📚 Experimental/Practical Assessment Key Points for KS3 WJEC Economics | KS3 WJEC 经济：实验/实践考核要点
In KS3 WJEC Economics, hands-on experiments and practical investigations are not just about memorising facts — they help you think like an economist. Whether you are running a classroom market simulation, conducting a survey on spending habits, or analysing real-world data, the assessment focuses on how you plan, collect evidence, interpret results, and evaluate your findings. Understanding the key skills and assessment criteria will boost your confidence and performance in any practical task.
在 KS3 WJEC 经济课程中，动手实验和实践调查不仅仅是记住事实——它们帮助你像经济学家一样思考。无论你是在课堂上进行市场模拟、对消费习惯开展问卷调查，还是分析真实世界的数据，考核的重点在于你如何规划、收集证据、解释结果并评估你的发现。理解这些关键技能和评估标准将提升你在任何实践任务中的信心和表现。
1. Designing Economic Investigations | 设计经济调查
Every practical task starts with a clear research question. For example, you might ask, ‘How does a change in price affect the quantity of sandwiches sold in the school canteen?’ Your question should be specific, testable, and linked to an economic concept such as demand or supply.
每一项实践任务都从一个明确的研究问题开始。例如，你可能会问：“价格变化如何影响学校食堂三明治的销售量？”你的问题应当具体、可验证，并与需求或供给等经济概念相关联。
Once you have a question, identify the variables. In the sandwich example, price is the independent variable (the one you change), and quantity sold is the dependent variable (the one you measure). You also need to control other factors, like the time of day or the type of sandwich, so your investigation is fair.
一旦有了问题，就要确定变量。在三明治的例子中，价格是自变量（你改变的变量），销售量是因变量（你测量的变量）。你还需要控制其他因素，比如时段或三明治的种类，以确保调查的公平性。
2. Collecting Primary and Secondary Data | 收集一手和二手数据
Primary data is information you gather yourself through experiments, surveys, or observations. In economics, you might run a mini-market in class where students trade tokens, and you record the prices and quantities at which trades happen.
一手数据是你自己通过实验、调查或观察收集的信息。在经济学中，你可能会在课堂上开展一个小型市场，让学生们用代币进行交易，你则记录下交易发生的价格和数量。
Secondary data comes from sources that already exist, such as government statistics, news articles, or school records. For a practical project, you could use the school’s lunch sales data from last term to compare with your own primary findings. Always note where the data comes from and check if it is reliable and up to date.
二手数据来自已有的来源，例如政府统计数据、新闻文章或学校记录。对于实践项目，你可以使用上学期学校午餐销售数据来与你的一手调查结果进行比较。务必注明数据来源，并检查其是否可靠且是最新的。
3. Using Questionnaires and Surveys | 使用问卷和调查方法
Questionnaires are a powerful tool for collecting economic data. If you want to know how students choose between packed lunch and canteen food, you could design a short survey asking about preferences, prices they are willing to pay, and reasons for their choices.
问卷是收集经济数据的强大工具。如果你想知道学生如何在自带午餐和食堂餐之间做选择，你可以设计一份简短的调查，询问他们的偏好、愿意支付的价格以及选择的原因。
To get valid results, use a mix of closed questions (e.g., multiple choice, ‘yes/no’) and a few open-ended questions. Avoid leading questions that push people towards a certain answer. For instance, instead of asking, ‘Don’t you think canteen food is overpriced?’, ask, ‘On a scale of 1 to 5, how would you rate the value for money of canteen meals?’
为了获得有效的结果，要混合使用封闭式问题（例如选择题、“是/否”题）和少量开放式问题。避免可能引导人们给出特定答案的诱导性问题。例如，不要问“你不觉得食堂餐太贵了吗？”，而是问“按1到5分打分，你如何评价食堂餐的性价比？”
4. Organising Data: Tables and Charts | 整理数据：表格与图表
Once you collect data, you need to present it clearly. A well-designed table helps you record raw data accurately. Always give the table a title and label each column with the variable and its unit, such as ‘Price per sandwich (pence)’ and ‘Number of sandwiches sold per day’.
收集到数据后，你需要清晰地呈现数据。一张精心设计的表格有助于你准确记录原始数据。始终给表格加上标题，并在每一栏标注变量及其单位，例如“每个三明治的价格（便士）”和“每天销售的三明治数量”。
Charts make patterns easy to see. A bar chart is useful to compare categories, while a line graph is best for showing trends over time. For the sandwich example, you could plot a line graph with price on the x-axis and quantity sold on the y-axis to see if the demand curve slopes downwards.
图表让模式一目了然。条形图适合比较不同类别，而折线图最适合显示随时间变化的趋势。对于三明治的例子，你可以绘制一张折线图，x轴表示价格，y轴表示销售量，看看需求曲线是否向下倾斜。
5. Calculating Averages and Percentages | 计算平均值和百分比
Economic data often involves numbers that need to be summarised. Calculating the mean (average) helps you find a typical value. For example, if you recorded the number of sandwiches sold at a price of £1.50 over five days as 12, 15, 13, 14, 16, the mean is (12+15+13+14+16) ÷ 5 = 14 sandwiches.
经济数据通常包含需要汇总的数字。计算平均值（平均数）有助于你找到一个典型数值。例如，如果你记录了三明治在1.50英镑的价格下一周五天的销售量分别为12、15、13、14、16，那么平均值为(12+15+13+14+16) ÷ 5 = 14个三明治。
Percentages are used to compare changes or shares. If a school’s lunch sales rose from 200 to 230 meals a day, the percentage increase is ((230-200) ÷ 200) × 100 = 15%. Use this to express how much a variable has grown relative to its starting point. A table with sample data is shown below.
