Key facts
Contents & fields
The dataset includes users, items, explicit ratings, and implicit ratings in CSV files for both French and English versions. User IDs and item IDs are consistent across files. Fields include:
- user_id——Unique user identifier
- job——User's job (if available)
- item_id——Unique item identifier
- language——Item language (French or English)
- name——Item name
- nb_views——Number of views of the item
- description——Item description
- created_at——Timestamp of rating or item creation
- Difficulty——Item difficulty
- Job——Job related to the item
- Software——Software related to the item
- Theme——Item theme
- duration——Item duration
- type——Item type
- watch_percentage——Watch percentage (explicit ratings)
- rating——Explicit rating value
Research uses
Suitable for recommender system research in education, especially algorithm evaluation based on explicit and implicit feedback, and comparison of recommendation effectiveness in multilingual environments.
This card was drafted from the source page; institution, coverage, time span, scale, fields and license are subject to the official page (pending human review).
Keywords
Why this is hard to get on your own
Educational recommender system datasets are scarce, especially those with both explicit and implicit feedback in a multilingual context.
