Lambu Education Impact Fellowship Program

Example innovation tracks:

• Adaptive Learning Platforms: Real-time personalization of pacing, content sequencing, and feedback using student-level performance data.

• Intelligent Tutoring Systems (ITS): Step-by-step support—especially in math and STEM—to address misconceptions and promote mastery.

• Accessibility & Inclusion: Speech-to-text, translation, content adaptation, and cognitive supports for disabilities and linguistic diversity.

• “AI-Unplugged” Models: Offline or teacher-mediated AI uses—e.g., automated grading of handwritten work—to enable equity in low-tech settings.

Outputs may include: prototype pilots, learning-gain studies, accessibility toolkits, or low-cost classroom integration strategies.

Innovation tracks:

• AI-Generated Teaching Materials: Automated lesson planning, question banks, culturally contextualized stories, or curriculum-aligned texts in local languages.

• AI Literacy Curriculum: Modules on data, algorithms, responsible AI, and ethics for K-12, TVET, or teacher-training institutions.

• Curriculum Intelligence Hubs: Data-aggregation tools identifying learning gaps and informing curriculum reform at national or district levels.

Outputs may include: prototype tools, curricular frameworks, implementation pilots, or policy guidance.

Innovation tracks:

• Automated Scoring: Machine-scored essays, short answers, or MCQs to improve speed, consistency, and formative feedback.

• Computerized Adaptive Testing (CAT): Difficulty calibrated to student performance for more precise measurement.

• Assessment of 21st-Century Skills: Gamified or simulation-based metrics for collaboration, creativity, and critical thinking.

• Secure Remote Proctoring: Responsible and privacy-aware monitoring to uphold assessment integrity.

Outputs may include: psychometric validation, equity-bias audits, implementation protocols, or ethics frameworks.

Innovation tracks:

• AI Coaching & Help-Desks: On-demand pedagogical support via chat interfaces or messaging platforms.

• Virtual Simulation Labs: Classroom management rehearsal environments with AI-driven avatars and realistic student behavior.

• Expert-Practice Deconstruction: Video analytics that surface tacit techniques of high-performing teachers for novices.

• AI-Supported Professional Learning Communities: Summaries, agenda-setting, or idea-clustering for distributed teacher groups.

Outputs may include: TPD pilots, usage-data analysis, and teacher-experience evaluations.

Innovation tracks:

• Automation of Routine Workflows: Admissions, attendance, fee management, payroll, and 24/7 parent communication.

• Data-Dashboarding: Real-time visualization of academic progress, well-being indicators, and risk signals.

• Resource Optimization: Algorithms supporting school placement, teacher allocation, or materials distribution based on localized needs.

Outputs may include: workflow efficiency studies, open-source dashboards, or public-sector implementation toolkits.

Innovation tracks:

• Predictive Analytics for Skills & Labor Forecasting: Demand-sensing for curriculum, TVET pathways, procurement, and workforce planning.

• Early Warning Systems (EWS): Student-risk models to trigger social-emotional, academic, or financial interventions before dropout.

• NLP-Based Service Management: Automatic routing or classification of citizen requests or school-level queries.

• AI-Supported Consultation & M&E: Platforms gathering public sentiment and enabling evidence-based policy adjustments.

Outputs may include: algorithmic governance models, safeguarding standards, or evaluation dashboards.