📚 Year 7 AQA Biology: Key Points for Practical Assessments | AQA 7年级生物：实验考核要点
Mastering practical skills is just as important as learning biological facts in Year 7. Your teacher will assess how safely you work, how you handle variables, and how well you can collect and interpret data. This guide walks through the key assessment areas so you know exactly what examiners and teachers are looking for in your practical work.
在7年级生物课程中，掌握实验技能与学习生物知识同样重要。老师会评估你的实验安全意识、变量处理能力，以及收集和解读数据的水平。本指南逐一梳理主要考核方面，帮助你清晰了解老师和考官的实验评分标准。
1. Laboratory Safety | 实验室安全
Always wear safety goggles when handling chemicals, heating substances, or using biological materials that might splash. Tie back long hair, tuck in loose clothing, and never eat or drink in the lab. Before starting any experiment, listen carefully to the teacher’s safety briefing and read the risk assessment.
在处理化学品、加热物质或可能飞溅的生物材料时，务必配戴护目镜。长发要束好，宽松的衣物要扎紧，实验室里严禁饮食。每次实验前，请认真听取老师的安全说明并阅读风险评估内容。
Know the location of the fire extinguisher, fire blanket, eyewash station, and first aid kit. If an accident happens, even a small spill, report it to your teacher immediately. Wash your hands after handling living organisms, soil, or chemicals.
熟悉灭火器、灭火毯、洗眼器和急救箱的位置。一旦发生意外，即使是小量溢出，也要立即报告老师。接触过活体生物、泥土或化学品后，务必洗手。
2. Identifying Variables | 识别变量
In any experiment, you must identify three types of variables. The independent variable is the one you deliberately change. The dependent variable is what you measure or observe as a result. Control variables are all the factors you keep the same to make the test fair.
在任何实验中，你都必须识别三种变量。自变量是你特意改变的那个因素；因变量是你测量或观察到的结果；控制变量是为了保证公平测试而保持不变的所有其他因素。
For example, when investigating how light intensity affects the rate of photosynthesis in pondweed, light intensity (distance of the lamp) is the independent variable, the number of oxygen bubbles produced per minute is the dependent variable, and temperature, mass of pondweed, and volume of water should be controlled.
例如，在研究光照强度如何影响水草光合作用速率时，光照强度（灯的远近）是自变量，每分钟产生的氧气气泡数是因变量，而温度、水草的质量和水的体积都应作为控制变量。
3. Designing a Fair Test | 设计公平实验
A fair test means only the independent variable affects the results. You must keep all control variables constant, and repeat measurements at least three times to improve reliability. Avoid changing more than one variable at a time, or you will not know which one caused the effect.
公平测试意味着只有自变量影响结果。你必须保持所有控制变量不变，并且每个测量至少重复三次以提高可靠性。避免一次改变多个变量，否则你将无法判断是哪个因素导致了变化。
If you are testing the effect of temperature on the activity of the enzyme amylase, use the same concentration and volume of starch solution each time, the same volume of amylase, and the same pH buffer. Only the water bath temperature should change between trials.
如果你测试温度对淀粉酶活性的影响，每次都要使用相同浓度和体积的淀粉溶液、等量的淀粉酶和相同的pH缓冲液。每次试验之间只改变水浴温度。
4. Using Apparatus and Making Measurements | 使用设备与测量
Choose the right measuring instruments for the job. Use a syringe or measuring cylinder for volume, a digital balance for mass, a thermometer for temperature, and a stopwatch for time. Always read the scale at eye level to avoid parallax error, and record the unit next to every number.
选择合适的测量工具：用量筒或注射器测体积，用电子天平测质量，用温度计测温度，用秒表测时间。读数时视线要与刻度齐平以避免视差，每个数据后面都要写清单位。
When using a microscope, start with the lowest power objective lens, use the coarse focus knob first, then fine focus. Handle slides carefully and always draw what you see with a sharp pencil, labelling visible structures.
