Biomedical engineering students are being asked to do more than follow laboratory instructions: they must learn how to think like scientists. A new teaching initiative from researchers at the National University of Singapore uses a web-based cell biology simulator to bring that challenge into a virtual classroom. The approach combines the Technological Pedagogical Content Knowledge framework, known as TPACK, with a four-stage guided inquiry model to help postgraduate students practise experimental design, interpret evidence and defend scientific conclusions. The work, published in Biomedical Engineering Education, suggests that virtual laboratories can become far more than digital substitutes for equipment when they are deliberately designed to target higher-order reasoning.
The educational problem addressed by the study is widespread across biomedical engineering. Traditional laboratory classes are effective for teaching procedures such as preparing samples, operating instruments and collecting measurements, but students may still struggle to understand why an experiment is designed in a particular way or how evidence supports a scientific claim. Physical laboratories can also be limited by cost, time, safety requirements, equipment availability and the number of students who can work simultaneously. Virtual simulations remove many of these barriers, allowing learners to repeat experiments, test alternative conditions and examine outcomes without consuming reagents or risking damage to expensive equipment. However, the researchers argue that technology alone does not automatically produce scientific thinking. Without careful instructional support, students may simply click through a simulation and reproduce procedures without developing the ability to connect data with theory.
The initiative centred on StarCellBio, an online experimental simulator originally developed through an MIT-supported educational project. The platform is designed to represent cell biology experiments in an interactive environment, enabling users to manipulate experimental conditions and observe simulated results. For the activity described in the study, students investigated cell-cycle regulation, a fundamental area of biology with direct relevance to cancer research, regenerative medicine, developmental biology and therapeutic design. The cell cycle is controlled by a network of regulatory proteins and checkpoints that determine whether a cell grows, duplicates its DNA, divides or pauses in response to damage. Understanding these processes requires more than memorising molecular names: students must reason about variables, controls, expected outcomes and the relationship between cellular mechanisms and observed data.
The course designers structured the activity around a 4D Guided Inquiry model: Discover, Design, Develop and Defend. In the Discover phase, students explored the biological problem and identified the concepts needed to understand cell-cycle regulation. They then moved to Design, where they formulated an experimental plan, selected relevant variables and considered how controls could distinguish among competing explanations. During Develop, students carried out the virtual experiments in StarCellBio and collected data. Finally, in Defend, they were expected to interpret their findings, relate them to the underlying biology and justify their conclusions using evidence. This sequence was intended to shift the learner’s role from passive recipient of instructions to active investigator responsible for explaining what the results mean.
TPACK provided the broader design principle for linking the simulation to teaching practice. The framework describes the intersection of technological knowledge, pedagogical knowledge and content knowledge. Technological knowledge concerns how the digital tool works and what kinds of experimentation it makes possible. Content knowledge involves the biological principles of cell-cycle regulation. Pedagogical knowledge determines how students are guided, questioned and assessed as they work through the task. The important feature is not the presence of these three forms of knowledge separately, but their integration. A simulator may accurately model a biological system, yet still be educationally weak if students do not receive prompts that expose misconceptions, compare hypotheses or require them to explain why a control is necessary.
In practical terms, the TPACK-based activity treated the simulator as a space for inquiry rather than as a virtual demonstration. Students were required to make decisions about their experiments and record their reasoning in laboratory handouts. Such documentation can reveal whether a learner understands the logic of an investigation: identifying an independent variable, predicting a dependent outcome, maintaining appropriate controls and distinguishing correlation from causation. In a cell-cycle experiment, for example, a student might need to predict how altering the activity of a regulatory protein would affect the distribution of cells across different stages of the cycle. The value of the exercise lies not only in obtaining a result, but in explaining whether that result supports the original hypothesis and whether alternative interpretations remain possible.
