Term explanation
In a learning context, virtual reality (VR) creates immersive, simulated environments in which learners can practice skills, explore scenarios, or experience situations that would be difficult, expensive, or dangerous to replicate in real life. VR training is used in industries such as healthcare, aviation, manufacturing, and emergency services. By placing learners inside a realistic environment, VR significantly increases engagement, retention, and the transfer of skills to real-world performance.
Before or after a VR learning experience, SlideLizard LIVE helps you gauge prior knowledge and gather feedback with live polls and quizzes directly in PowerPoint — making debriefs and knowledge checks seamlessly interactive.
Learn more →Written communication is the transmission of information through written text — including emails, reports, proposals, presentations, messages, and documentation. Unlike spoken communication, written messages persist over time and can be reviewed, shared, and referenced repeatedly. Effective written communication requires clarity, appropriate structure, careful word choice, and an understanding of the reader's needs and context. In business settings, it is one of the primary channels for formal decisions, instructions, and record-keeping.
Learn moreComputer-based training (CBT) refers to self-paced educational programs delivered through software on a computer, without requiring an internet connection or live instructor. CBT packages typically include multimedia content, simulations, and assessments. This format was widely adopted in the 1990s and 2000s as an alternative to classroom training, offering consistency and repeatability. Today, CBT is largely succeeded by web-based training (WBT), though it remains in use where internet access is limited or security is a concern.
Learn moreThe 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.
Learn moreAn orchestrator agent is a specialized AI agent that coordinates and directs the work of other agents — rather than executing tasks directly itself. In a multi-agent system, the orchestrator receives a high-level goal, uses task decomposition to break it into subtasks, assigns them to specialist agents, monitors progress, and assembles the final output. This pattern enables reliable automation of complex, multi-step enterprise workflows.
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