📚 Year 8 Cambridge Psychology: Key Points for Experimental/Practical Assessments | Year 8 剑桥心理学：实验/实践考核要点
In Year 8 Cambridge Psychology, experimental and practical assessments are designed to test your ability to think like a scientist. You will plan simple investigations, identify variables, collect and present data, and evaluate findings. This article summarises the essential points you need to master to succeed in these assessments.
在 Year 8 剑桥心理学中，实验和实践考核旨在测试你像科学家一样思考的能力。你需要规划简单的调查、识别变量、收集和呈现数据，并评价研究发现。本文总结了你在这些考核中取得成功必须掌握的关键要点。
1. Identifying Variables | 识别变量
In any experiment, variables are the factors that can change. It is crucial to identify different types of variables clearly.
在任何实验中，变量是可以变化的因素。清楚地识别不同类型的变量至关重要。
The independent variable (IV) is the factor you deliberately change or manipulate. For example, if you are testing whether noise affects concentration, the level of noise (loud vs quiet) is the IV.
自变量（IV）是你故意改变或操纵的因素。例如，如果你在测试噪音是否影响注意力，噪音水平（吵闹与安静）就是自变量。
The dependent variable (DV) is the factor you measure. It depends on the IV. In the noise experiment, the concentration score would be the DV.
因变量（DV）是你测量的因素。它取决于自变量。在噪音实验中，注意力得分就是因变量。
Control variables are all the other factors you keep the same to make the test fair. In the noise study, you might control room temperature, time of day, and task difficulty.
控制变量是你为了公平测试而保持恒定的所有其他因素。在噪音研究中，你可以控制室温、一天中的时间和任务难度。
2. Writing Hypotheses | 撰写假设
A hypothesis is a clear, testable prediction about what you expect to happen in your experiment. It is not just a guess; it is based on previous knowledge or observations.
假设是对你期望在实验中发生的情况的清晰、可检验的预测。它不仅仅是猜测，而是基于先前的知识或观察。
It is often written as a statement, such as: "Participants will score higher on a memory test in a silent room compared to a noisy room."
假设通常写成一个陈述句，例如：“与在嘈杂的房间里相比，参与者在安静的房间里记忆测试得分更高。”
In Cambridge Psychology, you might also learn about null and alternative hypotheses, but at Year 8 you mainly need a simple directional (one-tailed) or non-directional (two-tailed) prediction.
在剑桥心理学中，你可能也会学习零假设和备择假设，但在 Year 8 阶段，你主要需要简单的方向性（单尾）或非方向性（双尾）预测。
3. Designing an Experiment | 设计实验
A good experimental design ensures that your investigation is valid and reliable. You need to decide on the participants, materials, and procedure.
一个好的实验设计能确保你的调查是有效且可靠的。你需要确定参与者、材料和程序。
You will often use a repeated measures design (same participants in all conditions) or an independent groups design (different participants in each condition). Matching the groups on relevant variables can improve fairness.
你经常会使用重复测量设计（相同参与者参与所有条件）或独立组设计（不同参与者参与每个条件）。在相关变量上匹配各组可以提高公平性。
Standardised instructions are written so that every participant receives exactly the same information. This reduces experimenter bias.
使用标准化指导语是为了让每个参与者收到完全相同的信息，从而减少实验者偏差。
4. Ethical Considerations | 伦理考量
When conducting research with human participants, you must follow ethical guidelines. These protect participants from harm and ensure their rights are respected.
在对人类参与者进行研究时，你必须遵循伦理准则。这些准则保护参与者免受伤害，并确保他们的权利得到尊重。
Key principles include informed consent (participants agree to take part after knowing what the study involves), confidentiality (their data is kept private), and the right to withdraw (they can leave at any time without penalty).
关键原则包括知情同意（参与者在了解研究内容后同意参加）、保密性（他们的数据被保密）和退出权（他们可以随时退出而不会有任何惩罚）。
Deception should be avoided unless necessary, and if used, you must debrief participants afterwards, explaining the true purpose of the study.
应避免欺骗，除非必要，如果使用了欺骗，你必须在事后对参与者进行解释，告知研究的真实目的。
5. Sampling Methods | 抽样方法
The people who take part in your study are the sample, drawn from a target population. How you choose them matters because it affects the generalisability of your findings.
参与你研究的人是样本，从目标人群中抽取。你选择他们的方式很重要，因为这会影响研究结果的推广性。
Opportunity sampling uses whoever is readily available, such as students in your class. It is quick but may not be representative.
机会抽样使用任何容易找到的人，比如你班里的同学。这种方式很快，但可能不具有代表性。
Random sampling gives every person in the target population an equal chance of being chosen (e.g., drawing names from a hat). It is fairer but harder to achieve in practice.
