Turn your lessons into experiences.
Lessons students want to explore, participate in and remember.
Edugine helps tutors create and run live learning experiences where students actively participate, interact and collaborate — while tutors see what students are doing and guide the lesson in real time.
Lesson
C1ENPresenting Lab Results: Data That Speaks
Turn raw lab data into a clear, convincing presentation. Master the language of scientific reporting, learn to structure findings for different audiences, and present under pressure with live Q&A. A practical C1 English lesson for chemists and scientists on presenting research, data interpretation language, and handling audience questions. Ideal for chemistry professionals, R&D teams, and corporate English training.
How this lesson works
Students participate
Students interact directly with the lesson — responding, speaking, solving tasks, making decisions and joining activities.
You see what is happening
See student responses, answers, mistakes and activity in real time where supported.
You guide the experience
Guide the lesson, manage activities and timing, and respond to what students are doing where supported.
Everyone participates
Students actively contribute and interact instead of simply consuming lesson content.
Death by PowerPoint — What Makes Scientists Stop Listening? Talk Time
Talk Time
- What is the worst scientific presentation you have ever sat through? What made it bad?
- When you present your own data, what part do you find most difficult — structure, language, or confidence?
- Have you ever seen a presenter handle a tough question brilliantly? What did they do?
- What is the difference between presenting to fellow chemists and presenting to management?
- If you had to present six months of lab work in five minutes, what would you keep and what would you cut?
Scientific Presentation Vocabulary. Swipe Battle
Swipe Battle
Findings
The results or conclusions discovered through research or experimentation
Hypothesis
A prediction or proposed explanation that can be tested through experiments
Variable
A factor that remains constant throughout an experiment
Margin of error
The range of uncertainty in experimental measurements or results
Reproducibility
The ability to get the same results when an experiment is repeated
Correlation
A statistical relationship between two variables
Outlier
A data point that is significantly different from the rest of the dataset
Peer review
The process of having other experts evaluate your research before publication
Methodology
The system of methods and principles used in a particular area of study
Abstract
A long, detailed version of a research paper that includes all raw data
Control group
A group in an experiment that is not exposed to the variable being tested
Benchmark
A standard or reference point against which things can be compared
Yield
The amount of product obtained from a chemical reaction
Deviation
The amount by which a result differs from the expected or average value
Sample size
The number of observations or participants included in a study
Calibration
The process of adjusting an instrument to ensure accurate measurements
Contamination
Keeping a sample perfectly pure and free from unwanted substances
Significant
In statistics, a result unlikely to have occurred by chance alone
Raw data
Data that has been fully processed, analysed, and ready for publication
Error bar
A decoration added to charts to make them look more professional
How to Talk About Data: Sorting
Sorting
Describing trends
Hedging and caution
Emphasising importance
Lesson Board
Lesson Board
Present the Data — Choose the Right Phrase: Word Choice
Word Choice
- The results have been indicatingare indicatingindicate that the new catalyst significantly reduces reaction time.
- Such asAsLike you can see from Figure 2, yield increased steadily over 48 hours.
- The data is revealinghas been revealingreveals a strong correlation between temperature and purity levels.
- This doeswillcould indicate a previously unknown reaction pathway, but further tests are needed.
- It is worth notingto notenoted that this result has not been reported in any previous study.
- The margin of error was enoughtoovery small to affect our overall conclusions.
- BaseBasedBasing on these findings, we recommend scaling up production immediately.
- The key takingtaketakeaway from this experiment is that the modified process reduces waste by 30%.
- We might notshould notcannot rule out contamination as a possible factor in the anomalous results.
- Further research will beishas been needed to confirm whether this effect is reproducible.
Four Presentations, Four Styles: Jigsaw Reading
Jigsaw Reading
The Data Dump
Dr. Petrov stood in front of 40 slides packed with tables, numbers, and chemical structures. He read every data point aloud without explaining why any of it mattered. The audience stopped listening after slide 7. When someone asked what the practical application was, he said: "It's all in the data." His research was excellent. His presentation was forgotten by lunch.
The Storyteller
Dr. Nakamura opened her presentation with a question: "What if I told you we could cut purification time by 60%?" She showed only 12 slides. Each one had one key message and one visual. She walked the audience through the problem, the hypothesis, the experiment, and the result — like a story. She used hedging language carefully: "The data suggests..." not "We proved..." Her Q&A lasted longer than her talk because people wanted to know more.
The Overseller
Dr. Garcia was excited and it showed. He used words like "breakthrough," "revolutionary," and "game-changing" for every result. He dismissed limitations and said the data "clearly proved" his hypothesis. A senior researcher in the audience pointed out a flaw in his control group. Garcia had no answer. His credibility dropped in 30 seconds. The science was promising, but the language killed it.
The Apologiser
Dr. Johansson began by saying: "This is quite preliminary, and I'm not sure it means much yet." She repeatedly qualified her results with phrases like "this probably doesn't work" and "I'm not confident about this." Her data was actually strong — consistent results across three trials with tight error margins. But the audience trusted her self-assessment more than her data. Nobody asked follow-up questions because she had already told them it wasn't worth their time.
Comprehension questions
- Which presentation style was most effective for a scientific audience? Why?
- Which presenter made the biggest mistake, and how could they have fixed it?
- If you had to present the same data to your CEO, which style would you adapt?
Present Your Findings — Live Presentation. Elevator Pitch
Elevator Pitch
Useful phrases
- The key finding from our study is...
- What makes this significant is...
- The data clearly shows that...
- Based on our results, we recommend...
- One limitation worth noting is...
- This has direct implications for...
Present the results of a catalyst efficiency study. Your team tested three catalysts and one outperformed the others by 40%.
You are at an internal R&D meeting. Your audience is fellow chemists who understand the technical details. Be precise, use data language, and explain what this means for the next phase of research.
Explain a failed experiment to your project manager. The reaction did not produce the expected yield despite following the standard protocol.
Your manager is not a chemist. They want to know: what went wrong, what you learned, and what happens next. Keep it simple and solution-focused.
Present a quality control finding to senior management. Your team discovered that a batch of product did not meet purity specifications.
Management wants to know: how serious is it, what caused it, and what is the fix. They do not want chemistry jargon — they want a clear risk assessment and a decision.
Pitch your research findings to a potential industry partner at a conference. Your team developed a new synthesis method that reduces solvent waste by 50%.
You have 60 seconds to make them interested enough to schedule a follow-up meeting. Lead with the business impact, not the chemistry.
Science, Data, and the Truth. Speed Debate
Speed Debate
- Scientists should present their data with full confidence, even when they have doubts.
- A beautiful presentation with weak data is more dangerous than an ugly presentation with strong data.
- If your data does not support your hypothesis, you should still publish the results.
- Companies should allow researchers to present negative results at conferences.
- Non-scientists should never make decisions about scientific projects based on a short presentation.
- Using words like "breakthrough" in scientific presentations is always irresponsible.
- Peer review is too slow and needs to be replaced with faster methods.
- AI tools like ChatGPT should be used to help scientists write better presentations.
Why Edugine?
Turn your lessons into experiences.
Edugine helps tutors create and run live learning experiences where students actively participate, interact and collaborate — while tutors see what students are doing and guide the lesson in real time.