Lesson Plan

• Describe the five quality criteria—accuracy, relevance, age, detail, and completeness—and their impact on decision‑making.
• Analyse a data set using a checklist to assess each criterion.
• Apply evaluation techniques to improve data suitability for reporting.
• Justify decisions to accept, reject, or request additional information based on the evaluation results.

• Projector or interactive whiteboard
• Slide deck summarising the five criteria
• Sample CSV file of a market survey
• Printed evaluation checklist handout
• Laptops with spreadsheet software (e.g., Excel)
• Whiteboard markers

Begin with a quick think‑pair‑share on why poor data quality can cause costly mistakes. Link this to students’ prior experience analysing data in previous lessons. Explain that by the end of the session they will be able to evaluate information against five clear criteria and decide its fitness for use.

1. Do‑now (5'): Students list reasons why data quality matters; teacher records key points.
2. Mini‑lecture (10'): Present the five criteria with real‑world examples using slides.
3. Guided practice (15'): In pairs, students use the printed checklist to evaluate the sample CSV file displayed on the screen; teacher circulates to support.
4. Whole‑class debrief (10'): Groups share findings; discuss common errors and corrective actions.
5. Application activity (15'): Each pair creates a brief evaluation report for a new data set, stating whether it should be accepted or if more data is required.
6. Check for understanding (5'): Quick quiz (Kahoot/exit ticket) with three scenario questions to confirm mastery.

Recap the systematic five‑step evaluation process and highlight how it supports reliable reporting. Students complete an exit ticket summarising one improvement they will make when handling future data. Assign homework: evaluate a personal data set (e.g., fitness tracker logs) using the checklist and bring the report to the next lesson.