Use of technology in data collection (quantitative and qualitative,…

The idea

Technology changes how performers and coaches collect data. Quantitative data is numerical, such as a GPS unit reporting distance covered in metres or a heart-rate monitor logging beats per minute; qualitative data is descriptive, such as a coach noting that a sprinter's posture collapses in the final strides. Objective data is recorded by a device with minimal human judgement, for example a timing gate giving a 100 m time; subjective data depends on interpretation, such as a coach rating a gymnast's landing. Validity asks whether the data measures what it claims: a heart-rate monitor worn loosely may not reflect true cardiac effort. Reliability asks whether repeated measurements are consistent: the same timing gate should give similar results across trials. A test can be reliable but invalid, so both must be checked.

What earns the marks

• Quantitative data is numerical and measurable, for example distance in metres or heart rate in beats per minute.
• Qualitative data is descriptive and judgement-based, for example a coach's observation of technique or body position.
• Objective data is collected with minimal human interpretation, typically by a device such as timing gates or a GPS unit.
• Subjective data relies on human interpretation, such as a coach's rating of a performance.
• Validity concerns whether data measures what it claims to measure; reliability concerns whether repeated measurements give consistent results.
• A measurement can be reliable yet invalid, so consistency alone does not guarantee that the data is meaningful.

Common mistakes and how to put them right

• Treating quantitative and objective as identical.

  Put it right: Quantitative data is numerical, while objective data is collected with minimal human judgement; a coach could count tackles numerically but still judge subjectively what counts as a tackle.

• Assuming reliable data is automatically valid.

  Put it right: A faulty speed gun may give consistent readings that do not reflect true speed, so reliability must be checked separately from validity.

• Confusing qualitative with unreliable.

  Put it right: Descriptive observations can be systematic and useful, but they depend on the observer's interpretation and should be corroborated.

• Believing technology removes all subjectivity.

  Put it right: Someone still selects the device, the sampling rate and the variables recorded, so human decisions remain.

Exam tips

• Define each term precisely before applying it to a sporting example, so quantitative, qualitative, objective and subjective are clearly distinguished.
• Use a paired example such as timing gates (objective, quantitative) against a coach's technique rating (subjective, qualitative) to show the contrast.
• When asked about validity or reliability, state what the data claims to measure and whether repeated trials would give the same result.