# Inferring Concept Prerequisite Relations from Online Educational Resources

arXiv: https://arxiv.org/abs/1811.12640 · HTML: https://mlsanity.com/paper/1811.12640/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Nov 2018.

## Built on by (most cited first, 7 of 7)

- [Towards a General Pre-training Framework for Adaptive Learning in MOOCs](https://mlsanity.com/paper/2208.04708/) (2022)
- [From Robots to Books: An Introduction to Smart Applications of AI in Education (AIEd)](https://mlsanity.com/paper/2301.10026/) (2023)
- [Lost in Translation: Reimagining the Machine Learning Life Cycle in Education](https://mlsanity.com/paper/2209.03929/) (2022)
- [MOOCRep: A Unified Pre-trained Embedding of MOOC Entities](https://mlsanity.com/paper/2107.05154/) (2021)
- [Concept Prerequisite Relation Prediction by Using Permutation-Equivariant Directed Graph Neural Networks](https://mlsanity.com/paper/2312.09802/) (2023)
- [ProPRL: Property-Aware Prerequisite Relation Learning in Educational Knowledge Graphs](https://mlsanity.com/paper/2608.03006/) (2026)
- [Atom Learning Model (ALM): how a real classroom got tokenised](https://mlsanity.com/paper/2608.21106/) (2026)

## Abstract (arXiv)

The Internet has rich and rapidly increasing sources of high quality educational content. Inferring prerequisite relations between educational concepts is required for modern large-scale online educational technology applications such as personalized recommendations and automatic curriculum creation. We present PREREQ, a new supervised learning method for inferring concept prerequisite relations. PREREQ is designed using latent representations of concepts obtained from the Pairwise Latent Dirichlet Allocation model, and a neural network based on the Siamese network architecture. PREREQ can learn unknown concept prerequisites from course prerequisites and labeled concept prerequisite data. It outperforms state-of-the-art approaches on benchmark datasets and can effectively learn from very less training data. PREREQ can also use unlabeled video playlists, a steadily growing source of training data, to learn concept prerequisites, thus obviating the need for manual annotation of course prerequisites.