ERIC Number: ED663759
Record Type: Non-Journal
Publication Date: 2020-Apr
Pages: 11
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Available Date: N/A
An Interaction Design for Machine Teaching to Develop AI Tutors
Grantee Submission, Paper presented at the Annual Conference on Human Factors in Computing Systems (CHI 2020) (Honolulu, HI, Apr 25-30, 2020)
Intelligent tutoring systems (ITSs) have consistently been shown to improve the educational outcomes of students when used alone or combined with traditional instruction. However, building an ITS is a time-consuming process which requires specialized knowledge of existing tools. Extant authoring methods, including the Cognitive Tutor Authoring Tools' (CTAT) example-tracing method and SimStudent's Authoring by Tutoring, use programming-by-demonstration to allow authors to build ITSs more quickly than they could by hand programming with model-tracing. Yet these methods still suffer from long authoring times or difficulty creating complete models. In this study, we demonstrate that Simulated Learners built with the Apprentice Learner (AL) Framework can be combined with a novel interaction design that emphasizes model transparency, input flexibility, and problem solving control to enable authors to achieve greater model completeness in less time than existing authoring methods. [This paper was published in: "CHI '20 Conference on Human Factors in Computing Systems," ACM, 2020, Paper 99.]
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: Institute of Education Sciences (ED); Google LLC
Authoring Institution: N/A
IES Funded: Yes
Grant or Contract Numbers: R305B150008
Author Affiliations: N/A