Reimagine your L&D approach by embedding AI within microlearning to reinforce memory retention and drive performance. In this course, learners will explore how AI smartly tailors bite-sized content, automates spaced repetition schedules, and delivers context-aware reinforcement—all grounded in neuroscience and practical application. You’ll discover immersive techniques, ethical considerations, and analytics to make learning sticky, scalable, and truly learner-centric.
- Neuroscience of microlearning: cognitive load, spacing & active recall
- AI-powered micro-content curation & adaptive learning paths
- Personalized spaced-repetition and memory modeling
- Interactive micro-quizzes and reinforcement modalities
- Gamification and engagement techniques for retention
- Contextual performance support via on-demand microlearning
- Accessible & inclusive microlearning design
- XR-enhanced microlearn modules for immersive reinforcement
- Analytics-driven impact measurement & refinement
- Future trends: nano-learning, AI tutors, metaverse micro-content
- Leverage cognitive principles to design effective microlearning
- Use AI tools to curate personalized, adaptive micro-content
- Implement spaced-repetition tailored to each learner’s needs
- Create interactive micro-quizzes that reinforce learning
- Integrate gamified elements to boost retention and engagement
- Provide contextual micro-learning at the point of need
- Ensure accessibility and inclusion in micro-learning design
- Apply analytics to iterate and optimize retention strategies
Learning designers, L&D professionals, trainers, EdTech developers, instructional technologists, and performance coaches seeking to embed AI-enabled microlearning that maximizes knowledge retention and workplace performance.
Participants will engage in hands-on workshops, AI tool demos, microcontent prototyping, spaced-repetition labs, and gamification role-plays. This iterative, analytics-driven format ensures practical application and continuous refinement based on real-time data and learner feedback.
- Cognitive science: chunking, forgetting curve & active recall
- Neuroscience behind spaced repetition & retention
- Role of microlearning in modern workflows
- Lab: Design first micro-learning nugget
- Peer review: evaluate clarity & cognitive load
- AI micro-content curators (e.g., 5mins.ai, LMS portals)
- Adaptive learning paths and personalized modules
- Spaced-repetition models: algorithmic scheduling
- Workshop: Build an AI-driven micro-learning sequence
- Review: learner personas and adaption flow
- Designing interactive micro-quizzes and flashcards
- Embedding game elements for motivation
- Role-play: use of leaderboards, levels, and badges
- Contextual delivery: chatbots, reminders, in-flow prompts
- Lab: Prototype performance-support microcontent
- XR/AR micro-learning case use-cases
- Designing accessible micro-modules (captions, audio, language)
- Inclusive content audit and bias mitigation
- Lab: Create immersive, accessible micro-learning snippet
- Group critique: refine for inclusion
- Analytics dashboards: retention rates, completion, confidence
- Continuous improvement: A/B testing and iteration loops
- Nano-learning, AI tutors, metaverse micro-content
- Capstone: Design a full microlearning plan with AI and analytics
- Showcase: peer feedback and action strategies
Group & Corporate Discounts: Available for companies enrolling multiple participants to help maximize ROI. Individual Discounts: Offered to self-sponsored participants who pay in full and upfront. Registration Process: Corporate nominations must go through the client’s HR or Training department. Self-nominations must be prepaid via the “payment by self” option. Confirmation: All registrations are subject to DIXONTECH’s approval and seat availability. Refunds: Provided in case of course cancellation or no seat availability. Tax Responsibility: Clients are responsible for any local taxes in their country.