Teacher Knowledge Archive & AI Workshop
Dashboard
Build one topic. Share one reusable teacher pack.
Create an English curriculum pack, fill an anonymous Transit PBD, audit the data, generate AI prompts and export a complete NotebookLM Source Pack.
Golden Samples
Ready-to-demonstrate packs
Workshop Flow
Participant outcome
- 1Upload curriculum sourcesAdd the topic DSKP and authorised textbook/reference first.
- 2Build the topic and PBD evidenceMap SK/SP, assessment skills and anonymous Transit PBD.
- 3Use the Unit 5 NotebookLM workflowAudio Overview, study notes, Studio outputs and PBD analysis.
- 4Audit, export and shareVerify citations and export the complete Topic/Source Pack ZIP.
Curriculum Library
DSKP and SK/SP Explorer
Browse available curriculum mappings. Content marked “Teacher Build” remains editable and must be verified against the official DSKP.
Workshop Topic Builder
Create a portable ARKIBGURU Topic Pack
Choose any year and topic. Upload the relevant DSKP and textbook inside the same workflow, then keep official wording and teacher summaries separate.
Anonymous Assessment Workspace
Transit PBD
Selecting a curriculum topic automatically creates anonymous PBD 1 and PBD 2 samples from its Learning Standards. Performance Standards remain visible as the teacher reference, while Teacher TP stays a manual professional decision.
For every loaded Mathematics DLP or Science DLP topic, the app prepares 20 anonymous pupils across PBD 1 and PBD 2 using the active CS, LS and Performance Standards.
Topic-Specific Transit Form
Select a curriculum topic
| # | Pupil ID | No curriculum selected |
|---|---|---|
| Choose a verified topic and generate the table. | ||
Structured Export Records
NotebookLM Data View
| # | Pupil ID | LS | Learning Standard | Assessment TP | Evidence | Teacher TP | Decision | Teacher Note | Status |
|---|---|---|---|---|---|---|---|---|---|
| Load a Golden Sample or create a topic first. | |||||||||
Human-Controlled PBD Evidence
Audit, analyse and plan intervention
Validate the dataset first, compare PBD cycles, inspect every Learning Standard, then approve or modify pupil-level intervention suggestions.
Audit Report
Issues requiring attention
Audit Controls
Rules applied before analysis
TP Distribution
Pupils by teacher TP
PBD Progress
PBD 1 compared with PBD 2
Priority Findings
Strongest and weakest evidence
Support Rule
How pupils are classified
A pupil is flagged when the latest teacher TP is TP1–TP2, the latest average score is below 6/10, or the pupil declined and has at least two priority Learning Standards. This rule is shown for transparency and can be reviewed by the teacher.
PBD 1 vs PBD 2
Learning Standard comparison graph
Detailed Standards Table
Evidence, change and pupils requiring support
| LS | Learning Standard | PBD 1 | PBD 2 | Change | Status | Support Pupils |
|---|---|---|---|---|---|---|
| Run the audit to generate Learning Standard analysis. | ||||||
Pupil × Learning Standard Heatmap
Class evidence at a glance
Suggestions are generated from the audited evidence pattern. Approve, modify or reject each suggestion. Teacher decisions and notes are stored separately from calculated analysis.
Pupil-Level Intervention Planner
Action, evidence and teacher decision
| Pupil | Current TP | Priority LS | Evidence Gap | Suggested Intervention | Follow-up Evidence | Teacher Decision | Teacher Note | Completed |
|---|---|---|---|---|---|---|---|---|
| Run the audit to generate pupil-level suggestions. | ||||||||
NotebookLM • Gemini • ChatGPT
Prompt Centre
Generate structured English prompts using verified topic metadata and audited statistics. No platform receives data automatically.
Generated Prompt
NotebookLM — Audit Data
The app does not send this prompt anywhere. Review it, then copy it manually to your chosen AI platform.
Based on Module Unit 5 — NotebookLM in PBD
Teacher Knowledge Archive & NotebookLM Workflow
Follow Sections 5.2–5.6 in sequence: upload DSKP/textbook, create an Audio Overview, synthesize study notes, build the teacher knowledge archive, then analyse anonymous PBD evidence.
Unit 5 Workshop Journey
Follow the complete NotebookLM learning flow
Click a journey step only after completing that action in NotebookLM. Progress is saved in this browser.
Live Source Sync
Uploaded sources appear automatically
Upload DSKP / Textbook to NotebookLM
Prepare and verify the core sources
Use a clear PDF, professional file names and a small focused source set. Extract the exported ZIP before adding the files individually in NotebookLM.
Audio Overview
Generate a topic podcast
Keep the notebook focused on the selected topic and use one or two closely related sources for a clear Audio Overview.
Automatic Study Notes
Synthesise DSKP, textbook and topic evidence
NotebookLM should compare the selected sources, provide inline citations and clearly identify any curriculum gaps or differences.
Integrated Teacher Knowledge Archive
Organise sources and choose a Studio output
PBD & Internal Assessment Analysis
Audit anonymous data before NotebookLM analysis
Use anonymous IDs only. NotebookLM insights are a starting point and do not replace professional teacher judgement.
Unit 5 Export Contents
Files included in the Source Pack
Pack Preview
No active topic
Upload sources, create Audio Overview and study notes, use Studio outputs, audit anonymous PBD data, then save only verified work.
Facilitator Collection Workspace
Merge all group Topic Packs offline
Import many ARKIBGURU Topic Pack ZIP files, validate them, keep group versions separately, and export one portable Master Library ZIP.
Every imported pack remains a separate version in this browser. The app does not silently overwrite another group’s work. Select a pack and activate it only when you want to edit or generate a focused NotebookLM Source Pack.
Merge Audit
Duplicates, conflicts and validation notes
Browser-Generated Files
Export Centre
No Google Sheet write is required. Files are created on the participant’s device.
Compatibility Check