Course Effectiveness Report

Ask how a course is really landing and get a written read with an inline chart: pre versus post assessment scores, knowledge gain, and satisfaction across your recent cohorts, with the weak spots called out. Drafted on demand, grounded in your assessment data.

For L&D Specialists Instructional Designers Training Managers L&D Leaders
Sample prompt to Joy's Assistant

Put together an effectiveness read on [Consultative Selling]: compare pre and post assessment scores, the knowledge gain, and satisfaction, for our last [three cohorts].

What it can look like

An illustrative example. Your output will reflect your own sources, data, and prompts.

Put together an effectiveness read on Consultative Selling: compare pre and post assessment scores, the knowledge gain, and satisfaction, for our last three cohorts.

Reading the pre and post assessment scores plus satisfaction for the last three cohorts of Consultative Selling, the course is working, with one cohort standing out for the wrong reason. Here is the read.

Across the last three cohorts of Consultative Selling (96 learners), the course clears the bar. Average scores climbed from a 54% pre-assessment to an 81% post-assessment, a +27-point knowledge gain, with satisfaction at 4.4 out of 5 and completion at 94%.

+27 pts
Knowledge gain
▲ 54% to 81%
4.4/5
Satisfaction
94%
Completion

Where it gets interesting is the cohort-by-cohort comparison. Cohorts 1 and 2 look almost identical: pre-scores of 54% and 52% rising to 83% and 82%, gains of 29 and 30 points. Cohort 3 started in the same place, 55%, but landed at only 74% for a gain of just 19 points.

Pre vs post assessment average by cohort

CohortPre avgPost avgGain
Cohort 154%83%+29 pts
Cohort 252%82%+30 pts
Cohort 355%74%+19 pts

That 74% post-score is roughly 8 points below where the first two cohorts finished, and it is the one number pulling the blended average down. Cohort 3’s satisfaction dipped alongside it, which usually travels together. The differentiator I can see in the session records is the facilitator: Cohorts 1 and 2 ran with the same lead, Cohort 3 with a different one. That is the most likely cause of both the lower gain and the softer satisfaction.

The takeaway is a good-news one. The course works and works repeatably: two of three cohorts delivered a near-30-point gain from the same starting point, so the content and the assessment are sound. This is a facilitation fix for Cohort 3’s delivery, not a redesign of the course. Get the next run back to the stronger facilitator or coach the newer one, and this looks like a program you can stand behind with stakeholders.

Want me to break Cohort 3’s post-scores down by module to isolate where the drop is, or pull that cohort’s open-text satisfaction comments?

From a hunch about impact to a number you can defend

The Course Effectiveness Report recipe reads your pre and post assessment scores plus satisfaction on demand and returns a written analysis with one inline chart: average scores before and after by cohort, the knowledge gain, and the weak spot flagged with its likely cause. It’s drafted when you ask, not a board that runs on its own.

  1. Connect your assessment and satisfaction data

    Give Joy read-only access to your LMS or add an export with pre and post scores, satisfaction responses, and cohort records to the Knowledge Center.

  2. Ask for the effectiveness read

    Name the course and the cohorts you want compared. Joy reads the scores at ask time, computes the averages and the knowledge gain, and pulls satisfaction alongside.

  3. Read the analysis and chart

    Joy returns a short written read with one inline chart comparing pre and post averages by cohort, the gain and satisfaction called out, and any weak cohort flagged. The figures in the prose match the chart.

  4. Take it into the review

    Copy the read and numbers into your stakeholder update or program review. Joy drafts the analysis; you present it. Nothing is exported or scheduled for you.

  5. Make it one click for your team

    Save this ask as a custom command on the assistant your team already uses, so anyone can run it in one step.

Make it yours

Knowledge Gain, Computed

Averages pre and post scores by cohort and shows the point gain, so impact is a number, not a claim.

One Clear Chart

A single inline chart puts each cohort’s before and after side by side, so an underperformer is unmistakable.

Weak Spot Flagged

Calls out the cohort that gained less and the most likely cause, from satisfaction and session records.

Trace It to the Source

Follow up to break a cohort down by module or read its comments, and Joy re-reads to help you find the fix.

By Module

Break a cohort’s post-scores down by module to isolate exactly which section the drop sits in.

By Facilitator

Compare gain and satisfaction across facilitators to see whether delivery is driving the difference.

Trend Across Cohorts

Line up gain over successive cohorts to see whether the course is getting stronger or slipping.

Satisfaction Read

Pull the open-text comments for a cohort to explain a satisfaction dip in the learners’ own words.

Frequently Asked Questions

Is this a report file Joy generates and sends?

No. Despite the name, the report is a written analysis drafted on demand in chat, with one inline chart. You copy it into your own review or stakeholder update. Joy doesn’t auto-generate a file, email it, or run it on a schedule.

How is the knowledge gain calculated?

Joy averages the pre-assessment and post-assessment scores for each cohort and reports the difference in points. In the example, an average of 54% before rising to 81% after is a +27-point gain across the three cohorts.

Can it flag which cohort underperformed?

Yes. Joy compares each cohort’s gain and satisfaction and calls out the weak one. In the example it flags Cohort 3, whose 19-point gain and softer satisfaction line up with a different facilitator.

Does the chart match the written numbers?

Always. The pre and post averages in the prose are the same ones in the inline chart (Cohort 1 at 54 and 83, and so on), so you can quote either in your review without reconciling them.

Can I dig into why a cohort dipped?

Yes. Ask a follow-up and Joy re-reads the data to break a cohort’s post-scores down by module or pull its open-text satisfaction comments, so you can trace a drop to a specific section or delivery issue.

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