MWA Analytics Dashboard

Block plugin for Moodle 4.1+ — Learning Analytics dashboard for instructors, built as part of a Master's research project at IFES/CEFOR in the context of Distance Education (EaD) and teacher training.

Overview

MWA Analytics Dashboard transforms Moodle course logs and grade data into actionable pedagogical intelligence. Instead of navigating scattered reports, the instructor sees in one screen: which students are at risk, which activities are blocking the class, when students are most active, and what to do right now — all generated from real Moodle data.

With integrated AI, the plugin goes beyond numbers: it diagnoses each student's situation individually, generates personalised study plans, suggests improvements to course activities, and writes pedagogical messages ready to send. Instructors receive concrete guidance, not just raw data.

Requirements

| Item | Minimum |
|------|---------|
| Moodle | 4.1 (build 2022112800) |
| PHP | 7.4 |
| Moodle email | Configured (for email send type) |
| AI server (optional) | Any HTTP endpoint compatible with the MWA payload format |

Installation

1. Download the plugin ZIP from the Moodle Plugins Directory


2. Go to Site Administration ' Plugins ' Install plugins


3. Upload the ZIP and follow the prompts


4. Go to Site Administration ' Plugins ' Blocks ' MWA Dashboard ' Settings to configure the AI server (optional) and verify Moodle email settings


5. Add the MWA Analytics Dashboard block to any course page


6. Click Open Dashboard — the plugin fetches logs and grades automatically

Alternative: Extract the ZIP into <moodle_root>/blocks/mwa_dashboard/ and visit the admin notifications page.

Configuration

All settings are under Site Administration ' Plugins ' Blocks ' MWA Dashboard.

AI Server (optional)

AI features (individual recommendations, personalised plans, content analysis, message generation, class chat) require an external AI server. Without configuration, all other dashboard features work normally — only AI buttons are disabled.

| Setting | Description | Example |
|---------|-------------|---------|
| Endpoint URL | Base URL of the AI server. The plugin calls POST {endpoint}/ia for recommendations and POST {endpoint}/chat for the chat tab. Leave blank to disable all AI features. | https://your-server.com |
| API Key | Optional X-API-Key header sent with every request to protect your endpoint. | my-secret-key |
| Provider | Google Gemini or OpenAI (GPT-4o) — the server must support the chosen provider. | Google Gemini |
| Timeout | Maximum seconds to wait for the AI response (default: 90 s). | 90 |

AI payload format — the plugin sends:

[{

  "nomecompleto": "Student Name or Class",

  "instrucao": "<generated prompt with real course data>",

  "contexto": "Dashboard MWA"

}]

The server must respond with { "resposta": "..." }, { "response": "..." } or { "content": "..." }.

AI-powered features:

• 🔮 Individual engagement prediction with diagnosis and immediate action


• 🎯 Personalised 4-section study plan per student


• 
  
  
  
  • Content analysis — bottleneck diagnosis per activity + 3 course-level suggestions
  
  
  
  


• " Generate message with AI — subject and body tailored to each student's context


• ' Chat with the class — ask the AI anything using live course data as context


• 
  
  
  
  • Per-activity AI button — specific improvement suggestions for each stuck activity
  
  
  
  

Moodle Email (SMTP)

Email sending uses Moodle's own email_to_user() function. To set it up:

1. Go to Site Administration ' Server ' Email ' Outgoing mail configuration


2. Configure your SMTP host, port, username and password


3. Use the "Test outgoing mail configuration" button to confirm it works

No additional configuration is needed in MWA Dashboard — the plugin inherits Moodle's mail settings automatically.

| SMTP | Host | Port | Security |
|------|------|------|----------|
| Gmail | smtp.gmail.com | 587 | TLS (STARTTLS) |
| Outlook / Microsoft 365 | smtp.office365.com | 587 | TLS (STARTTLS) |
| Yahoo | smtp.mail.yahoo.com | 465 | SSL |

Gmail tip: Enable two-step verification and generate an App Password (not your Google account password) to use as the SMTP password.

Dashboard Tabs

🎯 Action Center

The starting screen. Five smart KPIs each show the current value plus a -/-/- delta chip comparing the recent half of log activity with the earlier half:

• Students in log — unique students with recorded activity


• Total interactions — all Moodle log events


• Average / student — interactions per active student


• At risk — students with engagement score < 40% (- green = fewer at risk = improvement)


• Grade average — mean raw grade across all students

Three action cards:

• 🔴 Urgent — Students with score < 40%. Coloured avatars; click an avatar to open the student profile. "️ Message button opens a bulk message modal.


