EdTech & AI Learning Glossary
Plain-English definitions of the AI and learning-technology terms that matter when you are choosing a platform for your institution.
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AI-Powered LMS
An AI-powered LMS is a learning management system that uses artificial intelligence to actively assist learning — generating practice questions, tutoring students from course content, adapting to weak areas, and measuring retention — rather than only storing and delivering content like a traditional LMS.
Read definitionRAG (Retrieval-Augmented Generation)
RAG (Retrieval-Augmented Generation) is an AI technique where a model first retrieves relevant passages from a specific document set, then uses them to generate an answer — so responses are grounded in your source material and can cite it, instead of relying on the model's general training.
Read definitionAdaptive Learning
Adaptive learning is an approach where the learning path adjusts in real time to each student's performance — surfacing easier or harder material, and targeting practice at the specific topics and question types where the student is weakest.
Read definitionOnline Proctoring
Online proctoring is the set of techniques used to maintain exam integrity during remote or computer-based tests — such as fullscreen lock, tab-switch detection, time limits, and live monitoring — so online exams stay fair and credible.
Read definitionSpaced Repetition
Spaced repetition is a study technique that schedules review of material at increasing intervals over time — reviewing just before you would forget — to move knowledge into long-term memory far more efficiently than cramming.
Read definitionWhite-Label LMS
A white-label LMS is a learning platform you can rebrand entirely as your own — with your institution's name, logo, colours, and domain — so students experience it as your product rather than a third-party tool.
Read definitionQuestion Bank
A question bank is an organised, reusable repository of exam and practice questions — tagged by topic, difficulty, and type — from which teachers assemble tests, generate practice sets, and analyse question quality over time.
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