An Interaction Design for Machine Teaching to Develop AI Tutors
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| Title: | An Interaction Design for Machine Teaching to Develop AI Tutors |
|---|---|
| Language: | English |
| Authors: | Daniel Weitekamp III (ORCID |
| Source: | Grantee Submission. 2020. |
| Peer Reviewed: | Y |
| Page Count: | 11 |
| Publication Date: | 2020 |
| Sponsoring Agency: | Institute of Education Sciences (ED) Google LLC |
| Contract Number: | R305B150008 |
| Document Type: | Speeches/Meeting Papers Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Artificial Intelligence, Intelligent Tutoring Systems, Instructional Design, Simulation, Educational Technology, Graduate Students, Doctoral Students, Prior Learning, Skill Development, Problem Solving |
| DOI: | 10.1145/3313831.3376226 |
| Abstract: | 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.] |
| Abstractor: | As Provided |
| IES Funded: | Yes |
| Entry Date: | 2025 |
| Accession Number: | ED663759 |
| Database: | ERIC |
| Abstract: | 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.] |
|---|---|
| DOI: | 10.1145/3313831.3376226 |