• 🟡 Attention — Activities with coverage below the adaptive threshold. Button navigates to the Activities tab.


• ' Opportunity — Peak access hour detected in logs with mini bar chart. Button navigates to the Heatmap.

Priority list — up to 5 highest-risk students. "View full list (N)" button navigates to Engagement Prediction. Clicking a student opens the AI Prediction panel with risk factors, weighted progress bars and feedback buttons.

Weekly Retention Curve — unique active students per week, colour-coded by trend. Click any data point for a drill-down: who did not return, who returned/joined, how many continued.

Engagement Index + Event Distribution — gauge chart of the class average score and a doughnut chart of resource types accessed (System and Login events excluded automatically).

🔔 Alerts

Six behavioural pattern detectors with -/- delta chips. Each alert lists affected students with quick-message buttons.

| Alert | Meaning |
|-------|---------|
| ' Viewed, not submitted | Accessed but never delivered |
| 📉 Sharp drop | Week-over-week access fell > 30% |
| ' Ghosts | Vanished early in the course — high dropout risk |
| ⚡ Symbolic access | Logged in on ≤ 2 days — presence without engagement |
| 🔄 Reactivated | Returned after a period of absence |
| 🌙 Night owls | ≥ 45% of accesses between 0h–5h |

' Class List

Full student roster in a table with: engagement score bar, last access date, days without access, total time, interactions and a quick-message button per student. Toggle between participation % and activities completed in the 4th column.

Engagement score formula:

# With grades released:

score = grade(50%) + activity_coverage(30%) + submissions(20%)



# Without grades (capped at 35%):

score = min(35, coverage - 30%)



# No grade data available:

score = coverage(60%) + submissions(40%)

' Student Profile

Detailed individual panel accessible by clicking any student name anywhere in the dashboard:

• Engagement score, last access, total interactions, active days, average session time, peak hour, favourite resource type


• GitHub-style activity calendar


• Daily access distribution chart (hour by hour)


• Grade per activity (colour-coded)


• Full contact history (messages sent via the dashboard)


• Quick message button

📋 Activities

Per-resource breakdown for every forum, task, quiz, SCORM, H5P and other activity. Clicking a resource opens a detail modal with:

• Participated / Pending / Completion rate KPIs


• Time per student ranking (session-based estimate from log timestamps)


• "️ Message to pending (N) — bulk message to students who accessed but did not submit


• "️ Message with no access (N) — bulk message to students who never accessed

" Grades

Grade overview with raw-value distribution histogram (0–20, 20–40, 40–60, 60–80, 80–100) and per-student detail. KPIs — Average, Approved (≥ 60 pts), In progress, No grade — each with -/- delta chip.

Export spreadsheet — generates a native .xlsx (no external library) with: Student, Total Grade, Status, and one column per graded activity. First row frozen, column widths adjusted.

- Content Analysis IA

Analyses resource reach and submission patterns across the entire course.

Where students get stuck — tasks and quizzes ranked by % of non-submission. Each item shows:

• Submitted vs not submitted counts


• Names of likely stuck students (cross-referenced with access logs)


• Severity badge (critical / attention / low)


• " AI button per item — diagnosis, content improvement and immediate action specific to that activity

Materials with low access — adaptive threshold: < 10 students = 70%, medium classes = 50%, large = 35%.

Generate AI suggestions — sends a prompt with all bottleneck data and student names. Returns 3 structured suggestions:

• ⚠️ Most critical bottleneck (cites real resource name)


• 📦 Most ignored material (improvement ideas)


• 🔀 Suggested trail reorganisation

🔥 Access Heatmap

Day - hour access grid. Hover tooltip shows access count, trend arrow (--) and deadline indicator (🔴). Two modes: Access (raw counts) and Dropout (students who stopped). Includes grade - time-slot correlation and automatic best intervention window suggestion.

