Utilizing Natural Language Processing (NLP) to Evaluate Engagement in Project-Based Learning

Sarah Priscilla Lee, Melissa Renae Perez, Marcelo Aaron Bonilla Worsley, Bobbie Dlan Burgess

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

Abstract

In a time of rapid development, 21st century learning emphasizes innovative thinking and making. This has heightened interest in STEAM subjects and its implementation in traditional classrooms through project-based learning (PBL). However, assessment is difficult for open-ended, PBL activities. This work-in-progress study utilizes natural language processing (NLP) tools to analyze content produced in a middle-school media arts classroom. The authors examine student engagement and excitement along dimensions of tone and authenticity. We discuss the results of NLP vis-a-vis feedback that 1) determines student engagement and excitement and 2) improves the implementation and display of project-based learning in traditional classrooms.

Original languageEnglish (US)
Title of host publicationProceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018
EditorsMark J.W. Lee, Sasha Nikolic, Gary K.W. Wong, Jun Shen, Montserrat Ros, Leon C. U. Lei, Neelakantam Venkatarayalu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1146-1149
Number of pages4
ISBN (Electronic)9781538665220
DOIs
Publication statusPublished - Jan 16 2019
Event2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018 - Wollongong, Australia
Duration: Dec 4 2018Dec 7 2018

Publication series

NameProceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018

Conference

Conference2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018
CountryAustralia
CityWollongong
Period12/4/1812/7/18

    Fingerprint

Keywords

  • blogs
  • natural language processing
  • project-based learning
  • social media

ASJC Scopus subject areas

  • Education
  • Artificial Intelligence
  • Computer Networks and Communications
  • Engineering (miscellaneous)

Cite this

Lee, S. P., Perez, M. R., Worsley, M. A. B., & Burgess, B. D. (2019). Utilizing Natural Language Processing (NLP) to Evaluate Engagement in Project-Based Learning. In M. J. W. Lee, S. Nikolic, G. K. W. Wong, J. Shen, M. Ros, L. C. U. Lei, & N. Venkatarayalu (Eds.), Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018 (pp. 1146-1149). [8615395] (Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TALE.2018.8615395