Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT

Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil Heffernan, Xintao Wu, Sean McGrew, Dongwon Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Educational content labeled with proper knowledge components (KCs) are particularly useful to teachers or content organizers. However, manually labeling educational content is labor intensive and error-prone. To address this challenge, prior research proposed machine learning based solutions to auto-label educational content with limited success. In this work, we significantly improve prior research by (1) expanding the input types to include KC descriptions, instructional video titles, and problem descriptions (i.e., three types of prediction task), (2) doubling the granularity of the prediction from 198 to 385 KC labels (i.e., more practical setting but much harder multinomial classification problem), (3) improving the prediction accuracies by 0.5–2.3% using Task-adaptive Pre-trained BERT, outperforming six baselines, and (4) proposing a simple evaluation measure by which we can recover 56–73% of mispredicted KC labels. All codes and data sets in the experiments are available at: https://github.com/tbs17/TAPT-BERT.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 22nd International Conference, AIED 2021, Proceedings
EditorsIdo Roll, Danielle McNamara, Sergey Sosnovsky, Rose Luckin, Vania Dimitrova
PublisherSpringer Science and Business Media Deutschland GmbH
Pages408-419
Number of pages12
ISBN (Print)9783030782917
DOIs
StatePublished - 2021
Event22nd International Conference on Artificial Intelligence in Education, AIED 2021 - Virtual, Online
Duration: Jun 14 2021Jun 18 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12748 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Artificial Intelligence in Education, AIED 2021
CityVirtual, Online
Period6/14/216/18/21

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

Fingerprint

Dive into the research topics of 'Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT'. Together they form a unique fingerprint.

Cite this