For information and reference only – not to be submitted as your own work. Use this extract to see how a 5CO02 answer is structured and how survey arithmetic is shown, then build your own response from your own evidence, your own spreadsheet and your centre’s rules. The assessment is your own work, and the brief states that AI must not be used to generate content.
This sample covers CIPD Level 5 Associate Diploma in People Management (Organisational Learning and Development pathway), unit 5CO02 Evidence-based practice, in the 2026 “Camellia” version delivered through a centre such as Reed Learning. It gives a short Task 1 extract (AC1.1) and a worked Task 2 data analysis (AC2.1 to AC2.3).
The unit requirements are summarised on our 5CO02 evidence-based practice assessment brief page.
Important: the real pulse-survey spreadsheet is issued to learners and is not reproduced here. Every survey figure below is invented to demonstrate the method and is labelled “(illustrative)”. Replace it with your own data.
Scenario in brief
You work for Analytics Insights, a people-data consultancy. A former colleague, now Head of People at Camellia, a UK plant-based cosmetics company, wants the People Department to use data more convincingly. Camellia’s priorities are recruitment and selection, onboarding, reward and learning and development. Task 1 is a report of around 2,900 words; Task 2 is a data analysis of about 1,000 words.
Task 1 extract – AC1.1: evidence-based practice at Camellia
Evidence-based practice means making decisions by combining the best available evidence from several sources, rather than relying on habit or fashion. Barends, Rousseau and Briner (2014) describe four sources: scientific literature, organisational data, practitioner expertise and stakeholder values. CIPD (no date) presents the same idea as a way of reducing bias and improving the quality of people decisions.
Its main strength is discipline. Its main weakness is that evidence is often incomplete, and a small team may lack time to appraise research properly (Rousseau, 2020). A balanced evaluation must say both.
Example 1 – selection methods
If Camellia’s hiring managers favour unstructured interviews, the People Team could compare that habit with meta-analytic evidence that structured interviews and work samples predict performance better (Schmidt and Hunter, 1998), then test the change against Camellia’s own early-turnover figures.
Example 2 – learning and development spend
Before buying another off-the-shelf course library, the team could combine published evidence on transfer of training with its own completion and application data, and ask line managers what actually stops people using new skills.
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Task 2 – AC2.1: calculating percentages and means (illustrative)
The method has four steps. First, count the responses for each option on each statement. Second, divide each count by the number of respondents (46) and multiply by 100. Third, round to a whole number, as the brief asks. Fourth, calculate the mean by multiplying each option’s score (1 to 5) by its count, adding the results and dividing by 46, then round the mean to a whole number as the brief requires. Keep the 2 dp value in your working so the rounding is visible.
Worked example for the first statement (illustrative): counts of 3, 7, 9, 19 and 8 give percentages of 7%, 15%, 20%, 41% and 17%. The mean is (1×3 + 2×7 + 3×9 + 4×19 + 5×8) ÷ 46 = 160 ÷ 46 = 3.48 (working value, 2 dp), reported as 3 when rounded to a whole number.
| Statement (illustrative) | Strongly disagree | Disagree | Neutral | Agree | Strongly agree | Mean (whole number; 2 dp working) |
|---|---|---|---|---|---|---|
| S1 I know which L&D opportunities are open to me | 3 (7%) | 7 (15%) | 9 (20%) | 19 (41%) | 8 (17%) | 3 (3.48) |
| S2 My manager supports my development time | 2 (4%) | 6 (13%) | 11 (24%) | 18 (39%) | 9 (20%) | 4 (3.57) |
| S3 Induction training prepared me for my role | 1 (2%) | 4 (9%) | 8 (17%) | 22 (48%) | 11 (24%) | 4 (3.83) |
| S4 L&D content is relevant to my daily work | 4 (9%) | 9 (20%) | 12 (26%) | 15 (33%) | 6 (13%) | 3 (3.22) |
| S5 I can apply what I learn within a month | 3 (7%) | 8 (17%) | 14 (30%) | 16 (35%) | 5 (11%) | 3 (3.26) |
| S6 Digital learning is easy to access | 1 (2%) | 3 (7%) | 7 (15%) | 21 (46%) | 14 (30%) | 4 (3.96) |
| S7 L&D is linked to career progression | 6 (13%) | 12 (26%) | 13 (28%) | 10 (22%) | 5 (11%) | 3 (2.91) |
| S8 I am asked for feedback on training | 7 (15%) | 14 (30%) | 11 (24%) | 9 (20%) | 5 (11%) | 3 (2.80) |
| S9 Overall, I am satisfied with L&D | 2 (4%) | 7 (15%) | 12 (26%) | 18 (39%) | 7 (15%) | 3 (3.46) |
Each row totals 46 responses. Rounded percentages can add to 99% or 101% (S4 adds to 101% and S9 to 99% here). That is a rounding effect, not an error; say so in a note under your table.