百分比用于比较变化或份额。如果学校午餐销售从每天200份增加到230份，那么增长百分比为((230-200) ÷ 200) × 100 = 15%。使用它可以表达一个变量相对于起点的增长幅度。下表展示了一个示例数据。
| Day | Price per meal (£) | Meals sold |
|---|---|---|
| Monday | 2.00 | 180 |
| Tuesday | 2.20 | 165 |
| Wednesday | 1.80 | 200 |
6. Interpreting Graphs and Trends | 解读图表与趋势
When looking at a graph, describe the overall trend first. Is the line going up, down, or staying flat? For instance, a line graph of snack sales might show an upward trend on Fridays, which could be explained by students treating themselves at the end of the week.
观察图表时，首先要描述总体趋势。线条是上升、下降还是持平？例如，一张零食销售折线图可能显示周五呈上升趋势，这可以用学生们在周末犒劳自己来解释。
Look for patterns such as seasonal peaks or sudden drops. Use economic concepts to explain them. If sales of ice cream rise sharply in sunny weather, you could link this to the concept of demand being influenced by external factors like weather. Always relate what you see to the economic question you started with.
寻找季节性的峰值或突然下降等模式，并用经济概念加以解释。如果冰淇淋的销量在晴朗天气中急剧上升，你可以将其与需求受天气等外部因素影响这一概念联系起来。始终将你看到的现象与你最初的经济问题联系起来。
7. Making Predictions from Data | 从数据中进行预测
After analysing your findings, you can make simple predictions. If your sandwich experiment showed that a 10% price increase led to a 5% fall in sales, you might predict that a further 10% rise would reduce sales by roughly another 5%. This helps you understand price elasticity in a basic way.
在分析完你的发现后，你可以进行简单的预测。如果你的三明治实验显示价格每上涨10%，销量就下降5%，那么你可能预测价格再涨10%会使销量再减少约5%。这有助于你从基础层面理解价格弹性。
However, predictions assume that nothing else changes — what economists call ‘ceteris paribus’. In real life, other factors like a new cafeteria opening or a change in student income can upset your forecast. Always mention these assumptions when you make predictions.
然而，预测假设其他条件不变——经济学家称之为“其他条件不变”。在现实生活中，新餐厅的开张或学生收入的变化等其他因素都可能打破你的预测。在做出预测时，务必提及这些假设条件。
8. Understanding Correlation vs. Causation | 区分相关与因果
Just because two variables move together does not mean one causes the other. In a project, you might find a positive correlation between the number of ice creams sold and the number of sun hats worn. But does ice cream cause sun hats? No — both are affected by a third factor: hot weather.
两个变量同时变动并不代表一个导致另一个。在一个项目中，你可能会发现冰淇淋销量和太阳帽佩戴数量之间存在正相关关系。但冰淇淋会导致太阳帽吗？不会——两者都受到第三个因素的影响：炎热的天气。
In economics practicals, always check for hidden variables. Before you conclude that raising the price of canteen meals caused a fall in demand, ask whether a new, cheaper food outlet opened nearby at the same time. Showing you can spot this difference is a key assessment skill.
在经济学实践中，始终要检查隐藏变量。在你得出提高食堂餐价格导致需求下降的结论之前，先问问是否同时附近新开了一家更便宜的小吃店。能够表明你发现了这种差异是一项关键的考核技能。
9. Evaluating Economic Experiments | 评估经济实验的局限性
No investigation is perfect. A good evaluation points out what could be improved. For example, your survey on spending habits might have a small sample size — perhaps you only asked your own class, which may not represent the whole school.
没有哪项调查是完美的。好的评估会指出可以改进的地方。例如，你关于消费习惯的调查可能样本量较小——也许你只问了自己班级的同学，这或许不能代表整个学校。
You might also discuss the reliability of your measurements. Did you record sales at exactly the same time each day? Was the data affected by special events, like a school trip, that reduced the number of students buying lunch? Highlighting these issues and suggesting improvements shows evaluative thinking.
你还可以讨论测量结果的可靠性。你是否每天在完全相同的时间记录销量？数据是否受到特殊事件的影响，比如学校旅行减少了购买午餐的学生人数？指出这些问题并提出改进建议，显示了评估性思维。
10. Presenting Findings and Conclusions | 呈现发现与结论
A strong practical write-up brings everything together. Start with a brief introduction that restates your research question and hypothesis. Then present your data using tables and charts, followed by an analysis where you explain what the data shows in economic terms.
一份出色的实践报告应将所有内容整合在一起。首先，用简短的引言重申你的研究问题和假设。然后使用表格和图表呈现数据，接着进行分析，用经济术语解释数据所显示的内容。
Your conclusion must answer the research question directly and be supported by evidence. If you found that price and demand moved in opposite directions, state that clearly and link it to the law of demand. Finally, suggest one or two ways the investigation could be extended or improved next time — this rounds off your practical assessment with a thoughtful, reflective touch.
你的结论必须直接回答研究问题，并得到证据的支持。如果你发现价格和需求呈反向变动，就要清晰地陈述这一点，并将其与需求定律联系起来。最后，提出一两种下次扩展或改进调查的方法——这样就能以深思熟虑、反思性的笔触为你的实践考核画上圆满的句号。
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