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Content Type Distribution and Readability of MOOCs

Published: 12 August 2020 Publication History

Abstract

Massive open online courses (MOOCs) provide a great opportunity to use multiple means of information representation through a mixture of various media such as text, graphics, and video, among others. However, most research on MOOCs focused on learning analytics and not much attention is given to content analysis. We gathered all text corpora and video transcripts of selected MOOCs using a web crawler and looked at word counts, clustered by distribution, and measured readability of the crawled data. Analyzing content distribution allows for a comparison of MOOCs regardless of topics, thus giving us an idea of what most course developers might think is ideal in terms of content distribution. This comparison along with readability analysis can be useful for course pre-run quality assessment and gauging content sufficiency.

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Massive open online courses (MOOCs) provide a great opportunity to use multiple means of information representation through a mixture of various media such as text, graphics, and video, among others. However, most research on MOOCs have focused on learning analytics, and not much attention is given to content analysis. We gathered all text corpora and video transcripts of selected MOOCs using a web crawler and looked at word counts, clustered by distribution, and measured readability of the crawled data. Analyzing content distribution allows for a comparison of MOOCs regardless of topics, thus giving us an idea of what most course developers might think is ideal in terms of content distribution. This comparison, along with readability analysis, can be useful for course pre-run quality assessment and gauging content sufficiency.

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Jeffrey S. Cross, Nopphon Keerativoranan, May Kristine Jonson Carlon, Yong Hong Tan, Zarina Rakhimberdina, Hideki Mori. 2019. Improving MOOC Quality Using Learning Analytics and Tools. In Proceedings of the IEEE 2019 Learning with MOOCs. (LWMOOCS'19), 174--179.
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Dan Davis, Daniel Seaton, Claudia Hauff, and Geert-Jan Houben. 2018. Toward Large-Scale Learning Design: Categorizing Course Designs in Service of Supporting Learning Outcomes. In Proceedings of the Fifth Annual ACM Conference on Learning at Scale. (L@S'18), 1--10.
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Do-Jong Kim, Yong-Woon Park, and Dong-Jo Park. 2001. A novel validity index for determination of the optimal number of clusters. IEICE Transactions on Information and Systems 84.2: 281--285.
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J. Peter Kincaid, Robert P. Fishburne Jr, Richard L. Rogers, and Brad S. Chissom. 1975. Derivation of new readability formulas (automated readability index, fog count, and flesch reading ease formula) for navy enlisted personnel.
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Stanford University: Open Learning Initiative. 2015. Creating Effective Online and Blended Courses. Retrieved January 1, 2020 from https://lagunita.stanford.edu/courses/StanfordOnline/O.P.E.N./CourseDesign/about
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Caroline Stratton and Rob Grace. 2016. Exploring linguistic diversity of MOOCS: Implications for international development. Proc. Assoc. Inform. Science and Technology, 53(1), 1--10
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European Credit Transfer and Accumulation System (ECTS). Retrieved May 21, 2020 from https://ec.europa.eu/education/resources-and-tools/european-credit-transfer-and-accumulation-system-ects_en

Cited By

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  • (2023)Fine Grained Spoken Document Summarization Through Text Segmentation2022 IEEE Spoken Language Technology Workshop (SLT)10.1109/SLT54892.2023.10022829(647-654)Online publication date: 9-Jan-2023
  • (2023)Educational Data Science Approach for an End-to-End Quality Assurance Process for Building Creditworthy Online CoursesEducational Data Science: Essentials, Approaches, and Tendencies10.1007/978-981-99-0026-8_4(151-191)Online publication date: 30-Apr-2023
  • (2023)Trial Assessment of Online Learners’ Engagement with 360-Degree Architecture VideosImmersive Learning Research Network10.1007/978-3-031-47328-9_5(70-83)Online publication date: 31-Oct-2023
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cover image ACM Other conferences
L@S '20: Proceedings of the Seventh ACM Conference on Learning @ Scale
August 2020
442 pages
ISBN:9781450379519
DOI:10.1145/3386527
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 August 2020

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Author Tags

  1. clustering
  2. content types
  3. moocs
  4. readability
  5. web crawler
  6. word counts

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L@S '20

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Overall Acceptance Rate 117 of 440 submissions, 27%

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Cited By

View all
  • (2023)Fine Grained Spoken Document Summarization Through Text Segmentation2022 IEEE Spoken Language Technology Workshop (SLT)10.1109/SLT54892.2023.10022829(647-654)Online publication date: 9-Jan-2023
  • (2023)Educational Data Science Approach for an End-to-End Quality Assurance Process for Building Creditworthy Online CoursesEducational Data Science: Essentials, Approaches, and Tendencies10.1007/978-981-99-0026-8_4(151-191)Online publication date: 30-Apr-2023
  • (2023)Trial Assessment of Online Learners’ Engagement with 360-Degree Architecture VideosImmersive Learning Research Network10.1007/978-3-031-47328-9_5(70-83)Online publication date: 31-Oct-2023
  • (2022)Mobile-Friendly Content Design for MOOCs: Challenges, Requirements, and Design OpportunitiesProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3502054(1-16)Online publication date: 29-Apr-2022
  • (2022)Microlearning and Automated Assessment – A Framework Implementation of Dissimilar Elements to Achieve Better Educational OutcomesMicrolearning10.1007/978-3-031-13359-6_1(1-26)Online publication date: 26-Oct-2022
  • (2021)Topic Modeling in MOOCs: What Was to Be Discussed, What the Instructor Discussed, and What the Learners Discussed2021 IEEE International Conference on Engineering, Technology & Education (TALE)10.1109/TALE52509.2021.9678621(849-853)Online publication date: 5-Dec-2021

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