The GAMSAT Section 3 (Reasoning in Biological and Physical Sciences) has undergone significant transformation over the past decade. While it once rewarded rote memorisation and textbook problem-solving, its modern form places a much stronger emphasis on higher-order reasoning, data interpretation, and adaptive thinking across unfamiliar contexts.
For aspiring medical students, this shift necessitates not only a change in what is studied, but also in how it is studied. In this article, I outline the key domains currently emphasised in Section 3, how best to approach them, and the rationale underpinning ACER’s evolving assessment design.
Although foundational scientific knowledge remains important, the most recent iterations of Section 3 reflect a clear preference for reasoning-oriented science over simple recall. Based on recent trends and curriculum alignment, the following themes are especially critical:
Both chemical and physical equilibria feature prominently, particularly in complex, multi-variable experimental contexts. Candidates are expected to interpret how perturbations (e.g. changes in pressure, concentration, temperature) affect dynamic systems, often through graphical or tabulated data.
Skills assessed: Qualitative trend analysis, mechanistic reasoning, understanding coupled systems
Common features: Titration curves, solubility equilibria, mechanics/kinetic comparisons
A distinct and growing emphasis is being placed on spatial cognition. These questions assess a candidate’s ability to mentally manipulate 2D and 3D structures—a skill crucial not only in biochemistry (e.g., chirality, molecular configuration) but also in anatomy and radiological interpretation.
Skills assessed: 3D mental rotation, structural matching, topological transformations
Common features: Folding nets, molecular conformation, isomer comparisons, stereochemistry
This is arguably the most defining feature of modern Section 3. Candidates are routinely presented with novel experimental setups, often adapted from real-world biomedical research or lab-based inquiry. The ability to extract patterns, interpret results, and make inferences from figures and tables is central to success.
Skills assessed: Quantitative reasoning, extrapolation, hypothesis testing
Common features: Dose-response curves, sigmoidal kinetics, enzyme inhibition models, physics-based motion graphs
While the GAMSAT is not a content-heavy exam in the traditional sense, a strong understanding of key concepts in chemistry, physics, and biology is still essential—particularly as they form the framework upon which reasoning questions are scaffolded.
Biology: Cell signaling, enzyme function, homeostasis
Chemistry: Acids and bases, redox reactions, organic mechanisms
Physics: Circuits, mechanics, thermodynamics, optics
However, the emphasis lies in application, not recall. Candidates are often required to integrate ideas across disciplines, interpret scientific methods, or critically analyse unexpected experimental results. Importantly, there is no background knowledge required and the relevant equations and rules are selectively distilled so only those important to the question are presented.
Success in Section 3 requires more than content familiarity. The exam is intentionally designed to challenge working memory, pattern recognition, and schema integration. The following strategies, informed by educational psychology and cognitive load theory, are particularly effective:
Rather than memorising isolated facts, focus on building interconnected frameworks of knowledge. This enables more efficient encoding and retrieval during high-stakes reasoning tasks.
Begin with worked examples
Transition to completion problems
Finish with full application in unseen contexts
This approach, rooted in cognitive load theory, helps manage intrinsic load while promoting transferable learning.
Train yourself to rapidly extract surface-level patterns before engaging in deeper analysis. This mimics the two-pass strategy commonly used by high-performing students: first identify what is being assessed, then commit to detailed reasoning if warranted.
Expose yourself to diverse experimental formats—scientific abstracts, real graphs, research figures—to normalise unfamiliarity. Instead of focusing solely on GAMSAT-style questions, incorporate primary literature or problem-based learning cases into your preparation.
ACER’s assessment philosophy centres on evaluating readiness for clinical training. The modern GAMSAT does not reward those who merely memorise science—it rewards those who can think like scientists under time constraints.
This reflects the broader goal of medical education: to develop professionals who can interpret new information, reason through uncertainty, and apply knowledge flexibly across domains. Section 3 thus functions as a proxy for scientific reasoning, pattern recognition, and resilience in the face of cognitive complexity.
In short: it simulates the intellectual challenges encountered in clinical problem-solving, albeit through a scientific lens.
GAMSAT Section 3 has become a sophisticated measure of scientific reasoning. To perform well, candidates must shift from passive memorisation to active cognitive engagement. This involves mastering key scientific domains—particularly systems equilibrium, spatial reasoning, and data interpretation—while adopting evidence-based study techniques that align with how the brain learns.
Approached strategically, the modern GAMSAT becomes less a mystery and more a predictable, learnable challenge.
For students seeking a structured path through this complexity, programs that incorporate these cognitive and content principles—such as targeted workbooks, progressive difficulty scaling, and reasoning-based feedback—are likely to offer the most efficient returns on effort.