🔮 Engagement Prediction

AI-powered dropout risk scoring:

• Engagement score = grades (50%) + activity coverage (30%) + task delivery (20%)


• Three KPI cards (Low / Average / High participation) with -/- delta chips


• Student list filterable by risk category and sortable by score, days without access or name


• Clicking a student ' Generate AI Recommendation: diagnosis, probable cause, immediate action and suggested message — generated by the AI server

🎯 Personalised Plan

Individual AI-generated study plans:

• Clicking a student ' Generate Plan — returns a 4-section plan:
  
  
  
  • 📚 Content Trail — 3 specific activities for this student's profile
  
  
  • ⏰ Suggested Rhythm — ideal frequency and session duration
  
  
  • 🎓 Learning Style — identified from access patterns
  
  
  • " Immediate Action — one concrete action for today
  
  
  
  


• Copy plan to clipboard button

' Chat with the Class

Conversational AI tab that uses live course data (student counts, scores, active alerts, activity names) as context. Ask anything: which students need attention, which activity is causing problems, draft an announcement, suggest a re-engagement strategy.

The conversation is session-only and does not persist between page loads.

"️ Messaging

The message modal is accessible from any tab. All sending uses Moodle's native infrastructure.

Two send types:

• ' Moodle Message — message_send() API. Arrives in the student's Moodle notifications. If the student has email notifications enabled, Moodle also delivers by email. Requires no additional configuration.


• 📧 Email — email_to_user(). Requires Moodle SMTP configured. Sent from Moodle's noreply address.

Generate with AI (") — the AI button in the modal footer uses the student's score, days without access, current grade, selected reason and chosen channel to auto-generate the subject and body. Tone adapts: formal for email, friendly for Moodle message.

Templates: Low engagement, Dropout risk, Pending task, Re-engagement, Praise.

Bulk send — progress bar and per-student status indicator.

' Interventions

Full contact history with effectiveness tracking:

• KPIs: Total sent, Return rate, Average return time, Still inactive


• Return time — automatically calculated from logs: how long after the message the student next accessed Moodle


• Export report — native .xlsx with 8 columns: Date, Student, Reason, Sender, Status, Return time, Channel, Subject

Privacy & Data

The plugin reads existing Moodle log and grade data. Messages use Moodle's native messaging and email infrastructure. Full GDPR/LGPD compliance is declared in classes/privacy/provider.php, including export and deletion of all personal data stored in block_mwa_dashboard_log and block_mwa_dashboard_messages.

Visibility & Access Control

• Visible only on course pages (course-view)


• Hidden on student profiles (user-profile: false) and My Courses page (my: false)


• Controlled by the block/mwa_dashboard:view capability — students do not have this capability by default


• Only users with the student role appear in logs, KPIs and lists — teachers, managers and moderators are excluded automatically

Third-party Libraries

| Library | Version | License |
|---------|---------|---------|
| Chart.js | 4.4.1 | MIT |

XLSX export and all file generation use native browser APIs (ZIP + OOXML) — no external library required.

Version

3.1.6 — July 2026

Maturity: Beta

3.1.6 highlights

• Completed i18n cleanup for Mustache templates reported by the Moodle plugin review.


• Localised the student score format in student_profile.mustache (sp_score_format).


• Localised Interventions tab delete tooltips and related status/error messages.


• Kept the package structure installable with mwa_dashboard/ as the ZIP root folder.

License

GNU General Public License v3 or later — see LICENSE for details.

Author

Bruno Porto

Professor and Researcher — IFES/CEFOR

Espírito Santo, Brazil — 2026

MWA Analytics Dashboard

Block plugin for Moodle 4.1+ — Learning Analytics dashboard for instructors, built as part of a Master's research project at IFES/CEFOR in the context of Distance Education (EaD) and teacher training.

Overview

MWA Analytics Dashboard transforms Moodle course logs and grade data into actionable pedagogical intelligence. Instead of navigating scattered reports, the instructor sees in one screen: which students are at risk, which activities are blocking the class, when students are most active, and what to do right now — all generated from real Moodle data.

With integrated AI, the plugin goes beyond numbers: it diagnoses each student's situation individually, generates personalised study plans, suggests improvements to course activities, and writes pedagogical messages ready to send. Instructors receive concrete guidance, not just raw data.

