From routine to research-based learning
Surekha Rao makes the case for rethinking Science practicals, which, she argues have become routine and dull.
Ditching ‘show and do’
For decades, science labs (‘practicals’) in schools have followed the same predictable routine: the teacher explains a concept, demonstrates an experiment and students replicate it—often jotting down results in lab manuals as a mere formality. While this traditional “show and do” approach may meet curriculum requirements, it rarely sparks curiosity, critical thinking, or meaningful engagement. Students often learn to complete steps and copy conclusions, but they rarely experience the thrill of discovery or understand the reasoning behind scientific phenomena. Is this truly experiential learning? The answer is largely no, though there are glimpses of potential when labs are approached thoughtfully.
A new framework for experiential science learning
Reimagining lab work starts with a framework rooted in curiosity, exploration, and reflection. By shifting the focus from rote replication to student-led investigation, we can make science both engaging and intellectually rewarding. The ‘3 Is’ may help
- Instigate: spark curiosity with real-world phenomena
The first step is to pique curiosity. Rather than starting with definitions, formulas, or instructions, teachers can present a puzzling real-world phenomenon. For example, instead of simply explaining the reactivity series of metals, a teacher might show how different metals react with water or acids under timed conditions. This approach encourages students to ask, “Why does this happen?” before learning “how it works.” Presenting unfamiliar, intriguing scenarios creates authentic motivation to explore and find answers. - Inspect: encourage students to investigate before instruction
Once curiosity is sparked, students should be given the freedom to investigate. Before any formal instruction, they can discuss hypotheses, brainstorm predictions, and test ideas. This approach helps students connect abstract concepts with their own thinking and observations. For instance, in a chemistry lab, students might predict which metals will react most vigorously, carry out the reactions safely, and observe the outcomes. Allowing exploration first transforms students from passive recipients into active learners, giving meaning to the later explanations and formal instruction. - Infer: scaffold deeper understanding
The final step is guiding students to refine their observations and draw conclusions. This phase encourages critical thinking and mirrors real scientific inquiry, where models and hypotheses are constantly revised based on evidence. Students might initially make inaccurate predictions, but through structured discussion, peer feedback, and reflection, they develop a more nuanced understanding of the underlying scientific principles. Encouraging reasoning over rote memorization ensures that students internalize concepts more effectively.
Thinking routines that promote deeper engagement
Structured thinking routines can transform science labs into spaces for intellectual exploration. These strategies have been effective and are worth trying out if you haven’t already done so:
- Observe, think, question: Students analyze images, graphs, or physical models, reflect on what they notice, and generate meaningful questions.
- Understand & peer-share: Learners sketch their understanding of a concept, then collaborate with peers to refine ideas, building both conceptual clarity and communication skills.
- Compare & contrast: Students examine scientific models, datasets, or experimental results side by side, identifying patterns and differences to inform their conclusions.
- Model building & iteration: Students create initial conceptual models, revise them based on experimental evidence, and discuss improvements with peers, mirroring the iterative nature of scientific discovery.
Integrating data analysis into lab work
Data analysis should be an active and inquiry-driven process, not a mechanical task of recording numbers. In real-world science, data is rarely neat, and interpretation requires critical thinking. Teachers can design activities that transform data into a discovery tool:
- Slow-release graphs: Reveal data gradually so students can form evolving interpretations and revise conclusions as new information emerges.
- Data stations: Students rotate through datasets, graphs, or models, analyzing results from multiple perspectives and fostering collaborative insight.
- Consensus records: Group members individually record observations, then synthesize collective insights, building a shared understanding of findings.
These strategies encourage discussion, reasoning, and teamwork, replicating the collaborative, iterative nature of real scientific research.
From labs to learning laboratories
When lab work is reimagined as an opportunity for questioning, exploration and reflection, science becomes far more engaging and meaningful. Moving from demonstration to exploration—and from dictation to inference – empowers students to think critically, ask questions, and test their own ideas.
This approach also prepares students for the future. Beyond exams, they develop essential skills such as analytical reasoning, collaboration, creativity, and resilience in the face of unexpected results. Labs are no longer just places to practice experiments; they become learning laboratories, dynamic spaces where curiosity meets discovery.
Ultimately, the purpose of science education is not to produce students who can follow instructions, but those who can reason, investigate, and innovate. By rethinking lab work, we shift the focus from performing tasks to cultivating minds, ensuring that the spirit of inquiry, and a love for science, thrives long after students leave the classroom.
Surekha Rao R is an experienced teacher of high school Chemistry and Science, focusing on research-based experiential learning. She lives in Bengaluru, Karnataka.
FEATURE IMAGE and support images: by Getty Images For Unsplash+
