Work in Progress

Analyzing Student Reflection Sentiments and Problem-Solving Procedures in MOOCs

Authors:

Alexander Shashkov,

Una-May O'ReillyAuthors Info & Claims

L@S '21: Proceedings of the Eighth ACM Conference on Learning @ Scale

Pages 247 - 250

https://doi.org/10.1145/3430895.3460150

Published: 08 June 2021 Publication History

Abstract

Student reflection is thought to be an important part of retaining and understanding knowledge gained in a course. Using natural language processing, we analyze and interpret student reflections from Massive Open Online Courses (MOOCs) to understand the students' sentiments and problem-solving procedures. The reflections are free text responses to questions from MIT 6.00.1x, an introductory programming MOOC. We compare different sentiment analysis methods, and conclude that the best-performing methods can robustly classify sentiment of student responses. In addition, we develop methods to analyze student problem-solving procedures using sentence parsing and topic modeling. We find our method can distinguish some common problem-solving procedures such as utilizing course resources.

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A short video introduction to the paper "Analyzing Student Reflection Sentiments and Problem-Solving Procedures in MOOCs", in which we extract student sentiment and common problem-solving procedures from free text reflections.

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References

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Cited By

Kong BHemberg EBell AO'Reilly UHilliger IKhosravi HRienties BDawson S(2023)Investigating Student's Problem-solving Approaches in MOOCs using Natural Language ProcessingLAK23: 13th International Learning Analytics and Knowledge Conference10.1145/3576050.3576091(262-272)Online publication date: 13-Mar-2023
https://dl.acm.org/doi/10.1145/3576050.3576091
Solopova VRostom ECremer FGruszczynski AWitte SZhang CLópez FPlößl LHofmann FRomeike RGläser-Zikuda MBenzmüller CLandgraf T(2023)PapagAI: Automated Feedback for Reflective EssaysKI 2023: Advances in Artificial Intelligence10.1007/978-3-031-42608-7_16(198-206)Online publication date: 26-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-42608-7_16

Index Terms

Analyzing Student Reflection Sentiments and Problem-Solving Procedures in MOOCs
1. Applied computing
  1. Education
2. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Information extraction

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Information

Published In

cover image ACM Other conferences

L@S '21: Proceedings of the Eighth ACM Conference on Learning @ Scale

June 2021

380 pages

ISBN:9781450382151

DOI:10.1145/3430895

General Chair:
Christoph Meinel
Hasso Plattner Institute for Digital Engineering Potsdam, Germany
,
Program Chairs:
Mar Pérez-Sanagustín
Paul Sabatier University Toulouse III, France
,
Marcus Specht
TU Delft, Netherlands
,
Amy Ogan
Carnegie Mellon University, USA

Copyright © 2021 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 08 June 2021

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L@S '21

L@S '21: Eighth (2021) ACM Conference on Learning @ Scale

June 22 - 25, 2021

Virtual Event, Germany

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Overall Acceptance Rate 93 of 382 submissions, 24%

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Cited By

Kong BHemberg EBell AO'Reilly UHilliger IKhosravi HRienties BDawson S(2023)Investigating Student's Problem-solving Approaches in MOOCs using Natural Language ProcessingLAK23: 13th International Learning Analytics and Knowledge Conference10.1145/3576050.3576091(262-272)Online publication date: 13-Mar-2023
https://dl.acm.org/doi/10.1145/3576050.3576091
Solopova VRostom ECremer FGruszczynski AWitte SZhang CLópez FPlößl LHofmann FRomeike RGläser-Zikuda MBenzmüller CLandgraf T(2023)PapagAI: Automated Feedback for Reflective EssaysKI 2023: Advances in Artificial Intelligence10.1007/978-3-031-42608-7_16(198-206)Online publication date: 26-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-42608-7_16

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