Term explanation
Asynchronous learning refers to educational experiences that do not require all participants to be present at the same time. Learners access materials, complete exercises, and submit work according to their own schedule within a defined timeframe. Common formats include recorded video lectures, discussion boards, and self-paced e-courses. Asynchronous learning offers flexibility for geographically dispersed or busy learners and forms the backbone of most online learning programs.
Want to add live interaction to your asynchronous learning program? SlideLizard LIVE lets you run interactive PowerPoint sessions with polls, quizzes, and Q&A that bring distributed learners together in real time.
Learn more →Informal communication is spontaneous, unstructured interaction between people that falls outside official organizational channels. It includes hallway conversations, team chat messages, lunch discussions, and impromptu calls. While informal communication is not planned or documented, it plays a vital role in organizational culture — building relationships, sharing tacit knowledge, and enabling faster problem-solving. In remote and hybrid workplaces, replicating the natural flow of informal communication has become an important design challenge.
Learn moreIn live online training, it is sometimes useful to divide the students into small groups for certain exercises, as it would be impossible to have conversations at the same time. Break-out-rooms are used so that people can talk to each other without disturbing the others. When the exercise is over, they are sent back to the main room.
Learn moreThe Slide Sorter view in PowerPoint shows thumbnails of all your slides in horizontal rows.The view is useful for applying global changes to several slides at once. Also it's useful for deleting and rearranging slides.
Learn moreGenerative AI refers to artificial intelligence systems that create new content — such as text, images, code, or structured data — in response to a prompt or task, rather than simply analyzing or classifying existing information. Powered by large language models and other foundation models, generative AI can write documents, summarize reports, produce slide content, and translate data into natural language. In enterprise settings, it is the core technology behind modern AI assistants, document automation tools, and presentation generators. A presentation-specific evolution of generative AI is the Large Presentation Model (LPM), which combines generative capabilities with enterprise context, brand guidelines, and the full presentation cycle.
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