to authentic clinical cases. A new study published in BMC Medical Education has now brought formal decision science to bear on this perennial pedagogical dilemma, asking anesthesiology faculty themselves to weigh the alternatives and producing a quantitative ranking that could reshape how departments allocate their teaching resources.

The research team, led by Tara Soleimani and colleagues at Kashan University of Medical Sciences and partner institutions across five Iranian universities of medical sciences, applied a family of techniques known collectively as multi-criteria decision analysis, or MCDA. Rather than asking faculty which teaching method they simply prefer, the approach forces a structured comparison of methods against explicit evaluation criteria, each assigned a numerical weight. The result is not an opinion poll but a transparent, reproducible scoring system in which every judgment is documented, every weight is justified, and the final ranking can be stress-tested to see whether it survives changes in assumptions. It is the same analytical machinery used in engineering, healthcare resource allocation, and environmental policy, here turned on the classroom.

The study’s first task was to decide what actually matters when judging a teaching method. The researchers conducted a scoping review of studies published between 2011 and 2025, following the PRISMA-ScR reporting guidelines to systematically identify evaluation criteria that previous educational research had deemed important. They then convened an expert panel of medical education specialists to refine this long list into a workable framework: seven domains containing 25 items in total. The resulting researcher-made instrument underwent formal face and content validation, with the team reporting content validity ratios and item-level content validity indices to demonstrate that experts agreed the items were relevant, clear, and essential. Only criteria that survived this statistical scrutiny were carried forward into the weighting phase.

With the criteria framework established, the study moved to its analytical core. Five experts completed pairwise comparisons, judging the relative importance of the criteria two at a time, and these judgments were analyzed using the fuzzy analytic hierarchy process, or FAHP. The fuzzy variant is a meaningful refinement of the classical method developed by Thomas Saaty in the 1970s. Instead of forcing experts to commit to a single crisp number when comparing two criteria, FAHP allows responses to be expressed as triangular fuzzy numbers, which capture a range of uncertainty around each judgment. Human evaluators are notoriously imprecise when asked whether one criterion is, say, exactly three times more important than another; fuzzy mathematics absorbs that hesitation rather than discarding it. The team also computed consistency ratios for both the middle values and the geometric mean bounds of the fuzzy judgments, ensuring that the pairwise comparisons were internally coherent rather than contradictory.

The weighting results are revealing in themselves. Quality of the educational experience received the highest weight at 0.2987, followed by perceived effectiveness at 0.2292 and interaction at 0.1795. Together, these three domains account for roughly seven-tenths of the total decision weight, a clear signal that the faculty experts prioritized the depth and impact of learning over logistical convenience. Two criteria were explicitly treated as cost factors, where lower values are better: time limitation and the need for technology. This is a crucial design choice, because a teaching method that scores brilliantly on engagement but consumes scarce faculty hours or demands infrastructure a department lacks must be penalized accordingly. The framework does not pretend that resources are unlimited; it builds scarcity directly into the arithmetic.

The second analytical stage, simple additive weighting or SAW, translated these weights into a final ranking. Fifteen faculty members who had at least three years of teaching experience and hands-on familiarity with all three methods rated how well each method performed on each criterion. The study deliberately required prior use of lecture, flipped classroom, and problem-based learning, so the ratings reflect lived experience rather than secondhand impressions. Each method’s scores were multiplied by the domain weights and summed, with the cost criteria subtracted in the appropriate direction. Problem-based learning emerged decisively in first place with a weighted score of 0.9701, the flipped classroom followed closely at 0.9148, and the traditional lecture trailed at 0.6068. The gap between the two active-learning formats was narrow; the gap between active learning and lecturing was not.

Dissecting the contributions behind the scores shows why the ranking came out as it did. Problem-based learning produced the largest weighted contributions in four of the seven domains: quality, interaction, perceived effectiveness, and performance. This aligns with what educational theory would predict, since PBL is explicitly engineered to place learners in the driver’s seat, forcing them to reason through clinical uncertainty, articulate their reasoning to peers, and defend their decisions. The flipped classroom claimed the largest contribution in flexibility, a reflection of its hybrid design that decouples content delivery from class time and lets students control the pace of their initial learning. The lecture, meanwhile, dominated in only one domain: availability. It remains the cheapest and most logistically forgiving method ever devised, capable of reaching unlimited numbers of students with minimal technology and preparation. The lecture’s problem is not that it does nothing well, but that what it does well matters least to the experts who weighted the criteria.

A ranking is only as credible as its robustness, and the researchers subjected theirs to an unusually thorough battery of sensitivity analyses. They varied the weights of all seven domains and found that the ordering of the three methods remained unchanged in every scenario examined. They examined rater-specific rankings individually and found high agreement among the fifteen faculty evaluators, quantified by Kendall’s coefficient of concordance of 0.804 with a p-value below 0.001, indicating that the consensus was statistically strong rather than an artifact of averaging. Finally, they ran 10,000 bootstrap resamples of the data, and problem-based learning retained its first-place position in 99.99 percent of them. For a field in which teaching recommendations often rest on single-institution surveys or narrative opinion, this level of analytical resilience is notable.

The authors are careful about what their findings do and do not establish. This is a faculty-perspective study, a cross-sectional snapshot of expert judgment rather than a measurement of what students actually learn. The conclusions explicitly call for prospective studies to evaluate learner outcomes and clinical competence, acknowledging that the ultimate test of any teaching method is whether it produces safer, more capable anesthesiologists. The framework is also context-specific, built from criteria identified in a scoping review and weighted by experts within a particular set of institutions, so departments elsewhere would need to consider their own educational priorities, available resources, and implementation conditions before importing the ranking wholesale. What the study offers is not a mandate but a decision-support tool: a validated, transparent method that any department could replicate with its own faculty and its own constraints.

Even with those caveats, the implications are hard to ignore. Anesthesiology education is a domain where the stakes of poor preparation are measured in operating room outcomes, and where simulation, case discussion, and team training have long been recognized as essential. A formal analysis showing that experienced faculty, when forced to weigh quality, effectiveness, and interaction against time and technology costs, place active learning far above the lecture adds quantitative weight to the ongoing shift away from passive instruction. The near-tie between problem-based learning and the flipped classroom is perhaps the most practically useful finding, because it suggests departments lacking the resources for full PBL implementation can capture much of the benefit through the more flexible flipped format. As medical schools worldwide confront crowded curricula, constrained budgets, and rising expectations for competency-based training, this study demonstrates that the choice of teaching method need not be a matter of tradition or taste. It can be measured, weighted, stress-tested, and decided, one transparent criterion at a time.

Subject of Research: Multi-criteria decision analysis of faculty priorities for lecture, flipped classroom, and problem-based learning in anesthesiology education

Article Title: Faculty priorities for lecture, flipped classroom, and problem-based learning in anesthesiology education: a fuzzy AHP–SAW multi-criteria decision analysis

Article References: Soleimani, T., Akbari, H., Hajijafari, M., Raeyat Mohtashami, A., & Mahdian, M. (2026). Faculty priorities for lecture, flipped classroom, and problem-based learning in anesthesiology education: a fuzzy AHP–SAW multi-criteria decision analysis. BMC Medical Education. https://doi.org/10.1186/s12909-026-10555-6

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10555-6

Keywords: anesthesiology education, problem-based learning, flipped classroom, lectures, multi-criteria decision analysis, fuzzy analytic hierarchy process, simple additive weighting, medical education, active learning, faculty priorities, decision support, teaching methods