OpenTutor: Designing a Rapid-Authored Tutor that Learns as you Grade
Despite strong evidence that dialog-based intelligent tutoring systems (ITS) can increase learning gains, few courses include these tutors. In this research, we posit that existing dialog-based tutoring systems are not widely used because they are too complex and unfamiliar for a typical teacher to...
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| Format: | Article |
| Language: | English |
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LibraryPress@UF
2021-04-01
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| Series: | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
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| Online Access: | https://journals.flvc.org/FLAIRS/article/view/128576 |
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| author | Benjamin D Nye Rushit Sanghrajka Vinit Bodhwani Martin Acob Daniel Budziwojski Kayla Carr Larry Kirshner William R Swartout |
| author_facet | Benjamin D Nye Rushit Sanghrajka Vinit Bodhwani Martin Acob Daniel Budziwojski Kayla Carr Larry Kirshner William R Swartout |
| author_sort | Benjamin D Nye |
| collection | DOAJ |
| description | Despite strong evidence that dialog-based intelligent tutoring systems (ITS) can increase learning gains, few courses include these tutors. In this research, we posit that existing dialog-based tutoring systems are not widely used because they are too complex and unfamiliar for a typical teacher to adapt or augment. OpenTutor is an open-source research project intended to scale up dialog-based tutoring by enabling ordinary teachers to rapidly author and improve dialog-based ITS, where authoring is presented through familiar tasks such as assessment item creation and grading. Formative usability results from a set of five non-CS educators are presented, which indicate that the OpenTutor system was relatively easy to use but that teachers would closely consider the cost benefit for time vs. student outcomes. Specifically, while OpenTutor grading was faster than expected, teachers reported that they would only spend any additional time (compared to a multiple choice) if the content required deeper learning. To decrease time to train answer classifiers, OpenTutor is investigating ways to reduce cold-start problems for tutoring dialogs. |
| format | Article |
| id | doaj-art-2bb504f86df946688f25b488e92112aa |
| institution | OA Journals |
| issn | 2334-0754 2334-0762 |
| language | English |
| publishDate | 2021-04-01 |
| publisher | LibraryPress@UF |
| record_format | Article |
| series | Proceedings of the International Florida Artificial Intelligence Research Society Conference |
| spelling | doaj-art-2bb504f86df946688f25b488e92112aa2025-08-20T01:52:19ZengLibraryPress@UFProceedings of the International Florida Artificial Intelligence Research Society Conference2334-07542334-07622021-04-013410.32473/flairs.v34i1.12857662965OpenTutor: Designing a Rapid-Authored Tutor that Learns as you GradeBenjamin D Nye0Rushit Sanghrajka1Vinit Bodhwani2Martin Acob3Daniel Budziwojski4Kayla Carr5Larry Kirshner6William R Swartout7University of Southern CaliforniaUniversity of UtahUniversity of Southern CaliforniaCalifornia State University, SacramentoUniversity of Southern CaliforniaUniversity of Southern CaliforniaUniversity of Southern CaliforniaUniversity of Southern CaliforniaDespite strong evidence that dialog-based intelligent tutoring systems (ITS) can increase learning gains, few courses include these tutors. In this research, we posit that existing dialog-based tutoring systems are not widely used because they are too complex and unfamiliar for a typical teacher to adapt or augment. OpenTutor is an open-source research project intended to scale up dialog-based tutoring by enabling ordinary teachers to rapidly author and improve dialog-based ITS, where authoring is presented through familiar tasks such as assessment item creation and grading. Formative usability results from a set of five non-CS educators are presented, which indicate that the OpenTutor system was relatively easy to use but that teachers would closely consider the cost benefit for time vs. student outcomes. Specifically, while OpenTutor grading was faster than expected, teachers reported that they would only spend any additional time (compared to a multiple choice) if the content required deeper learning. To decrease time to train answer classifiers, OpenTutor is investigating ways to reduce cold-start problems for tutoring dialogs.https://journals.flvc.org/FLAIRS/article/view/128576intelligent tutoring systemsnatural language processingauthoring toolsonline learningusability |
| spellingShingle | Benjamin D Nye Rushit Sanghrajka Vinit Bodhwani Martin Acob Daniel Budziwojski Kayla Carr Larry Kirshner William R Swartout OpenTutor: Designing a Rapid-Authored Tutor that Learns as you Grade Proceedings of the International Florida Artificial Intelligence Research Society Conference intelligent tutoring systems natural language processing authoring tools online learning usability |
| title | OpenTutor: Designing a Rapid-Authored Tutor that Learns as you Grade |
| title_full | OpenTutor: Designing a Rapid-Authored Tutor that Learns as you Grade |
| title_fullStr | OpenTutor: Designing a Rapid-Authored Tutor that Learns as you Grade |
| title_full_unstemmed | OpenTutor: Designing a Rapid-Authored Tutor that Learns as you Grade |
| title_short | OpenTutor: Designing a Rapid-Authored Tutor that Learns as you Grade |
| title_sort | opentutor designing a rapid authored tutor that learns as you grade |
| topic | intelligent tutoring systems natural language processing authoring tools online learning usability |
| url | https://journals.flvc.org/FLAIRS/article/view/128576 |
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