使用显微镜时，先从低倍物镜开始，先用粗准焦螺旋，再用细准焦螺旋。小心操作玻片标本，并用铅笔清晰绘制所见结构，标注出可见的部位。
5. Recording Data in Tables | 在表格中记录数据
Draw your results table with a ruler before you start the experiment. The independent variable goes in the left-hand column, and the dependent variable (with repeats) in the next columns. Each column heading must include the quantity and unit, for example 'Temperature (°C)' or 'Time taken for starch to disappear (s)'.
实验开始前用尺子画好结果表格。自变量放在左边一列，因变量（包括重复测量值）放在右侧的各列。每列表头必须写明量和单位，例如“温度（°C）”或“淀粉消失所需时间（s）”。
Record your raw data accurately during the experiment, not from memory afterwards. Calculate the mean of the repeated readings, ignoring any clear outliers that resulted from mistakes.
在实验过程中如实记录原始数据，不要事后凭记忆补写。计算重复读数的平均值时，要排除因失误产生的明显异常值。
6. Drawing Graphs | 绘制图表
Use the correct type of graph: a line graph for continuous data (e.g. temperature over time), and a bar chart for discrete categories (e.g. number of leaves eaten by snails on different plant species). Put the independent variable on the x‑axis and the dependent variable on the y‑axis.
根据数据类型选择正确的图表：连续数据（如温度随时间变化）用折线图，离散分类数据（如蜗牛在不同植物上吃掉的叶片数）用条形图。将自变量放在 x 轴，因变量放在 y 轴。
it, mark the scale evenly, and plot points with a small cross (×). Draw a line of best fit – straight line through most points, ignoring outliers. Give your graph a descriptive title.
两个坐标轴都标注变量和单位，刻度要均匀，用小的叉号（×）描点。画一条最佳拟合线——穿过大部分点的平滑曲线或直线，并忽略异常点。给图表起一个准确的标题。
7. Drawing Conclusions | 得出结论
Your conclusion must refer directly to the data. State what your results show about the relationship between the independent and dependent variables. Use the format: ‘As [independent variable] increases, [dependent variable] increases/decreases, because…’ and then give a scientific explanation.
结论必须直接引用数据。陈述你的结果显示了自变量和因变量之间存在什么关系。使用句式：“随着[自变量]的增加，[因变量]增加/减少，因为……”，然后给出科学解释。
Do not just repeat the numbers; explain the biological reason behind the pattern. If the results do not match your prediction, state that clearly and suggest a possible reason based on your knowledge.
不要只是重复数字，而要解释规律背后的生物学原因。如果结果与预测不符，也要明确指出来，并根据你的知识提出一个可能的原因。
8. Evaluating the Experiment | 实验评估
No experiment is perfect. In your evaluation, discuss sources of error, such as difficult‑to‑control temperature, reaction time when using a stopwatch, or limitations of the measuring instruments. Explain how each error could have affected the results.
没有任何实验是完美的。在评估中，讨论误差来源，例如难以控制的温度、使用秒表时的反应时间，或测量仪器的精度限制。解释每种误差可能如何影响了结果。
Suggest at least two specific improvements. Instead of saying ‘do it more carefully’, suggest using a water bath for temperature control, using a datalogger for faster measurements, or increasing the number of repeats to calculate a more reliable mean.
至少提出两条具体的改进建议。不要只是说“更仔细地做”，可以建议用水浴控制温度、使用数据记录仪加快测量速度，或者增加重复次数以便计算出更可靠的平均值。
Finally, check whether the results can be trusted by comparing them with class data or published values. A good evaluation shows that you understand the limits of the method and can think scientifically about how to improve it.
最后，通过对比全班数据或已知参考值，判断结果是否可信。一份好的评估能够体现你理解方法的局限性，并能从科学角度思考如何改进实验。
Published by TutorHao | Biology Revision Series | aleveler.com
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