Let's Teach Kibot: Discovering Discussion Patterns between Student Groups and Two Conversational Agent Designs

Autor/in	Nguyen, Ha
Titel	Let's Teach Kibot: Discovering Discussion Patterns between Student Groups and Two Conversational Agent Designs
Quelle	In: British Journal of Educational Technology, 53 (2022) 6, S.1864-1884 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Nguyen, Ha)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0007-1013
DOI	10.1111/bjet.13219
Schlagwörter	Artificial Intelligence; Cooperative Learning; High School Students; Marine Biology; Discussion (Teaching Technique); Knowledge Level; Technology Uses in Education; Science Instruction + Suchen Sie Ihr Suchwort? Künstliche Intelligenz; Kooperatives Lernen; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Meeresbiologie; Wissensbasis; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht
Abstract	Conversational agents can deepen reasoning and encourage students to build on others' knowledge in collaborative learning. Embedding agents in group work, however, presents challenges where groups may ignore the agents, and this calls for designs where students perceive agents as learning partners. This study examines group interactions with two text-based agents (ie, chatbots) that posed as an expert and a less knowledgeable peer in a high school marine biology lesson. Student messages (N = 1764) from 18 groups (52 students ages 14-15) received codes for reasoning, building on prior ideas, and responsiveness to the agents. Results indicate no differences between agents in how often each discussion move occurred. Interestingly, sequential pattern mining suggests that the less-knowledgeable-peer agent prompted groups to show questioning and building on others' ideas, similar to how students may act as peer tutors to the agent. Meanwhile, sequences with the expert agent resembled student-teacher exchange, where groups responded to the agent's nudges and then provided reasoning. Findings illustrate the affordances of embedding humanized features in technology designs to promote discussion. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01