Purpose
This LurnyMagic page allows content creators to convert an existing audio or video recording into a structured, bite-sized learning experience.
Suitable source files may include:
Training recordings
Webinars and presentations
Expert interviews
Lectures and talks
Product demonstrations
Recorded meetings or discussions
Podcasts and other educational audio
Lurny processes the spoken content and uses it to generate a microlesson.
How to create the microlesson
Open Create a Microlesson from the left-side menu.
Select From Audio & Video.
Click Upload file.
Browse your device and select the required audio or video file.
Alternatively, drag the file from your device and drop it into the designated upload area.
Wait while Lurny uploads and processes the file.
Follow the subsequent prompts to review and create the microlesson.
Lurny analyses the recording and converts its relevant content into a structured learning experience.
File upload options
Upload file
Click this button to browse your device and select the audio or video recording you want to use.
Drag and drop
Drag the required file from your computer and release it inside the designated upload area.
Recent microlessons
The lower section displays microlessons previously generated from uploaded audio or video files. Each card may show:
The generated cover image
The microlesson title
The XP learners can earn
Learner or engagement information
Selecting a card allows the creator to open and manage the generated microlesson.
Recommended practices
Use recordings with clear and audible speech.
Minimise background noise, overlapping voices and interruptions.
Choose recordings that have a clear learning purpose.
Trim lengthy introductions, silences and unrelated discussions before uploading.
Ensure speakers use understandable language and explain specialised terminology.
Obtain the necessary permission before uploading confidential or copyrighted recordings.
Review the generated content for accuracy and organisational relevance before publishing.
Important: The quality of the generated microlesson depends on the clarity of the recording and the relevance of its spoken content. Poor audio quality, heavy background noise or multiple people speaking simultaneously may reduce accuracy.