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

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

doi:10.1109/TALE.2018.8615395

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

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

School of Education and Social Policy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

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 language	English (US)
Title of host publication	Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018
Editors	Mark J.W. Lee, Sasha Nikolic, Montserrat Ros, Jun Shen, Leon C. U. Lei, Gary K.W. Wong, Neelakantam Venkatarayalu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1146-1149
Number of pages	4
ISBN (Electronic)	9781538665220
DOIs	https://doi.org/10.1109/TALE.2018.8615395
State	Published - Jul 2 2018
Event	2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018 - Wollongong, Australia Duration: Dec 4 2018 → Dec 7 2018

Publication series

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

Conference

Conference	2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018
Country/Territory	Australia
City	Wollongong
Period	12/4/18 → 12/7/18

Keywords

blogs
natural language processing
project-based learning
social media

ASJC Scopus subject areas

Education
Artificial Intelligence
Computer Networks and Communications
Engineering (miscellaneous)

Access to Document

10.1109/TALE.2018.8615395

Cite this

Lee, S. P., Perez, M. R., Worsley, M. B., & Burgess, B. D. (2018). Utilizing Natural Language Processing (NLP) to Evaluate Engagement in Project-Based Learning. In M. J. W. Lee, S. Nikolic, M. Ros, J. Shen, L. C. U. Lei, G. K. W. Wong, & N. Venkatarayalu (Eds.), Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018 (pp. 1146-1149). Article 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 Bonilla et al. / 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 ; Montserrat Ros ; Jun Shen ; Leon C. U. Lei ; Gary K.W. Wong ; Neelakantam Venkatarayalu. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1146-1149 (Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018).

@inproceedings{aee7be2b84634169a0b883ddbf7ed1d7,

title = "Utilizing Natural Language Processing (NLP) to Evaluate Engagement in Project-Based Learning",

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.",

keywords = "blogs, natural language processing, project-based learning, social media",

author = "Lee, {Sarah Priscilla} and Perez, {Melissa Renae} and Worsley, {Marcelo Bonilla} and Burgess, {Bobbie Dlan}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018 ; Conference date: 04-12-2018 Through 07-12-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/TALE.2018.8615395",

language = "English (US)",

series = "Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1146--1149",

editor = "Lee, {Mark J.W.} and Sasha Nikolic and Montserrat Ros and Jun Shen and Lei, {Leon C. U.} and Wong, {Gary K.W.} and Neelakantam Venkatarayalu",

booktitle = "Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018",

address = "United States",

}

Lee, SP, Perez, MR, Worsley, MB & Burgess, BD 2018, Utilizing Natural Language Processing (NLP) to Evaluate Engagement in Project-Based Learning. in MJW Lee, S Nikolic, M Ros, J Shen, LCU Lei, GKW Wong & 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 Bonilla et al.
Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018. ed. / Mark J.W. Lee; Sasha Nikolic; Montserrat Ros; Jun Shen; Leon C. U. Lei; Gary K.W. Wong; Neelakantam Venkatarayalu. Institute of Electrical and Electronics Engineers Inc., 2018. 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 proceeding › Conference contribution

TY - GEN

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

AU - Lee, Sarah Priscilla

AU - Perez, Melissa Renae

AU - Worsley, Marcelo Bonilla

AU - Burgess, Bobbie Dlan

PY - 2018/7/2

Y1 - 2018/7/2

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.

KW - blogs

KW - natural language processing

KW - project-based learning

KW - social media

UR - http://www.scopus.com/inward/record.url?scp=85062091150&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85062091150&partnerID=8YFLogxK

U2 - 10.1109/TALE.2018.8615395

DO - 10.1109/TALE.2018.8615395

M3 - Conference contribution

AN - SCOPUS:85062091150

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 - Ros, Montserrat

A2 - Shen, Jun

A2 - Lei, Leon C. U.

A2 - Wong, Gary K.W.

A2 - Venkatarayalu, Neelakantam

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018

Y2 - 4 December 2018 through 7 December 2018

ER -

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

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

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this