The researchers evaluated the activity through students’ laboratory handouts, their perceptions of the learning outcomes and their experience using StarCellBio. Most students were able to perform the simulated experiments and collect data successfully. They also described the platform as user-friendly and considered it an authentic environment for carrying out scientific investigations. According to the study, learners felt that the simulator encouraged critical thinking about experimental choices and supported scientific inquiry. These responses are important because usability is a practical requirement for any educational technology. If students spend most of their time struggling with navigation, the technology can overwhelm the scientific objective. A clear interface, by contrast, allows attention to remain focused on hypotheses, evidence and interpretation.
Yet the evaluation also exposed a central difficulty. Some students found it challenging to apply scientific reasoning to theoretical concepts in the context of cell-cycle regulation. This gap illustrates why a virtual laboratory cannot be treated as a complete teacher. A student may successfully manipulate the simulator, produce a graph and identify a change in cell behaviour without understanding the molecular explanation behind the pattern. Likewise, an apparently clear result may be overinterpreted if the learner has not considered experimental controls, uncertainty or the limitations of the simulated model. The study therefore highlights the importance of explicit scaffolding, including carefully sequenced questions, opportunities for discussion, prompts that connect data with biological mechanisms and assessment criteria that reward evidence-based argument rather than mere completion of steps.
The findings have implications well beyond one cell biology lesson. Biomedical engineers routinely work at the boundary between biological systems, quantitative analysis and technological design. Their professional decisions may involve evaluating tissue-engineering strategies, interpreting diagnostic data, optimising drug-delivery systems or assessing the performance of medical devices. In each case, procedural competence must be accompanied by the ability to frame a question, design a fair test, evaluate evidence and communicate a defensible conclusion. Web-based simulations can provide a flexible environment in which those skills are rehearsed repeatedly and safely, particularly before students enter a physical laboratory or research setting. They may also support blended learning by allowing learners to prepare for hands-on work, revisit difficult concepts or continue investigations outside scheduled class time.
The Singapore team’s broader message is that the future of virtual laboratory education will depend less on how realistic a simulation looks than on how intelligently it is embedded in instruction. StarCellBio gave students access to an interactive model of cell biology, but the TPACK framework and 4D inquiry structure gave that access a purpose. The initiative shows both the promise and the limits of digital experimentation: technology can make scientific activity accessible, repeatable and engaging, but higher-order reasoning must be taught through deliberate pedagogical design. For students learning to become biomedical engineers, the most valuable outcome may not be the virtual experiment itself, but the habit of asking what should be tested, why the evidence matters and how confidently a conclusion can be defended.
Subject of Research: Biomedical engineering laboratory education using virtual cell biology simulations
Article Title: A TPACK-Based Approach to Teach Experimental Design and Scientific Reasoning with a Web-Based Lab Simulator
Article References: Rahman, K., Rai, B. & Leo, C. H. “A TPACK-Based Approach to Teach Experimental Design and Scientific Reasoning with a Web-Based Lab Simulator.” Biomedical Engineering Education (2026). Key references include Mishra and Koehler’s TPACK framework; Pedaste et al. on inquiry-based learning; Quintana et al. on scaffolding science inquiry; and de Jong, Linn and Zacharia on physical and virtual laboratories.
Image Credits: AI Generated
DOI: 10.1007/s43683-026-00245-6
Keywords: TPACK, guided inquiry, 4D Discover-Design-Develop-Defend model, StarCellBio, virtual laboratory simulations, experimental design, scientific reasoning, cell-cycle regulation, biomedical engineering education, scientific argumentation
Tags: cost-effective virtual labs for postgraduate studentsdigital tools for scientific evidence interpretationenhancing experimental design skills through virtual labsguided inquiry models in online biomedical educationhigher-order thinking in virtual science learninginquiry-based learning in biomedical educationonline cell biology laboratory simulatorremote laboratory instruction in biomedical engineeringsafety and accessibility in virtual scientific experimentsTPACK framework in science educationvirtual experiments for scientific reasoningvirtual laboratory simulations in biomedical engineering
