Curiosity notebook: a platform for learning by teaching conversational agents

Edith Law, Parastoo Baghaei Ravari, Nalin Chhibber, Dana Kulic, Stephanie Lin, Kevin D. Pantasdo, Jessy Ceha, Sangho Suh, Nicole Dillen

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

1 Citation (Scopus)


Learning by teaching is an established pedagogical technique; however, the exact process through which learning happens remains difficult to assess, in part due to the variability in the tutor-tutee pairing and interaction. Prior research proposed the use of teachable agents acting as students, in order to facilitate more controlled studies of the learning by teaching phenomenon. In this work, we introduce a learning by teaching platform, Curiosity Notebook, which allows students to work individually or in groups to teach a conversational agent a classification task in a variety of subject topics. We conducted a 4-week exploratory study with 12 fourth and fifth grade elementary school children, who taught a conversational robot how to classify animals, rocks/minerals and paintings. This paper outlines the architecture of our system, describes the lessons learned from the study, and contributes design considerations on how to design conversational agents and applications for learning by teaching scenarios.

Original languageEnglish
Title of host publicationCHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
EditorsJoanna McGrenere, Andy Cockburn
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages9
ISBN (Electronic)9781450368193
Publication statusPublished - 2020
EventInternational Conference on Human Factors in Computing Systems 2020 - Honolulu , United States of America
Duration: 25 Apr 202030 Apr 2020
Conference number: 38th (Website) (Proceedings)

Publication series

NameConference on Human Factors in Computing Systems - Proceedings


ConferenceInternational Conference on Human Factors in Computing Systems 2020
Abbreviated titleCHI 2020
CountryUnited States of America
Internet address


  • Conversational agents
  • Learning by teaching

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