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Question-type Identification for Academic Questions in Online Learning Platform

arXiv 2211.13727 ↗First posted 24 Nov 2022cs.CL cs.AI cs.LGcited by 0

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Abstract (arXiv)

Online learning platforms provide learning materials and answers to students' academic questions by experts, peers, or systems. This paper explores question-type identification as a step in content understanding for an online learning platform. The aim of the question-type identifier is to categorize question types based on their structure and complexity, using the question text, subject, and structural features. We have defined twelve question-type classes, including Multiple-Choice Question (MCQ), essay, and others. We have compiled an internal dataset of students' questions and used a combination of weak-supervision techniques and manual annotation. We then trained a BERT-based ensemble model on this dataset and evaluated this model on a separate human-labeled test set. Our experiments yielded an F1-score of 0.94 for MCQ binary classification and promising results for 12-class multilabel classification. We deployed the model in our online learning platform as a crucial enabler for content understanding to enhance the student learning experience.

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References · 11

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,166
  3. 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,307
  4. 2018CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledgecited by 1,822
  5. 2018Know What You Don't Know: Unanswerable Questions for SQuADcited by 1,554
  6. 2017Snorkel: Rapid Training Data Creation with Weak Supervisioncited by 372
  7. 2022QALD-9-plus: A Multilingual Dataset for Question Answering over DBpedia and Wikidata Translated by Native Speakerscited by 39
  8. 2019Multi-class Hierarchical Question Classification for Multiple Choice Science Examscited by 7
  9. 2017RiPLE: Recommendation in Peer-Learning Environments Based on Knowledge Gaps and Interestscited by 3
  10. 2022A New Era: Intelligent Tutoring Systems Will Transform Online Learning for Millionscited by 3
  11. 2020Question Type Classification Methods Comparisoncited by 1

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