Knowledge assessment

Jan 9, 2024

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The assessment of knowledge is a quite different issue from that of training evaluation based on surveys. Knowledge assessment is the objective measurement of the outcomes that were the subject of the training, while satisfaction evaluation is, by nature, a subjective measurement.

Knowledge assessment

Why is assessing knowledge important?

Knowledge assessment and training evaluation are useful and relevant, but it's common for training evaluation to not sufficiently integrate knowledge assessment. One of the reasons is simply that the tools used for surveys are very different from knowledge measurement tools, and often the solutions deployed for training evaluation do not cater to both.

However, the need is very clear. The very purpose of training is to acquire knowledge and skills that were not previously possessed. Measuring satisfaction without measuring acquired knowledge is like evaluating a diet whose ultimate goal was weight loss, not with a scale, but with a satisfaction questionnaire.

Participant satisfaction is always a relevant measure, but knowing that the objective has been factually achieved is no less interesting. Not only to know it but to be able to demonstrate and quantify it.

One of ExperQuiz's characteristics is to address this dual need with the same set of tools: satisfaction evaluation and knowledge measurement.

Reporting the added value of training

For a client, as well as for the training financier, be it a company or an OPCO, the most important thing is not just knowing that the trainee left content. What's important is knowing that their money has served a purpose, that the investment in training has achieved its primary goal: the acquisition of skills.

From this perspective, a training evaluation that does not integrate the measurement of acquired knowledge is insufficient. One could even say: if a choice had to be made, it should be the evaluation of the acquired skills that should remain.

Measuring before/after knowledge

It's important to measure not only the knowledge held at the end of the training but truly the acquired knowledge, i.e., the difference between before and after the training. A good level of knowledge post-training, when it was already good beforehand, would rather indicate that participants did not need this training.

This implies starting any training with an initial knowledge assessment. This will have a dual purpose:

  1. It will validate the prerequisites necessary for this training, confirming or refining the need for training itself.
  2. It will set a milestone for the measurement of acquired knowledge, which will be the subject of a second evaluation at the end of training.

Ideally, this evaluation could take place in the enrollment process itself, as it's crucial to know if the training is genuinely suitable and if the prerequisites are well validated.

Specifics of knowledge assessment

Knowledge assessment, the evaluation of knowledge and skills, is a richer and more complex issue than collecting information through surveys.

Firstly, it relies on tests, which are pedagogical content specific to each theme, and practically to each training. Implementing a knowledge measurement system requires a more significant investment in preparing content, i.e., question bases. However, these pedagogical contents will not have evaluation as their sole purpose; they are also tools for work, serving the training. It's proven that immediate activations of knowledge represented by answering questions are one of the best ways to learn.

Knowledge assessment will involve a variety of question types, which may include questions dedicated to the evaluation of soft skills or even open-ended questions that will be subject to manual correction and grading.

To learn more about best practices in assessment, request the white papers offered by ExperQuiz:

  1. Best practices for the design and deployment of assessments in business: the challenges of evaluation, evaluation pedagogy, diversity of use cases in business, best practices for question and questionnaire development.
  2. Improving the quality of your tests through statistics: average, standard deviation, standard scores, weighting, correlation, interquartile range, KR20 and margin of error, how to identify questions that need revision.
  3. Best practices in training evaluation: learner, manager, trainer satisfaction, measurement of acquired knowledge, the 3 levels of Kirkpatrick, automation.

Extending Training Programs

If a evaluation system has been implemented to engage learners at various intervals following their training, and this system is already used to gather satisfaction feedback and measure acquired knowledge, why not go further by using the same tools?

This is what can be termed "extending the training," meaning utilizing the weeks and months following the training to offer participants activities to maintain the acquired knowledge.

For instance, participants can be regularly presented with a small test: one question per day for 60 days or 5 questions every Monday morning for 3 months. Regardless of the chosen frequency, the idea is to maintain knowledge through regular activations.

Everyone has heard of the forgetting curve: knowledge acquired initially is quickly forgotten, but each time it's reactivated, refreshed, it will be forgotten more slowly. The forgetting curve is in less decline until, eventually, the knowledge, activated sufficiently, becomes permanent.

It should be emphasized that this is implemented with the same tools, without any additional effort: if these tools are available, the additional cost is zero, and, on the contrary, the service can be billed specifically in some cases.

Of course, these maintenance activities should be optional and accepted by the trainee. The requests are not binding, and everyone will be free to decide that today, they do not have the time to dedicate to them. However, experience teaches us that trainees readily engage in the process.

Micro-learning and adaptive-learning

This extension of training can take the form of regular, spaced-out engagements, and this is what is called micro-learning: learning distilled in small doses over time.

To be effective, micro-learning must be associated with adaptive-learning, meaning personalization of each engagement, each exercise, based on the results already obtained. This combination of micro-learning and adaptive-learning is one of the strengths of the ExperQuiz solution.

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