Overview
NotebookLM for Teachers
This guide outlines specific, actionable strategies for Senior Secondary (S4βS6) educators to leverage NotebookLM Enterprise. The strategies focus entirely on pedagogical applications adaptable to any DSE elective subject, followed by a dedicated section on mandatory compliance and ethical restrictions in accordance with the Hong Kong Generative Artificial Intelligence Technical and Application Guideline issued by the HKSAR Digital Policy Office.
All strategies are subject-neutral and can be adapted to any DSE elective.
Part 1
Lesson Preparation & Material Development
The following five strategies help teachers build richer, more responsive learning materials using NotebookLM's AI features.
Establish Vetted "Sources of Truth" for DSE Exams
ShareTeachers can upload approved notes, worksheets, past paper marking schemes, and textbook excerpts into a single Notebook. By utilising the Share feature, teachers of subjects with strict syllabus definitions and data-response requirements can distribute this highly focused, searchable database directly to their students.
Construct Dynamic Flipped Classroom Materials
Video OverviewTeachers can transition from static pre-reading to dynamic pre-viewing. A teacher covering complex phenomena or dense theoretical chapters can upload text-heavy documents and use the Video Overview tool to automatically generate a concise visual summary for students to watch before class.
Map Curriculum Trajectories for DSE Modules
Mind MapDuring term planning, teachers can input unit objectives to generate a comprehensive Mind Map. A teacher handling subjects with interconnected core and elective modules can use this to map out and visualise the linkages between concepts to ensure logical curriculum flow.
Distill Complex Texts into Reading Guides
ReportsWhen introducing advanced reading materials, teachers can use the Reports feature to generate structured summaries, key vocabulary lists, and critical thinking questions. A teacher of humanities subjects involving extensive reading or primary source analysis can use this to scaffold the reading process.
Drive Pedagogical Adjustments via Formative Metrics
ChatTeachers can upload mock exam performance metrics to quickly identify broader learning gaps. A teacher evaluating data-based questions (DBQs) or specific skill-based assessments can analyse performance to isolate specific topics that require targeted reteaching.
Part 2
Fostering Self-Regulated Learning (Teacher-Directed)
The following five strategies show teachers how to direct students towards independent, active learning using NotebookLM.
Mandate DBQ & Extended Response Blueprinting
Mind MapTeachers can require S5β6 students to upload their researched notes and trigger a Mind Map before drafting essays. A teacher guiding subjects requiring structured essays or extended responses can enforce this as a mandatory structural outline for assessing complex multi-perspective issues.
Facilitate On-the-Go Auditory Revision
Audio OverviewTeachers can direct students to convert their revision notes into an Audio Overview. Teachers can show students studying content with complex processes or sequential systems how to transform notes into a podcast-style format, enabling auditory learning during daily commutes.
Assign Active Recall DSE Quizzing
ReportsTeachers can instruct students to move away from passive reading by using the Reports feature to generate custom multiple-choice quizzes and flashcards. This is highly effective for teachers guiding students in highly factual subjects to master specific definitions, dates, or formulas.
Provide Multimodal Differentiated Study Playlists
Multiple outputsTeachers can train students to cater to their specific learning styles. A teacher of subjects requiring multi-modal conceptual understanding can demonstrate how to take a single source document and convert it simultaneously into a Report, an Audio Overview, and a Mind Map.
Coordinate Collaborative Peer Review Hubs for SBA
ShareTeachers can establish and oversee shared workspaces for School-based Assessment (SBA) projects. For subjects with mandatory SBAs or collaborative investigative projects, teachers guide groups to centralise their research, allowing the AI to synthesise the notes into cohesive group reports.
Part 3
Compliance & Ethical Restrictions
When utilising generative AI tools, teachers must ensure strict compliance with the following guidelines based on the Hong Kong Generative Artificial Intelligence Technical and Application Guideline issued by the HKSAR Digital Policy Office:
Data Privacy
Teachers must comply with the Personal Data (Privacy) Ordinance (PDPO) (Cap. 486) when handling personal data. Personal data must be anonymised or cleansed before being inputted into generative AI services.
Human Oversight & Grading
If AI is used for grading assignments and exams, final results should always be reviewed by human educators.
Academic Integrity
Teachers must ensure that students obtain teacher approval before using AI in their coursework. AI-generated content should be clearly identifiable to prevent misuse that violates academic integrity.
Content Truthfulness
When teachers use generative AI in teaching, they must ensure that the generated content is truthful, accurate, and consistent in both textual and visual representation.
Intellectual Property
Teachers must consciously respect intellectual property rights and avoid using generated content that constitutes the whole or substantial copying of copyright works so as to prevent copyright disputes.
Bias & Fairness
Strict controls must be implemented to eliminate model biases. Algorithms and review mechanisms should be employed to prevent the generation of biased or discriminatory content.
Internal Policies
Teachers must adhere to the school's internal policies regarding permitted tools, permissible uses (e.g., drafting, summarising), and permissible types and amounts of input information.
Section 5
Need Help?
If you have any questions about using NotebookLM, please contact Mr Arthur Chan or Mr Ken Kum of the Tech in Ed Task Force.