Riiid answer correctness prediction
https://www.kaggle.com/c/riiid-test-answer-prediction
Kaggle AIEd Challenge 2020 Winners announced in [https://sites.google.com/view/tipce-2021]
This year, the company released EdNet, the world’s largest open database for AI education containing more than 100 million student interactions.
In this competition, your challenge is to create algorithms for “Knowledge Tracing,” the modeling of student knowledge over time. The goal is to accurately predict how students will perform on future interactions. You will pair your machine learning skills using Riiid’s EdNet data.
Kaggle 2nd place solution with an explanation paper
- LSTM-SAKT: LSTM-encoded SAKT-like transformer for knowledge tracing (Oya & Morishima, 2021)
- Kaggle notebook: https://www.kaggle.com/mamasinkgs/public-private-2nd-place-solution
- Additional discussion: https://www.kaggle.com/c/riiid-test-answer-prediction/discussion/210113
EdNet Shared Task Papers (7 papers)
- Paper 1: “Modeling the EdNet Dataset with Logistics Regression”
- Paper 2: “Do We Need to Go Deep? Knowledge Tracing with Big Data
- Paper 3: Interpreting Deep Knowledge Tracing Model on EdNet Dataset”
- Paper 4: On the Interpretability of Deep Learning Based Models for Knowledge Tracing”
- Paper 5: Neural Knowledge Tracing for EdNet Correctness Prediction”
- Paper 6: An Empirical Comparison of Deep Learning Models for Knowledge Tracing on Large-Scale Dataset
- Paper 7: Evaluating DAS3H on the EdNet Dataset