Case Study
×Refunds Done Right: From a Training Need to a Course
What does a course look like when it is built to close one measured gap and to show whether it did?
Try the Course Design Document (PDF)
Key Takeaways
The course targets two errors a check found, not a topic.
After a policy change, agents used the wrong time limit and ended replies without a time frame. Every objective is written against one of those errors.
Learners decide before they are taught, then practise once a week for a month.
The module opens with three cases decided before any rules. Worked examples fade into cases with a step missing. Four ten-minute sets bring the rules back a week apart.
Evaluation was designed before the course was built.
The same ten-question check runs before and after, a second team starts four weeks later as a comparison, and one business figure is agreed in advance.
The Need
This case follows on from Finding Where Training Is Needed, where the model can be run. In an invented online retailer, Hartwell Home, the needs register opened a row for one customer service team. Its reopened tickets rose from about 9% to 16% over two months while the rest of the department stayed flat.
A ten-minute check on the linked skills found two problems. Agents applied the refund policy wrongly 38% of the time, usually with the wrong time limit. They gave no clear next step 34% of the time, usually with no time frame. The figures are illustrative.
Before anything was built, three other causes were ruled out: a new tool, staffing, and an out-of-date document. The refund policy had changed in the spring and only some agents had learned it. Two problems were passed on rather than trained: the internal policy summary still showed the old time limit, and the refund screen did not show the purchase date.
The Learners
The course is for agents already in the job, from 3 months to 5 years. They handle refunds every day. It is a refresher after a policy change, not an induction, and it fits into one 30-minute session and ten minutes a week.
The Objectives
Each objective targets one error the check found. By the end, an agent can:
- Choose the right outcome (refund, repair, replacement or decline) under the current policy and consumer law.
- Keep responsibility with the company: never send a customer to the manufacturer, and never ask for proof of a fault in the first two years.
- End every reply with who does what next, and by when.
- Check a reply against three points before sending it.
The Design
The module has five lessons.
| Lesson | What happens | Why |
|---|---|---|
| Three Customers | Agents decide three cases before seeing any rules, then see model answers | Attempting first shows each agent where their habits differ from the policy |
| The Policy on One Page | The rules as one decision table | A table is what agents use at work |
| Watch It Done | Two cases worked step by step, a prediction question, a sorting task | Worked examples suit learners meeting a new rule set |
| Your Turn | Three cases, each with one step missing | Fading the steps moves agents from watching to doing |
| Before You Send | A three-point check | A short routine to use on the job |
Four practice sets follow, one a week. Each has six questions that mix the skills, so agents first decide which rule applies. Before seeing each answer, they say how sure they are. A confident wrong answer shows a rule someone is applying wrongly without knowing it. Each answer shows which rule applied and why, never a score against colleagues. The policy table is open in week 1, a link away in week 2, and gone in weeks 3 and 4.
The Law
The first draft of Hartwell’s policy was invented, and it broke Spanish consumer law: it passed faults after 60 days to the manufacturer’s warranty. The course now teaches the real rules. Goods carry a 3-year guarantee. A fault that appears in the first 2 years is presumed present at delivery. The seller repairs or replaces first, and refunds if that fails. Hartwell’s own extras, a 30-day change-of-mind window and a 48-hour rule for damage, sit on top of the law.
Building It with AI
The module was drafted with Articulate 360’s AI from content written in advance, then edited by hand in Rise. The draft needed six changes:
| What the AI did | Why it mattered | Change made |
|---|---|---|
| Merged two lessons and repeated the practice cases | Learners would answer the same cases twice | One set of cases, lessons reordered |
| Opened with “trust your instincts” and “respond before you check the policy” | It taught the opposite of the course | Decide now, then compare with the policy |
| Shortened a change-of-mind case to “looks different from the photo” | An item unlike its description counts as faulty, so the wrong answer became arguable | Rewritten as a plain change of mind |
| Said returns must be in “original condition” | Agents would refuse returns without the box | “The condition it arrived in” |
| Wrote a question with two correct answers | A right answer would be marked wrong | One option replaced |
| Oversold the course (“master”, “empowers you”) | Experienced staff switch off | A plain description naming the need |
The Evaluation
The evaluation was planned before the course was built.
| Question | Measure | When |
|---|---|---|
| Did they learn it? | The same ten-question check, scored by skill | Before the module and after week 4 |
| Do they do it at work? | Reopened tickets, and a sample of refund replies scored on the four objectives | Eight weeks before and after |
| Was it the training? | A second team that starts four weeks later | Weeks 0 to 4 |
| Did they find it useful? | Three questions, recorded but not counted as evidence of learning | Week 4 |
Results are reported by team and skill only, never by name, and never for a group under five. Nothing goes into a performance review. The register row closes when the reopen rate is back in line and the comparison team shows the change came from the training.
Limits
Hartwell Home, its figures and its teams are invented. The check scores are illustrative. A small group of volunteers will take the check, the course and the check again, and a group that size shows change, not cause. The business figure is designed and simulated in the data model, not observed in a real company.
Sources
Learning-science references are from the project's How People Learn research. The legal rules summarise Spanish consumer law for teaching and are not legal advice.
Learning Design
- Kapur, M. (2008). Productive failure. Cognition and Instruction 26(3), 379-424.
- Renkl, A. and Atkinson, R. K. (2003). Structuring the transition from example study to problem solving in cognitive skill acquisition. Educational Psychologist 38(1), 15-22.
- Roediger, H. L. and Karpicke, J. D. (2006). Test-enhanced learning. Psychological Science 17(3), 249-255.
- Cepeda, N. J. and colleagues (2006). Distributed practice in verbal recall tasks. Psychological Bulletin 132(3), 354-380.
- Rohrer, D. and Taylor, K. (2007). The shuffling of mathematics problems improves learning. Instructional Science 35, 481-498.
- Butterfield, B. and Metcalfe, J. (2001). Errors committed with high confidence are hypercorrected. Journal of Experimental Psychology: Learning, Memory, and Cognition 27(6), 1491-1494.
- Kluger, A. N. and DeNisi, A. (1996). The effects of feedback interventions on performance. Psychological Bulletin 119(2), 254-284.
Analysis and Evaluation
- Moore, C. (2017). Map It: The Hands-On Guide to Strategic Training Design.
- Kirkpatrick, D. L. and Kirkpatrick, J. D. (2006). Evaluating Training Programs, 3rd edition.
- Alliger, G. M. and colleagues (1997). A meta-analysis of the relations among training criteria. Personnel Psychology 50(2), 341-358.
The Law in the Course
- Real Decreto-ley 7/2021 (Spain): the 3-year legal guarantee for goods, in force from 1 January 2022.
- Directive 2011/83/EU on consumer rights: the 14-day right of withdrawal.