How would you structure a validation plan to assess whether a training program actually improves job performance?

• A. Only collect post-training performance data.
• B. Rely solely on trainer impressions.
• C. Define performance criteria, collect baseline data, implement controlled or quasi-experimental design, gather qualitative feedback, measure post-training performance over time, analyze results.
• D. Skip baseline data.

Answer: (C)

Assessing whether training actually improves job performance relies on establishing what good performance looks like, knowing where you started, and tracking changes in a way that lets you link any gains to the training rather than to other factors. Start by defining clear performance criteria so you know precisely what counts as improvement. Then collect baseline data before the training so you have a starting point to compare against. Use a controlled or quasi-experimental design to separate the training effect from other influences like changes in the work environment or time. Gather qualitative feedback from participants and supervisors to capture insights about how the training translates to real work. Measure post-training performance over time to assess both initial impact and whether the improvement endures or transfers to the job. Finally, analyze the results to draw evidence-based conclusions about effectiveness.

This approach matters because it builds a valid, evidence-based picture of impact rather than relying on impressions or single-point measurements. Collecting baseline data is essential to quantify change, and a design with controls helps attribute change to the training itself. Relying only on post-training data, trainer impressions, or skipping baseline data leaves you with incomplete or biased conclusions about actual performance improvements.