AC2.2: choosing and interpreting two charts
Use two different chart types because they answer different questions. A bar chart of means ranks the nine statements at a glance. A 100% stacked bar of response percentages shows how opinion is split, which a mean can hide.
Chart 1 – bar chart of mean scores (illustrative)
Draw nine horizontal bars from 1 to 5, ordered from highest to lowest. Label each bar with its whole-number mean (and the 2 dp value if space allows) and add a dotted line at the neutral midpoint of 3. Rank the bars using the 2 dp working values, because rounding creates ties.
| Rank | Statement | Mean (whole number; 2 dp working) |
|---|---|---|
| 1 | S6 Digital learning access | 4 (3.96) |
| 2 | S3 Induction preparation | 4 (3.83) |
| 3 | S2 Manager support | 4 (3.57) |
| 4 | S1 Awareness of opportunities | 3 (3.48) |
| 5 | S9 Overall satisfaction | 3 (3.46) |
| 6 | S5 Applying learning | 3 (3.26) |
| 7 | S4 Relevance | 3 (3.22) |
| 8 | S7 Career link | 3 (2.91) |
| 9 | S8 Feedback sought | 3 (2.80) |
Interpretation (illustrative): access and induction score best (both round to 4), while career progression (2.91) and feedback (2.80) sit just below the neutral point of 3. Both display as 3 once rounded, so use the 2 dp working values and the response percentages to make that point. Treat means with care. Likert items are ordinal, so a mean is a convenient summary rather than a precise measurement (Jamieson, 2004), and 46 respondents is a small base.
Chart 2 – 100% stacked bar of response percentages (illustrative)
Draw one bar per statement, split into the five options, with disagreement on the left in one colour family and agreement on the right in another. Neutral sits in the middle in grey.
Interpretation (illustrative): on S8, 21 of 46 respondents (46%) disagree or strongly disagree, against 14 (30%) who agree or strongly agree, so the problem is widespread, not a handful of unhappy voices. On S3, 72% agree or strongly agree, which supports keeping the induction design. The stacked view also shows that S7 has a high neutral share (28%), which could mean employees do not understand the career pathways rather than reject them.
AC2.3: recommendations to improve L&D
Good recommendations point back to the data, name a benefit, admit a risk and give a rough financial implication. Costs below are illustrative assumptions; use figures supported by your scenario or clearly marked assumptions.
| Recommendation | Evidence from data | Benefit | Risk | Financial implication |
|---|---|---|---|---|
| 1 Add a career-pathway map and a development conversation to each appraisal cycle | S7 mean 3 (2.91); 28% neutral | Clearer links between learning and progression; may support retention | Raises expectations the business cannot meet | Mostly manager time; small design cost (illustrative) |
| 2 Run a short feedback loop after every course, with action reported back | S8 mean 3 (2.80); 46% disagree | Better content and a stronger evidence base for future purchasing | Survey fatigue | Low; existing survey tool (illustrative) |
| 3 Brief line managers on protecting learning time and following up | S2 and S5 only moderately positive | Better transfer of learning into work | Short-term workload pressure | Indirect cost of hours away from work (illustrative) |
Support each recommendation with literature. For instance, evaluating training beyond reactions, at the level of behaviour and results, is a long-standing principle (Kirkpatrick and Kirkpatrick, 2006), and the CIPD (no date) stresses combining internal data with research before committing budget. Add a sentence saying that a single pulse survey cannot prove cause and effect, so Camellia should track the same statements again in six months.
Keep the whole of Task 2 near 1,000 words. Tables and charts are excluded from the count, but going more than 10% over the limit risks a refer.
If you want help with the data side of a CIPD report, see our statistics writing help and read the companion guide on calculating Likert percentages and means for 5CO02.
You can also send your brief through the assignment submission form for a quote, or check student feedback on the reviews page first.
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References
Barends, E., Rousseau, D.M. and Briner, R.B. (2014) Evidence-based management: the basic principles. Amsterdam: Center for Evidence-Based Management.
CIPD (no date) Evidence-based practice for effective decision-making [factsheet]. London: Chartered Institute of Personnel and Development. Available at: https://www.cipd.org/uk/knowledge/factsheets/evidence-based-practice-factsheet (Accessed: 12 October 2026).
Jamieson, S. (2004) ‘Likert scales: how to (ab)use them’, Medical Education, 38(12), pp. 1217–1218.
Kirkpatrick, D.L. and Kirkpatrick, J.D. (2006) Evaluating training programs: the four levels. 3rd edn. San Francisco: Berrett-Koehler.
Rousseau, D.M. (2020) ‘Making evidence-based organizational decisions in an uncertain world’, Organizational Dynamics, 49(1), 100756.
Schmidt, F.L. and Hunter, J.E. (1998) ‘The validity and utility of selection methods in personnel psychology: practical and theoretical implications of 85 years of research findings’, Psychological Bulletin, 124(2), pp. 262–274.