AI Learning Analytics Dashboard
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How is the whole group doing, in one view? Individual reports answer questions about individuals, and the question a course leader has is about thirty people at once: who is drifting, what is working, and where attention is worth spending this week.
A dashboard is many measures side by side. Its job is to make the outliers visible without reading thirty files.
Short answer: The AI Learning Analytics Dashboard is a free tool that turns cohort data into a single readable view. You paste what you have on a group, and it reports the pattern across several measures at once rather than one learner at a time.
What is AI Learning Analytics Dashboard?
It reads a group rather than a person. Attendance, submissions, marks, engagement notes and anything else you hold go in together, and what comes back is a view across all of them with the exceptions called out.
Why Use AI Learning Analytics Dashboard?
Because cohort data is usually held in several places and looked at one column at a time.
| How cohort data gets read | What it misses | What a combined view shows |
|---|---|---|
| Attendance register alone | Present students who submit nothing | The combination, which is the real signal |
| Marks alone | A falling student still passing | Direction as well as position |
| Class average | Both tails | The outliers at either end |
| One measure per meeting | Anybody who is fine on that measure | Students who are quietly failing on two |
Who Should Use It?
- Course leaders with a cohort and several spreadsheets
- Tutors and form staff responsible for a group's overall picture
- Training managers reporting on a programme's participants
- Anyone preparing for a review meeting who needs the exceptions named
- Small providers with no analytics platform of their own
A dashboard is only worth reading if you can confirm that:
- ✅ At least three measures are included
- ✅ Ranges and counts appear, not only averages
- ✅ Learners are identified by number, never by name
- ✅ The window matches your meeting cycle
- ✅ You asked for people on two or more warning signs
Each measure is good evidence of something and poor evidence of something else, which is why the combination matters.
| Measure | Good evidence of | Poor evidence of |
|---|---|---|
| Attendance | Access and opportunity | Understanding |
| Marks | Attainment at a point in time | Effort or direction |
| Submission timing | Workload pressure | Ability |
| Speaking in sessions | Confidence | Knowledge |
How Does AI Learning Analytics Dashboard Work?
The site runs every tool on a shared working surface, and tracking sits behind this generate button.
- Prompt box. It is labelled for the data, items or activity to track. Paste what you hold, in whatever untidy form it exists.
- Model selector. The model menu sits above the button, holding MSB AI, DeepSeek, OpenAI ChatGPT and the rest.
- Advanced options. Ten controls in the accordion, set out below.
- Generate. Your data and settings run through a prompt layer written for tracking.
- Result card. The dashboard appears with its word count beneath.
- Export row. DOC, TXT and HTML downloads sit under the card.
- Activity history. Previous dashboards remain below with copy, listen, reuse, download and open result.
Key Features
Dashboard as a format
Output Format includes Dashboard, which arranges several measures for a glance rather than a read.
Cohort level view
Describe a group and the report treats it as a group, naming the outliers rather than averaging them away.
Exceptions flagged
Flag Issues is what turns a table of numbers into a list of people worth a conversation.
Several metrics at once
Metric Priority sets which measure leads, and the others still appear around it.
Week on week comparison
The history panel keeps each dashboard, so this week reads against last week rather than in isolation.
Advanced Options Guide
Ten controls. The format and the flagging toggle are what separate a dashboard from a restated spreadsheet.
| Option | What it controls | Setting for a cohort dashboard |
|---|---|---|
| Tracking Focus | Progress, Performance, Goals, Tasks, Metrics, Milestones, Trends or Status | Metrics, or Status for a weekly board |
| Time Window | Daily, Weekly, Monthly, Quarterly, Yearly or Custom | Weekly or Monthly, matching your meeting cycle |
| Output Format | Dashboard, Table, Summary, Checklist, Report or Timeline | Dashboard |
| Metric Priority | Completion, Quality, Speed, Consistency, Growth or Efficiency | Consistency, since irregular engagement predicts trouble |
| Highlight Trends | Compares across the window | On |
| Flag Issues | Names the exceptions | On. This is the output you act on |
| Include Summary | Adds an overall position | On for a meeting |
| Age-Appropriate Language | Adjusts wording | Off for a staff document |
| Detail Level | Slider from 1 to 100 | Around 50. High detail rebuilds the spreadsheet |
| Custom Instructions | Free text up to 1000 characters | Which measures matter, and a request to name students on two or more warning signs |
Example Inputs
Bea runs a cohort of twenty four and has three separate spreadsheets. She opens the AI Learning Analytics Dashboard and pastes all three summaries with names replaced.
