TY - JOUR
T1 - Machine-assisted analysis of communication in environmental engineering
AU - Taraban, Roman
AU - Robledo, David
AU - Donato, Francesco V.
AU - Campbell, Ryan C.
AU - Kim, Jeong Hee
AU - Reible, Danny D.
AU - Na, Chongzheng
N1 - Publisher Copyright:
© American Society for Engineering Education 2020.
PY - 2020/6/22
Y1 - 2020/6/22
N2 - ABET is committed to promoting the broad development of engineering students, including knowledge of the social, cultural, environmental, and global implications of engineering practice. Coincident with the cultural shift within engineering education is a scholarly interest in the formal and informal communications of engineers and students. The present study was situated in a graduate course in environmental engineering that incorporated the arts and humanities with the goal of developing personal and professional reflection in students. The goal of this paper is to describe and analyze two methods of machine-based formative assessment of students' essays written in response to lectures and activities that related to art and narrative within the course. The two machine-based tools used here were i) naïve Bayes analysis and ii) Meaning Extraction Helper. The results showed that both tools were able to identify differences in student essays. We suggest several ways in which these machine-based methods could be extended to aid in assessing learning and reflective thinking in students.
AB - ABET is committed to promoting the broad development of engineering students, including knowledge of the social, cultural, environmental, and global implications of engineering practice. Coincident with the cultural shift within engineering education is a scholarly interest in the formal and informal communications of engineers and students. The present study was situated in a graduate course in environmental engineering that incorporated the arts and humanities with the goal of developing personal and professional reflection in students. The goal of this paper is to describe and analyze two methods of machine-based formative assessment of students' essays written in response to lectures and activities that related to art and narrative within the course. The two machine-based tools used here were i) naïve Bayes analysis and ii) Meaning Extraction Helper. The results showed that both tools were able to identify differences in student essays. We suggest several ways in which these machine-based methods could be extended to aid in assessing learning and reflective thinking in students.
UR - http://www.scopus.com/inward/record.url?scp=85095738056&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85095738056
SN - 2153-5965
VL - 2020-June
JO - ASEE Annual Conference and Exposition, Conference Proceedings
JF - ASEE Annual Conference and Exposition, Conference Proceedings
M1 - 978
T2 - 2020 ASEE Virtual Annual Conference, ASEE 2020
Y2 - 22 June 2020 through 26 June 2020
ER -