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  4. Sara, the Lecturer: Improving Learning in Online Education with a Scaffolding-Based Conversational Agent
 
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Sara, the Lecturer: Improving Learning in Online Education with a Scaffolding-Based Conversational Agent

Journal
ACM CHI Conference on Human Factors in Computing Systems
Type
conference paper
Date Issued
2020-04-25
Author(s)
Winkler, Rainer  
Hobert, Sebastian
Salovaara, Antti
Söllner, Matthias  
Leimeister, Jan Marco  
Abstract (De)
Enrollment in online courses has sharply increased in higher education. Although online education can be scaled to large audiences, the lack of interaction between educators and learners is difficult to replace and remains a primary chal-lenge in the field. Conversational agents may alleviate this problem by engaging in natural interaction and by scaffold-ing learners’ understanding similarly to educators. However, whether this approach can also be used to enrich online video lectures has largely remained unknown. We developed Sara, a conversational agent that appears during an online video lecture. She provides scaffolds by voice and text when needed and includes a voice-based input mode. An evalua-tion with 182 learners in a 2 x 2 lab experiment demonstrated that Sara, compared to more traditional conversational agents, significantly improved learning in a programming task. This study highlights the importance of including scaf-folding and voice-based conversational agents in online videos to improve meaningful learning.
Language
English
HSG Classification
contribution to scientific community
HSG Profile Area
SoM - Business Innovation
Refereed
Yes
Publisher
ACM CHI Conference on Human Factors in Computing Systems
Publisher place
Honolulu, Hawai'i
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/112203
Subject(s)

information managemen...

education

Division(s)

IWI - Institute of In...

Eprints ID
259193
File(s)
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Thumbnail Image

open.access

Name

chi20c-sub8720-cam-i16.pdf

Size

990.84 KB

Format

Adobe PDF

Checksum (MD5)

8657319623a44b0a28282386749e8bef

Loading...
Thumbnail Image

open.access

Name

chi20c-sub8720-cam-i16.pdf

Size

990.84 KB

Format

Adobe PDF

Checksum (MD5)

8657319623a44b0a28282386749e8bef

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