Research synthesis: concepts, methods, application and evidence

Teaching explanation

• Define the key ideas inside “questions, theory, literature and conceptual frameworks”, give an example and a non-example, and connect them to the previous chapter rather than learning isolated vocabulary.
• Use this subject method: frame an answerable question before selecting a method. Explain why it is appropriate, which assumptions it introduces and which evidence would show that it has failed.
• Apply “Answerable enquiry = bounded population + phenomenon + method + time and claim limit”. Define every term, preserve units or authority, and interpret the result in the original research synthesis context.
• Produce protocol, then separate raw evidence, processing, inference and judgement so another learner can audit the conclusion.
• Test and correct this misconception: a large sample repairs a biased design

Formula or reasoning frame

Answerable enquiry = bounded population + phenomenon + method + time and claim limit

Worked solution

1. Supplied research synthesis case for “questions, theory, literature and conceptual frameworks”: A draft question asks, 'Does feedback make every learner better?' Rewrite it as a bounded, answerable enquiry.
2. Select the matching frame, “Answerable enquiry = bounded population + phenomenon + method + time and claim limit”, and identify the exact quantities or textual details provided by the case before applying it.
3. State the condition that makes this frame relevant, including the unit, population, source or decision boundary where applicable; do not supply missing facts as if they were observed.
4. Worked solution: For example: 'In this class, how do learners describe the usefulness of written feedback on a specified writing task over four weeks?' This identifies group, feedback form, task and period, and asks about reported experience rather than claiming a universal causal effect.
5. Check the method against “a large sample repairs a biased design”; explain which supplied fact supports the conclusion and which further evidence would be needed to generalise it.

Teaching explanation

• Define the key ideas inside “quantitative, qualitative and mixed methods”, give an example and a non-example, and connect them to the previous chapter rather than learning isolated vocabulary.
• Use this subject method: register sources, inclusion criteria and analytical decisions. Explain why it is appropriate, which assumptions it introduces and which evidence would show that it has failed.
• Apply “Response rate = completed responses ÷ eligible invitations × 100%”. Define every term, preserve units or authority, and interpret the result in the original research synthesis context.
• Produce source and decision log, then separate raw evidence, processing, inference and judgement so another learner can audit the conclusion.
• Test and correct this misconception: statistical significance proves practical importance

Formula or reasoning frame

Response rate = completed responses ÷ eligible invitations × 100%

Worked solution

1. Supplied research synthesis case for “quantitative, qualitative and mixed methods”: A synthetic survey receives 18 completed responses from 30 eligible invitations. Find its response rate.
2. Select the matching frame, “Response rate = completed responses ÷ eligible invitations × 100%”, and identify the exact quantities or textual details provided by the case before applying it.
3. State the condition that makes this frame relevant, including the unit, population, source or decision boundary where applicable; do not supply missing facts as if they were observed.
4. Worked solution: Response rate = 18 ÷ 30 × 100 = 60%. The rate describes participation among those invited; it does not show that respondents represent all eligible people or that answers are unbiased.
5. Check the method against “statistical significance proves practical importance”; explain which supplied fact supports the conclusion and which further evidence would be needed to generalise it.

Teaching explanation

• Define the key ideas inside “sampling, validity, reliability, reflexivity and ethics”, give an example and a non-example, and connect them to the previous chapter rather than learning isolated vocabulary.
• Use this subject method: protect consent, privacy, safeguarding and withdrawal. Explain why it is appropriate, which assumptions it introduces and which evidence would show that it has failed.
• Apply “Voluntary-response participation = replies ÷ eligible learners × 100%; representativeness needs separate evidence”. Define every term, preserve units or authority, and interpret the result in the original research synthesis context.
• Produce ethical review, then separate raw evidence, processing, inference and judgement so another learner can audit the conclusion.
• Test and correct this misconception: many citations guarantee a sound literature review

Formula or reasoning frame

Voluntary-response participation = replies ÷ eligible learners × 100%; representativeness needs separate evidence

Worked solution

1. Supplied research synthesis case for “sampling, validity, reliability, reflexivity and ethics”: A voluntary notice receives eight replies from 40 eligible learners. Identify the sampling limitation.
2. Select the matching frame, “Voluntary-response participation = replies ÷ eligible learners × 100%; representativeness needs separate evidence”, and identify the exact quantities or textual details provided by the case before applying it.
3. State the condition that makes this frame relevant, including the unit, population, source or decision boundary where applicable; do not supply missing facts as if they were observed.
4. Worked solution: Only 8/40 = 20% chose to respond. Learners with strong views or easier access may be overrepresented; neither the size nor direction of that bias can be determined from the count alone. No identifiable learner data is needed for this exercise.
5. Check the method against “many citations guarantee a sound literature review”; explain which supplied fact supports the conclusion and which further evidence would be needed to generalise it.

Teaching explanation

• Define the key ideas inside “analysis, argument, peer review, impact and defence”, give an example and a non-example, and connect them to the previous chapter rather than learning isolated vocabulary.
• Use this subject method: distinguish description, association, inference and causation. Explain why it is appropriate, which assumptions it introduces and which evidence would show that it has failed.
• Apply “Descriptive percentage-point difference = later percentage − earlier percentage; causation needs stronger design”. Define every term, preserve units or authority, and interpret the result in the original research synthesis context.
• Produce analysis trail, then separate raw evidence, processing, inference and judgement so another learner can audit the conclusion.
• Test and correct this misconception: a large sample repairs a biased design

Formula or reasoning frame

Descriptive percentage-point difference = later percentage − earlier percentage; causation needs stronger design

Worked solution

1. Supplied research synthesis case for “analysis, argument, peer review, impact and defence”: In synthetic class summaries, 6 of 10 answer an item correctly before a workshop and 8 of 10 answer a related item afterwards. State what the data show.
2. Select the matching frame, “Descriptive percentage-point difference = later percentage − earlier percentage; causation needs stronger design”, and identify the exact quantities or textual details provided by the case before applying it.
3. State the condition that makes this frame relevant, including the unit, population, source or decision boundary where applicable; do not supply missing facts as if they were observed.
4. Worked solution: The reported proportions are 60% and 80%, a 20-percentage-point difference. The figures alone do not establish the same learners changed, that the items had equal difficulty or that the workshop caused the difference.
5. Check the method against “a large sample repairs a biased design”; explain which supplied fact supports the conclusion and which further evidence would be needed to generalise it.