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Leveraging Book Indexes for Automatic Extraction of Concepts in MOOCs

Authors:

Assma Boughoula,

Aidan San,

ChengXiang ZhaiAuthors Info & Claims

L@S '20: Proceedings of the Seventh ACM Conference on Learning @ Scale

Pages 381 - 384

https://doi.org/10.1145/3386527.3406749

Published: 12 August 2020 Publication History

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Abstract

Concepts are basic elements in any learning module and are thus very useful for modeling, summarizing, and previewing the content of any module. Automatic extraction of the major concepts from online education materials enables many useful applications. In this paper, we propose to leverage textbooks and their back-of-the-book indexes as training data to train a supervised machine learning algorithm for automatic extraction of concepts from text data in the education domain. We evaluate this idea by training neural networks on three textbooks and applying the trained neural networks to extract concepts from the lecture transcripts of two MOOCs. Our results suggest great promise for further exploration of this direction.

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Digital Library

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Cited By

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Tix BBinsted K(2024)Better Results Through Ambiguity Resolution: Large Language Models that Ask Clarifying QuestionsAugmented Cognition10.1007/978-3-031-61572-6_6(72-87)Online publication date: 29-Jun-2024
https://dl.acm.org/doi/10.1007/978-3-031-61572-6_6
Boughoula ARos KZhai C(2022)An Optimization Approach to Automatic Construction of Browsable Concept Index for Organizing Online Educational Content2022 IEEE International Conference on Knowledge Graph (ICKG)10.1109/ICKG55886.2022.00011(22-31)Online publication date: Nov-2022
https://doi.org/10.1109/ICKG55886.2022.00011

Index Terms

Leveraging Book Indexes for Automatic Extraction of Concepts in MOOCs
1. Applied computing
  1. Education
    1. E-learning
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Information extraction

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L@S '20: Proceedings of the Seventh ACM Conference on Learning @ Scale

August 2020

442 pages

ISBN:9781450379519

DOI:10.1145/3386527

General Chair:
David Joyner
Georgia Tech
,
Program Chairs:
Rene Kizilcec
Cornell University
,
Susan Singer
Rollins College

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Association for Computing Machinery

New York, NY, United States

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Published: 12 August 2020

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L@S '20

L@S '20: Seventh (2020) ACM Conference on Learning @ Scale

August 12 - 14, 2020

Virtual Event, USA

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Tix BBinsted K(2024)Better Results Through Ambiguity Resolution: Large Language Models that Ask Clarifying QuestionsAugmented Cognition10.1007/978-3-031-61572-6_6(72-87)Online publication date: 29-Jun-2024
https://dl.acm.org/doi/10.1007/978-3-031-61572-6_6
Boughoula ARos KZhai C(2022)An Optimization Approach to Automatic Construction of Browsable Concept Index for Organizing Online Educational Content2022 IEEE International Conference on Knowledge Graph (ICKG)10.1109/ICKG55886.2022.00011(22-31)Online publication date: Nov-2022
https://doi.org/10.1109/ICKG55886.2022.00011

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Cited By

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Recommendations

Crowd-sourced learning in MOOCs: learning analytics meets measurement theory

Facilitating MOOCs learning through weekly meet-up: a case study in Taiwan

Supportiveness of language MOOCs for self-regulated learning: a review of commercial language MOOCs on the market

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