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
StatePublished - 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

Students
Processing
language
classroom
learning
Display devices
Feedback
authenticity
student
art
time

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
Lee, Sarah Priscilla ; Perez, Melissa Renae ; Worsley, Marcelo Aaron Bonilla ; Burgess, Bobbie Dlan. / Utilizing Natural Language Processing (NLP) to Evaluate Engagement in Project-Based Learning. Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018. editor / Mark J.W. Lee ; Sasha Nikolic ; Gary K.W. Wong ; Jun Shen ; Montserrat Ros ; Leon C. U. Lei ; Neelakantam Venkatarayalu. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1146-1149 (Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018).
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Lee, SP, Perez, MR, Worsley, MAB & Burgess, BD 2019, Utilizing Natural Language Processing (NLP) to Evaluate Engagement in Project-Based Learning. in MJW Lee, S Nikolic, GKW Wong, J Shen, M Ros, LCU Lei & N Venkatarayalu (eds), Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018., 8615395, Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018, Institute of Electrical and Electronics Engineers Inc., pp. 1146-1149, 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018, Wollongong, Australia, 12/4/18. https://doi.org/10.1109/TALE.2018.8615395

Utilizing Natural Language Processing (NLP) to Evaluate Engagement in Project-Based Learning. / Lee, Sarah Priscilla; Perez, Melissa Renae; Worsley, Marcelo Aaron Bonilla; Burgess, Bobbie Dlan.

Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018. ed. / Mark J.W. Lee; Sasha Nikolic; Gary K.W. Wong; Jun Shen; Montserrat Ros; Leon C. U. Lei; Neelakantam Venkatarayalu. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1146-1149 8615395 (Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018).

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

TY - GEN

T1 - Utilizing Natural Language Processing (NLP) to Evaluate Engagement in Project-Based Learning

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AU - Perez, Melissa Renae

AU - Worsley, Marcelo Aaron Bonilla

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N2 - 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.

AB - 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.

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M3 - Conference contribution

T3 - Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018

SP - 1146

EP - 1149

BT - Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018

A2 - Lee, Mark J.W.

A2 - Nikolic, Sasha

A2 - Wong, Gary K.W.

A2 - Shen, Jun

A2 - Ros, Montserrat

A2 - Lei, Leon C. U.

A2 - Venkatarayalu, Neelakantam

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Lee SP, Perez MR, Worsley MAB, Burgess BD. Utilizing Natural Language Processing (NLP) to Evaluate Engagement in Project-Based Learning. In Lee MJW, Nikolic S, Wong GKW, Shen J, Ros M, Lei LCU, Venkatarayalu N, editors, Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1146-1149. 8615395. (Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018). https://doi.org/10.1109/TALE.2018.8615395