Letting AI write your quiz: what works, and what to reread
AI writes twenty questions in a minute. Three of them are bad, and it is always the same three. How to spot them before the session.
The notebook
Evaluating training, concretely
Articles on measuring what was learned, immediate and delayed evaluation, and what can actually be proved about a course.
Attendee data in training: what to decide before the session
Who is the controller, what may be projected, how long to keep answers. The questions worth settling before you ask a room to respond.
Why your follow-up questionnaire only gets 10% responses
A post-training questionnaire answered by a minority does not measure the training: it measures the motivation of the people who answered. The causes, in order of cost.
Building the evaluation evidence a quality audit asks for
What auditors commonly want to see on learning assessment, and how to produce it session by session instead of reconstructing a folder the night before.
Running a live quiz without turning the room into a contest
Projected quizzes motivate part of the group and expose the rest. How to get participation with no leaderboard, no names and no accounts.
The Kirkpatrick model, and why everyone stops at level 1
Kirkpatrick's four levels of training evaluation explained plainly, with what each level actually costs to measure: and why almost everyone stops at the first.
Measuring what was learned, competency by competency
One overall mark hides which idea landed and which did not. How to tag questions with competencies and read progress you can act on.
Immediate and delayed evaluation: what each one actually measures
Immediate evaluation captures satisfaction; delayed evaluation measures what stayed. Why both are needed, and why the second is almost never run.
How to evaluate a training course: the three moments that matter
A satisfaction sheet measures how the day felt, not what was learned. Here is how to evaluate training before, during and after: and what each moment actually tells you.