Agent Loop
The agent loop is the core operating cycle of an autonomous AI agent. It runs continuously through four phases: Perception (gathering information), Reasoning (planning the next step), Action (executing — such as calling a tool or generating content), and Observation (evaluating the result). The loop repeats until the task is complete or the agent requires human input. This is the mechanism behind Agentic AI systems — it is what allows agents to handle complex, multi-step tasks that a single prompt-and-response model could not.
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Game-based Learning
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.
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Audience Dynamics
Audience dynamics refers to the behavioral and social patterns that emerge within a group of listeners during a presentation or event. This includes how energy, attention, engagement, and mood shift over time — and how individual participants influence the group. Understanding audience dynamics helps presenters adapt their pacing, tone, and content in real time. Factors such as group size, seating arrangements, time of day, and topic familiarity all affect the dynamic of a given audience.
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Outline view
The outline view in PowerPoint shows a list with the whole text of all slides on the left of the screen. There are no images and graphics displayed in this view. It's useful for editing the presentation and can also be saved as a Word document.
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