Requirements

| Item | Minimum |
|------|---------|
| Moodle | 4.1 (build 2022112800) |
| PHP | 7.4 |
| Moodle email | Configured (for email send type) |
| AI server (optional) | Any HTTP endpoint compatible with the MWA payload format |

Installation

1. Download the plugin ZIP from the Moodle Plugins Directory


2. Go to Site Administration ' Plugins ' Install plugins


3. Upload the ZIP and follow the prompts


4. Go to Site Administration ' Plugins ' Blocks ' MWA Dashboard ' Settings to configure the AI server (optional) and verify Moodle email settings


5. Add the MWA Analytics Dashboard block to any course page


6. Click Open Dashboard — the plugin fetches logs and grades automatically

Alternative: Extract the ZIP into <moodle_root>/blocks/mwa_dashboard/ and visit the admin notifications page.

Configuration

All settings are under Site Administration ' Plugins ' Blocks ' MWA Dashboard.

AI Server (optional)

AI features (individual recommendations, personalised plans, content analysis, message generation, class chat) require an external AI server. Without configuration, all other dashboard features work normally — only AI buttons are disabled.

| Setting | Description | Example |
|---------|-------------|---------|
| Endpoint URL | Base URL of the AI server. The plugin calls POST {endpoint}/ia for recommendations and POST {endpoint}/chat for the chat tab. Leave blank to disable all AI features. | https://your-server.com |
| API Key | Optional X-API-Key header sent with every request to protect your endpoint. | my-secret-key |
| Provider | Google Gemini or OpenAI (GPT-4o) — the server must support the chosen provider. | Google Gemini |
| Timeout | Maximum seconds to wait for the AI response (default: 90 s). | 90 |

AI payload format — the plugin sends:

[{

  "nomecompleto": "Student Name or Class",

  "instrucao": "<generated prompt with real course data>",

  "contexto": "Dashboard MWA"

}]

The server must respond with { "resposta": "..." }, { "response": "..." } or { "content": "..." }.

AI-powered features:

• 🔮 Individual engagement prediction with diagnosis and immediate action


• 🎯 Personalised 4-section study plan per student


• 
  
  
  
  • Content analysis — bottleneck diagnosis per activity + 3 course-level suggestions
  
  
  
  


• " Generate message with AI — subject and body tailored to each student's context


• ' Chat with the class — ask the AI anything using live course data as context


• 
  
  
  
  • Per-activity AI button — specific improvement suggestions for each stuck activity
  
  
  
  

Moodle Email (SMTP)

Email sending uses Moodle's own email_to_user() function. To set it up:

1. Go to Site Administration ' Server ' Email ' Outgoing mail configuration


2. Configure your SMTP host, port, username and password


3. Use the "Test outgoing mail configuration" button to confirm it works

No additional configuration is needed in MWA Dashboard — the plugin inherits Moodle's mail settings automatically.

| SMTP | Host | Port | Security |
|------|------|------|----------|
| Gmail | smtp.gmail.com | 587 | TLS (STARTTLS) |
| Outlook / Microsoft 365 | smtp.office365.com | 587 | TLS (STARTTLS) |
| Yahoo | smtp.mail.yahoo.com | 465 | SSL |

Gmail tip: Enable two-step verification and generate an App Password (not your Google account password) to use as the SMTP password.

Dashboard Tabs

🎯 Action Center

The starting screen. Five smart KPIs each show the current value plus a -/-/- delta chip comparing the recent half of log activity with the earlier half:

• Students in log — unique students with recorded activity


• Total interactions — all Moodle log events


• Average / student — interactions per active student


• At risk — students with engagement score < 40% (- green = fewer at risk = improvement)


• Grade average — mean raw grade across all students

Three action cards:

• 🔴 Urgent — Students with score < 40%. Coloured avatars; click an avatar to open the student profile. "️ Message button opens a bulk message modal.


• 🟡 Attention — Activities with coverage below the adaptive threshold. Button navigates to the Activities tab.


• ' Opportunity — Peak access hour detected in logs with mini bar chart. Button navigates to the Heatmap.

Priority list — up to 5 highest-risk students. "View full list (N)" button navigates to Engagement Prediction. Clicking a student opens the AI Prediction panel with risk factors, weighted progress bars and feedback buttons.

Weekly Retention Curve — unique active students per week, colour-coded by trend. Click any data point for a drill-down: who did not return, who returned/joined, how many continued.

Engagement Index + Event Distribution — gauge chart of the class average score and a doughnut chart of resource types accessed (System and Login events excluded automatically).