随机抽样让目标人群中的每个人都有平等的机会被选中（例如，从帽子里抽名字）。这更公平，但在实践中更难实现。
6. Data Collection: Observations and Questionnaires | 数据收集：观察与问卷
In practical assessments, you often collect data through direct observation or self-report questionnaires. Both have strengths and limitations.
在实践考核中，你经常通过直接观察或自我报告问卷来收集数据。两者都有优点和局限性。
Observations can be structured (using a checklist of behaviours) or unstructured (noting everything that occurs). Observers must be trained to be consistent to achieve inter-rater reliability.
观察可以是结构化的（使用行为检查表）或非结构化的（记下发生的一切）。观察者必须接受培训以保持一致性，从而实现评分者间信度。
Questionnaires contain closed questions (yes/no, rating scales) which give numerical data, or open questions where participants write their own answers. Closed questions are easier to analyse statistically.
问卷包含封闭式问题（是/否、评分量表），产生数值数据；或开放式问题，让参与者写出自己的答案。封闭式问题更容易进行统计分析。
7. Presenting Data | 呈现数据
Once data are collected, you need to present them clearly. Bar charts are commonly used to compare averages (means) across conditions.
收集数据后，你需要清晰地呈现它们。柱状图通常用于比较不同条件下的平均值（平均数）。
When drawing a bar chart, label both axes clearly. The IV goes on the x-axis (horizontal) and the DV (mean score) on the y-axis (vertical). Include a title that explains what the graph shows.
绘制柱状图时，要清晰地标注两个轴。自变量放在 x 轴（水平轴），因变量（平均得分）放在 y 轴（垂直轴）。还要加上标题，说明图表显示的内容。
Tables are also useful for presenting raw data and summary statistics. Make sure to give each table a number and a brief heading.
表格也可用于呈现原始数据和汇总统计。确保每个表格都有编号和简短的标题。
8. Describing Results | 描述结果
When describing results, state what the numbers show in words. Avoid making conclusions yet. For example: "The mean recall score was 15.3 in the silent condition and 11.7 in the noisy condition."
描述结果时，用文字说明数字显示的内容。暂时不要下结论。例如：“安静条件下平均回忆得分为 15.3，嘈杂条件下为 11.7。”
You can comment on whether the difference seems large or small, but the formal evaluation of significance may involve basic measures of central tendency (mean, median, mode) and range.
你可以评论差异看起来是大还是小，但对显著性的正式评价可能涉及基本的集中趋势量数（平均数、中位数、众数）和范围。
To calculate the mean, use the formula:
要计算平均数，使用公式：
Mean = Σx ÷ n
Where Σx is the sum of all scores and n is the number of participants. You can also calculate the range (highest score minus lowest score) to show the spread of data.
其中 Σx 是所有得分的总和，n 是参与者数量。你还可以计算范围（最高分减最低分）以显示数据的分布情况。
9. Drawing Conclusions | 得出结论
A conclusion should refer back to the hypothesis. Does the data support the prediction? You can say, "The results support the hypothesis that a silent environment improves recall."
结论应回指假设。数据支持预测吗？你可以说：“结果支持了安静环境能改善回忆的假设。”
Do not claim to 'prove' a hypothesis. In science, data can support or not support a theory but rarely proves it absolutely. Acknowledge any limitations.
不要声称“证明”了假设。在科学中，数据可以支持或不支持一个理论，但很少绝对证明它。要承认任何局限性。
Finally, suggest what could be done differently next time, and propose a related future investigation.
最后，建议下次可以有何不同之处，并提出相关的未来研究方向。
10. Evaluating Your Research | 评价你的研究
Evaluation involves discussing the strengths and weaknesses of your method. Consider reliability (consistency of results) and validity (whether you measured what you intended to measure).
评价包括讨论你所用方法的优点和缺点。考虑信度（结果的一致性）和效度（你是否测量了你打算测量的东西）。
For example, if you used an independent groups design, individual differences between participants might have acted as an extraneous variable, lowering internal validity.
例如，如果你使用了独立组设计，参与者之间的个体差异可能成为额外变量，降低内部效度。
Also discuss the ecological validity – how much the study setting reflects real life. A laboratory experiment gives high control but low ecological validity.
还要讨论生态效度——研究环境在多大程度上反映了现实生活。实验室实验控制度高，但生态效度低。
Improvements could include using a matched pairs design or conducting the study in a more natural setting.
改进措施可以包括使用配对组设计，或在更自然的环境中进行研究。
Published by TutorHao | Psychology Revision Series | aleveler.com
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