Term explanation
Game-based learning (GBL) uses game mechanics — such as points, levels, challenges, and rewards — to deliver educational content in an engaging format. Games motivate learners through competition, narrative, and immediate feedback, making them particularly effective for skill practice and knowledge reinforcement. Game-based learning ranges from simple quiz games to complex simulations and serious games developed for specific professional training scenarios.
SlideLizard LIVE brings game-based learning to any PowerPoint presentation: create competitive quizzes with scoreboards, give participants instant feedback after every question, and make knowledge transfer genuinely fun.
Learn more →The Notes Page view in PowerPoint shows a smaller version of the slide with a small area for notes underneath. In the presentation every slide has it's own space for notes. During the presentation the notes do not appear on screen. They are just visible in the presentation mode.
Learn moreMicrolearning delivers educational content in short, focused segments — typically between 3 and 10 minutes. Rather than completing a lengthy course, learners engage with bite-sized units that cover a single concept or skill. Microlearning is effective for knowledge reinforcement, mobile training, and just-in-time learning. It fits naturally into busy workdays and is widely used in corporate onboarding, compliance training, and professional development programs.
Learn moreA multi-agent system is a setup in which several autonomous AI agents work together, each handling a specific part of a larger task. The agents can communicate, divide work, and combine their outputs to achieve goals that would be difficult for a single model. Typically, an orchestrator agent coordinates the workflow while specialist agents execute defined subtasks. In enterprise contexts, multi-agent systems allow complex workflows — such as researching a topic, drafting content, checking compliance, and distributing a presentation — to be fully automated.
Learn moreAgentic AI refers to artificial intelligence systems that act autonomously to achieve multi-step goals — without requiring a human to trigger each action individually. Unlike traditional AI that responds to single prompts, agentic AI plans, decides, and executes sequences of tasks on its own, often integrating with external tools and data sources. In enterprise settings, agentic AI is increasingly used to automate complex workflows such as reporting, content creation, and communication. In the domain of presentations, this approach is realised through the Large Presentation Model (LPM) — an agentic AI system that orchestrates the entire presentation cycle in an enterprise context.
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