🔔 Alerts

Six behavioural pattern detectors with -/- delta chips. Each alert lists affected students with quick-message buttons.

| Alert | Meaning |
|-------|---------|
| ' Viewed, not submitted | Accessed but never delivered |
| 📉 Sharp drop | Week-over-week access fell > 30% |
| ' Ghosts | Vanished early in the course — high dropout risk |
| ⚡ Symbolic access | Logged in on ≤ 2 days — presence without engagement |
| 🔄 Reactivated | Returned after a period of absence |
| 🌙 Night owls | ≥ 45% of accesses between 0h–5h |

' Class List

Full student roster in a table with: engagement score bar, last access date, days without access, total time, interactions and a quick-message button per student. Toggle between participation % and activities completed in the 4th column.

Engagement score formula:

# With grades released:

score = grade(50%) + activity_coverage(30%) + submissions(20%)



# Without grades (capped at 35%):

score = min(35, coverage - 30%)



# No grade data available:

score = coverage(60%) + submissions(40%)

' Student Profile

Detailed individual panel accessible by clicking any student name anywhere in the dashboard:

• Engagement score, last access, total interactions, active days, average session time, peak hour, favourite resource type


• GitHub-style activity calendar


• Daily access distribution chart (hour by hour)


• Grade per activity (colour-coded)


• Full contact history (messages sent via the dashboard)


• Quick message button

📋 Activities

Per-resource breakdown for every forum, task, quiz, SCORM, H5P and other activity. Clicking a resource opens a detail modal with:

• Participated / Pending / Completion rate KPIs


• Time per student ranking (session-based estimate from log timestamps)


• "️ Message to pending (N) — bulk message to students who accessed but did not submit


• "️ Message with no access (N) — bulk message to students who never accessed

" Grades

Grade overview with raw-value distribution histogram (0–20, 20–40, 40–60, 60–80, 80–100) and per-student detail. KPIs — Average, Approved (≥ 60 pts), In progress, No grade — each with -/- delta chip.

Export spreadsheet — generates a native .xlsx (no external library) with: Student, Total Grade, Status, and one column per graded activity. First row frozen, column widths adjusted.

- Content Analysis IA

Analyses resource reach and submission patterns across the entire course.

Where students get stuck — tasks and quizzes ranked by % of non-submission. Each item shows:

• Submitted vs not submitted counts


• Names of likely stuck students (cross-referenced with access logs)


• Severity badge (critical / attention / low)


• " AI button per item — diagnosis, content improvement and immediate action specific to that activity

Materials with low access — adaptive threshold: < 10 students = 70%, medium classes = 50%, large = 35%.

Generate AI suggestions — sends a prompt with all bottleneck data and student names. Returns 3 structured suggestions:

• ⚠️ Most critical bottleneck (cites real resource name)


• 📦 Most ignored material (improvement ideas)


• 🔀 Suggested trail reorganisation

🔥 Access Heatmap

Day - hour access grid. Hover tooltip shows access count, trend arrow (--) and deadline indicator (🔴). Two modes: Access (raw counts) and Dropout (students who stopped). Includes grade - time-slot correlation and automatic best intervention window suggestion.

🔮 Engagement Prediction

AI-powered dropout risk scoring:

• Engagement score = grades (50%) + activity coverage (30%) + task delivery (20%)


• Three KPI cards (Low / Average / High participation) with -/- delta chips


• Student list filterable by risk category and sortable by score, days without access or name


• Clicking a student ' Generate AI Recommendation: diagnosis, probable cause, immediate action and suggested message — generated by the AI server

🎯 Personalised Plan

Individual AI-generated study plans:

• Clicking a student ' Generate Plan — returns a 4-section plan:
  
  
  
  • 📚 Content Trail — 3 specific activities for this student's profile
  
  
  • ⏰ Suggested Rhythm — ideal frequency and session duration
  
  
  • 🎓 Learning Style — identified from access patterns
  
  
  • " Immediate Action — one concrete action for today
  
  
  
  


• Copy plan to clipboard button

' Chat with the Class

Conversational AI tab that uses live course data (student counts, scores, active alerts, activity names) as context. Ask anything: which students need attention, which activity is causing problems, draft an announcement, suggest a re-engagement strategy.

The conversation is session-only and does not persist between page loads.

"️ Messaging

The message modal is accessible from any tab. All sending uses Moodle's native infrastructure.

