A Conversational Agent to Improve Response Quality in Course Evaluations
Journal
Conference on Human Factors in Computing Systems (CHI)
Type
conference paper
Date Issued
2020-04
Author(s)
Abstract (De)
Recent advances in Natural Language Processing (NLP) bear the opportunity to design new forms of human-computer interaction with conversational interfaces. We hypothesize that these interfaces can interactively engage students to increase response quality of course evaluations in education compared to the common standard of web surveys. Past research indicates that web surveys come with disadvantages, such as poor response quality caused by inattention, survey fatigue or satisficing behavior. To test if conversational interfaces have a positive impact on the level of enjoyment and the response quality, we design an NLP-based conversational agent and deploy it in a field experiment with 127 students in our lecture and compare it with a web survey as a baseline. Our findings indicate that using conversational agents for evaluations are resulting in higher levels of response quality and level of enjoyment, and are therefore, a promising approach to increase the effectiveness of surveys in general.
Language
English
HSG Classification
contribution to scientific community
HSG Profile Area
SoM - Business Innovation
Refereed
Yes
Event Title
Conference on Human Factors in Computing Systems (CHI)
Event Location
Honolulu, Hawaii
Event Date
25-30 April 2020
Official URL
Division(s)
Eprints ID
259507
File(s)![Thumbnail Image]()
open.access
Name
LBW349.pdf
Size
1020.95 KB
Format
Adobe PDF
Checksum (MD5)
6e1dde4bed77cfd2b9e2304b5035a172