What are the most common mistakes you make when evaluating your training methods?

1 Not defining clear criteria

One of the first steps in evaluating your training methods is to define clear and measurable criteria for success. These criteria should be based on your learning objectives, your target audience, and your desired outcomes. Without clear criteria, you might end up measuring the wrong things, using inappropriate tools, or missing important feedback. To avoid this mistake, you should write down your criteria before designing or delivering your training and make sure they are SMART: specific, measurable, achievable, relevant, and time-bound.

2 Not choosing the right methods

Another common mistake is to choose the wrong evaluation methods for your training. There are many evaluation methods available, such as surveys, quizzes, observations, interviews, focus groups, tests, or simulations. However, not all methods are suitable for all types of training, goals, or contexts. For example, a survey might be useful for measuring satisfaction or reactions, but not for measuring skills or behaviors. A test might be useful for measuring knowledge or comprehension, but not for measuring attitudes or motivation. To avoid this mistake, you should match your evaluation methods to your criteria, your learning objectives, and your training format.

3 Not collecting enough data

A third common mistake is to collect insufficient or incomplete data for your evaluation. This can happen if you only rely on one source of data, such as self-reports or trainer observations, or if you only collect data at one point in time, such as before or after the training. This can limit your ability to capture the full range of effects, outcomes, and feedback from your training. To avoid this mistake, you should use multiple sources of data, such as learners, trainers, managers, or peers, and collect data at multiple points in time, such as before, during, and after the training, or even longer.

4 Not analyzing the data properly

A fourth common mistake is to analyze the data incorrectly or inadequately for your evaluation. This can happen if you use inappropriate or inaccurate statistical methods, such as using averages or percentages without considering the sample size or the distribution of the data. It can also happen if you ignore or overlook important factors, such as the context, the baseline, or the confounding variables that might affect your results. To avoid this mistake, you should use appropriate and accurate statistical methods, such as comparing means, testing hypotheses, or calculating effect sizes. You should also consider the context, the baseline, and the confounding variables that might explain or influence your results.

5 Not communicating the results effectively

A fifth common mistake is to communicate the results poorly or not at all for your evaluation. This can happen if you use jargon, technical terms, or complex charts that are not understandable or relevant for your audience. It can also happen if you do not share the results with the stakeholders, such as the learners, the trainers, the managers, or the sponsors, who might benefit from or act on the results. To avoid this mistake, you should use simple, clear, and concise language and visuals that are tailored to your audience. You should also share the results with the stakeholders and provide recommendations, feedback, or action plans based on the results.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?