Two send types:

• ' Moodle Message — message_send() API. Arrives in the student's Moodle notifications. If the student has email notifications enabled, Moodle also delivers by email. Requires no additional configuration.


• 📧 Email — email_to_user(). Requires Moodle SMTP configured. Sent from Moodle's noreply address.

Generate with AI (") — the AI button in the modal footer uses the student's score, days without access, current grade, selected reason and chosen channel to auto-generate the subject and body. Tone adapts: formal for email, friendly for Moodle message.

Templates: Low engagement, Dropout risk, Pending task, Re-engagement, Praise.

Bulk send — progress bar and per-student status indicator.

' Interventions

Full contact history with effectiveness tracking:

• KPIs: Total sent, Return rate, Average return time, Still inactive


• Return time — automatically calculated from logs: how long after the message the student next accessed Moodle


• Export report — native .xlsx with 8 columns: Date, Student, Reason, Sender, Status, Return time, Channel, Subject

Privacy & Data

The plugin reads existing Moodle log and grade data. Messages use Moodle's native messaging and email infrastructure. Full GDPR/LGPD compliance is declared in classes/privacy/provider.php, including export and deletion of all personal data stored in block_mwa_dashboard_log and block_mwa_dashboard_messages.

Visibility & Access Control

• Visible only on course pages (course-view)


• Hidden on student profiles (user-profile: false) and My Courses page (my: false)


• Controlled by the block/mwa_dashboard:view capability — students do not have this capability by default


• Only users with the student role appear in logs, KPIs and lists — teachers, managers and moderators are excluded automatically

Third-party Libraries

| Library | Version | License |
|---------|---------|---------|
| Chart.js | 4.4.7 | MIT |

XLSX export and all file generation use native browser APIs (ZIP + OOXML) — no external library required.

Version

3.1.4 — July 2026

Maturity: Beta

License

GNU General Public License v3 or later — see LICENSE for details.

Author

Bruno Porto

Professor and Researcher — IFES/CEFOR

Espírito Santo, Brazil — 2026

MWA Analytics Dashboard

A Moodle block plugin that provides real-time learning analytics, engagement prediction, and AI-powered pedagogical intervention tools for instructors.

Screenshots

Action Center — Urgent alerts and daily priorities

Class List — Participation, time on course and last access

Activities — Per-resource breakdown with submission tracking

Grades — Progress tracking with per-activity detail

Contact Report — Intervention history and CRM

Features

• Action Center — Urgent alerts: students at risk of dropout, missing submissions, sudden engagement drops


• Engagement Index — Multi-dimensional score combining grades (50%), activity coverage (30%), and task delivery (20%)


• Evasion Prediction — AI-powered analysis identifying students at risk based on access patterns


• Student Profiles — Individual CRM with contact history, private notes, and engagement timeline


• Activity Analysis — Per-resource breakdown showing who accessed, who submitted, who didn't


• Time-on-Resource — Session-based time estimation per student per activity


• Heatmap — Access patterns by day/hour with student names on hover


• AI Recommendations — GPT-powered suggestions for course design and individual student intervention


• Email Integration — Send personalized emails via Gmail API with auto-logging to contact history


• Contact Report — Full CRM with filters, timeline and XLSX export


• Export — XLSX export for grades, contact reports and student lists

Requirements

• Moodle 4.1 or later


• PHP 7.4 or later


• Standard log store enabled (logstore_standard)

Installation

1. Download the plugin ZIP file


2. Go to Site Administration ' Plugins ' Install plugins


3. Upload the ZIP file and follow the prompts


4. Add the MWA Analytics Dashboard block to any course page

Alternatively, extract the ZIP into /blocks/mwa_dashboard/ and visit the admin notifications page.

Usage

1. Navigate to a course where you have teacher/manager role


2. Click Open Dashboard in the MWA block


3. The plugin automatically fetches logs and grades from Moodle


4. Optionally connect Gmail for AI-assisted email sending

Privacy

This plugin reads existing Moodle log and grade data for analysis purposes. It does not store any personal data in its own database tables. See classes/privacy/provider.php for the GDPR/LGPD compliance implementation.

Third-party libraries

• Chart.js v4.4.7 — MIT License


• SheetJS v0.20.3 — Apache-2.0 License

License

GNU General Public License v3 or later — see LICENSE for details.

Author

Bruno Porto — 2026
Educimat/IFES - 2026