Cohort: 24 participants, week 7 of 12.
Attendance: 19 above 80%, three between 50 and 79%, two
below 50%.
Submissions: 21 of 24 submitted assignment 1. Of those, 4
were late. Assignment 2 due last week, 17 submitted.
Marks so far: range 41 to 88, median 64. Four below the
pass mark on assignment 1.
Engagement notes: five participants have never spoken in
a session. Two of those are the low attenders.
Tracking Focus = Metrics
Time Window = Weekly
Output Format = Dashboard
Metric Priority = Consistency
Highlight Trends = On
Flag Issues = On
Include Summary = On
Age-Appropriate Language = Off
Detail Level = 50
Custom Instructions = Use participant numbers, no names.
Name anybody showing two or more warning signs rather than
listing every measure separately. Tell me which single
intervention this week would reach the most at risk people.Example Outputs
The combination was the finding. Three participants appeared on both the low attendance list and the missing submission list, and two of those were also in the never spoken group, which is a different and much smaller problem than the twelve names the three separate spreadsheets had between them.
The recommended intervention was a single contact with those three rather than a general message to the cohort, on the reasoning that a broadcast reaches the people who are already fine. That is the kind of conclusion a combined view produces and a column by column read does not.
Pro tip Ask for the people appearing on two or more measures. Any single measure produces a long list and most of it is noise, whereas the intersection is short, actionable and almost always the group that genuinely needs contacting.
Caution Do not paste student names or identifying details. Use participant numbers and keep the key yourself, because cohort data about identifiable individuals is personal data and handing it to any external service creates an obligation you probably have not assessed. Everything useful here works on numbered rows.
Note A dashboard shows the current position across measures. If the question is about direction over a longer period rather than this week's exceptions, the AI Learning Trend Tracker is built for movement across time instead.
Two habits make the difference between a dashboard you act on and one you file:
- ✅ Every measure you hold is pasted, not just the marks
- ✅ Identifiers are replaced with numbers before anything leaves your machine
- ✅ The request asks for intersections rather than lists
- ✅ The window matches your actual meeting cycle
- ✅ Last week's dashboard is available to compare against
What works well
- Combines measures that normally live in separate files
- Names the intersection, which is where the real risk sits
- Turns three spreadsheets into one page before a meeting
- Free to use, with no account needed
What to watch for
- Never paste identifying student data
- It only knows the measures you supply
- It is not a live system and holds no data between runs
- High detail rebuilds the spreadsheet you were trying to summarise
AIToolsay is a free platform with a large library of AI tools, and this one sits in the learning analytics group. Each tool takes a single job, comes with its own controls, and runs on prompt engineering written for it, which is why a dashboard reads a cohort while a progress tracker reads a person. Nothing installs and no account is needed. The engine menu covers MSB AI, OpenAI ChatGPT, Google Gemini, Anthropic Claude AI, DeepSeek and more. Browse the neighbouring tools from the AIToolsay homepage.
Frequently Asked Questions
Is the AI Learning Analytics Dashboard free?
Yes, and the page works without an account.
Can I paste my class list?
Not with names or identifying details. Replace them with numbers and keep the key locally, since identifiable student data should not leave your systems.
Is this a live dashboard?
No. It produces a written view from data you paste, and nothing is stored or updated between runs.
How many measures should I include?
All of them. The value is in the combination, and a dashboard built on marks alone tells you what the marks already told you.
Why ask for intersections?
Because any single measure produces a long list. Students appearing on two or more are the short list worth acting on this week.
How often should I run it?
Match your meeting cycle, usually weekly or fortnightly, and keep each one so the comparison exists.
Cohort data usually contains a clear answer that nobody can see because it is spread across three files. Putting the measures beside each other, and asking for the overlap, is most of what analytics is for at this scale.
So open the AI Learning Analytics Dashboard, paste every measure with the names removed, and ask which participants appear on more than one warning sign. Thanks for reading, and I hope the short list is shorter than you expect. If the weekly view earns its place, the AIToolsay community is open to you, our social accounts announce every new tool, push notifications reach you first, and the newsletter carries guides in this style.
Let AI Speak.
Sabir
Founder of AIToolsay and a passionate AI enthusiast dedicated to building practical, user-friendly AI tools that simplify everyday tasks.
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