What makes a data-collection method good, and why compare against a model performer?
Judging the quality of data-collection methods using reliability, validity, practicability and appropriateness, the value of comparing results against a model performer, and the organisational issues to consider when gathering data.
An SQA National 5 Physical Education answer on judging data-collection methods, covering reliability, validity, practicability and appropriateness, the value of comparing results against a model performer, and the organisational issues to consider when gathering data.
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What this dot point is asking
A data-collection method is only useful if the data it gives can be trusted. The SQA wants you to judge the quality of a method using four ideas: reliability, validity, practicability and appropriateness. You should also know the value of comparing your results against a model performer, and the organisational issues to think about when gathering data.
The four qualities of a good method
These four ideas decide whether you can trust your data.
- Reliability. If a test is repeated the same way and gives a similar score, it is reliable. Without reliability, a later change might be due to the test, not real improvement, making comparison unfair.
- Validity. A valid method measures the right thing. Using a flexibility test to judge endurance is not valid, so the data would be meaningless.
- Practicability. A method must fit the resources you have. A test needing expensive lab equipment is not practicable in a normal PE setting.
- Appropriateness. The method must match the factor and the level of the performer, for example a simple questionnaire for a mental factor rather than a fitness test.
Comparing against a model performer
A benchmark gives your data meaning.
Without a benchmark, a score on its own is hard to judge. Comparing to a model performer (or to published norm tables, which do the same job) turns a raw number into a clear strength or weakness.
Organisational issues
Good data depends on how carefully you gather it.
- Standardised conditions. Test in the same place, at the same time of day and after the same warm-up, so changes reflect the performer, not the conditions.
- Equipment and time. Have everything ready so the test runs smoothly and is not rushed, which protects reliability.
Examples in context
Example 1. A reliable but invalid choice. A pupil uses a sit-and-reach test every week and gets consistent scores, so it is reliable. But they use it to judge their cardio-respiratory endurance, which it does not measure, so it is not valid for that purpose and the data misleads them.
Example 2. Benchmarking a skill. A gymnast films their routine and compares it against a video of a model performer. The comparison shows their landings lack control, a weakness the raw routine alone would not have made obvious.
Try this
Q1. Define reliability in the context of collecting data. [1 mark]
- Cue. A method gives consistent results when repeated under the same conditions.
Q2. State one organisational issue to consider when collecting data. [1 mark]
- Cue. For example, standardising the conditions, having the right equipment ready, or allowing enough time.
Exam-style practice questions
Practice questions written in the style of SQA exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.
SQA N5 style4 marksExplain why reliability and validity are important when collecting data on performance.Show worked answer →
This explain question needs both terms defined and a reason each matters for the quality of the data, with two marks available per term.
Reliability means the method gives consistent results if it is repeated under the same conditions. This matters because if a test is unreliable, a later change in score might be due to the test, not real improvement, so a before-and-after comparison would be unfair.
Validity means the method actually measures what it is meant to measure. This matters because if a method is not valid, for example using a flexibility test to judge endurance, the data is meaningless and would lead to the wrong development needs.
Markers reward each term defined and linked to why it protects the quality of the data, up to four marks.
SQA N5 style2 marksDescribe how comparing your results against a model performer can help you.Show worked answer →
A 2-mark describe answer needs a clear sense of what a model performer is and how the comparison helps.
A model performer is someone who performs the activity to a high standard, used as a benchmark of what good looks like.
Comparing your data against theirs shows the gap between your performance and the standard, which helps you identify your weaknesses and set realistic targets to work towards.
Markers reward the idea of a high-standard benchmark (1) and using the comparison to identify weaknesses or set targets (1), to a total of two marks.
Related dot points
- Methods of collecting information on factors impacting on performance, including why data is gathered (the cycle of analysis), general and specific observation schedules, the use of recognised standardised fitness tests, and gathering both initial (baseline) and ongoing data.
An SQA National 5 Physical Education answer on methods of collecting information about the factors impacting on performance, covering why data is gathered as part of the cycle of analysis, general and specific observation schedules, recognised standardised fitness tests, and the value of baseline and ongoing data.
- Matching appropriate data-collection methods to each of the four factors, including questionnaires and self-reflection for mental and emotional factors, observation schedules and peer or coach feedback for social and skill factors, and standardised tests and movement analysis for physical factors, and the difference between qualitative and quantitative data.
An SQA National 5 Physical Education answer on choosing the right data-collection method for each factor, covering questionnaires and self-reflection for mental and emotional factors, observation and feedback for social and skill factors, standardised tests and movement analysis for physical factors, and qualitative versus quantitative data.
- Approaches to develop performance, including selecting appropriate approaches for each factor, the use of SMART targets, and the principles of effective practice such as progression from simple to complex and from practice to game-like conditions.
An SQA National 5 Physical Education answer on approaches to develop performance, covering how to select an appropriate approach for each factor, the use of SMART targets, and the principles of effective practice such as progressing from simple to complex and from practice to game-like conditions.