Intelligent Tutoring Systems - If You Build (and Open) Them, The Answers Will Come.
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| Title: | Intelligent Tutoring Systems - If You Build (and Open) Them, The Answers Will Come. |
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| Authors: | WEITZ, ROB1 rob.weitz@shu.edu, KODAGANALLUR, VISWANATHAN1, ROSENTHAL, DAVID1 |
| Source: | Technology, Instruction, Cognition & Learning. 2010, Vol. 8 Issue 1, p1-14. 14p. |
| Subject Terms: | *Intelligent tutoring systems, *Computer assisted instruction, *Brain, Expert systems, Information theory |
| Abstract: | Building intelligent tutoring systems presents significant challenges -- one challenge arises because tutoring is concerned with unobservable inner workings of the human brain; another results from the formidable task of knowledge representation and reasoning; still a third is due to the competing theories of teaching and learning. Over the past four decades, the intelligent tutoring systems community has made significant progress. Recently the field has witnessed some important and substantive debates, centered broadly on issues of knowledge representation, tutoring paradigms and deep infrastructures. We broaden the debate and raise new issues that can advance the state of the art in research and practice. We argue that there is little to distinguish constraint-based and cognitive tutors in terms of deep infrastructures. Further, we contend that the most productive way to pursue this debate and to more generally advance the field of intelligent tutors is to a) have the same researchers build tutors using different paradigms, b) use currently defined high standards for evaluation, c) open the knowledge bases of existing tutors and d) make the tutors themselves available for examination and testing by the intelligent tutor community. [ABSTRACT FROM AUTHOR] |
| Copyright of Technology, Instruction, Cognition & Learning is the property of Old City Publishing, Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 55233105 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Intelligent Tutoring Systems - If You Build (and Open) Them, The Answers Will Come. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22WEITZ%2C+ROB%22">WEITZ, ROB</searchLink><relatesTo>1</relatesTo><i> rob.weitz@shu.edu</i><br /><searchLink fieldCode="AR" term="%22KODAGANALLUR%2C+VISWANATHAN%22">KODAGANALLUR, VISWANATHAN</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22ROSENTHAL%2C+DAVID%22">ROSENTHAL, DAVID</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Technology%2C+Instruction%2C+Cognition+%26+Learning%22">Technology, Instruction, Cognition & Learning</searchLink>. 2010, Vol. 8 Issue 1, p1-14. 14p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Intelligent+tutoring+systems%22">Intelligent tutoring systems</searchLink><br />*<searchLink fieldCode="DE" term="%22Computer+assisted+instruction%22">Computer assisted instruction</searchLink><br />*<searchLink fieldCode="DE" term="%22Brain%22">Brain</searchLink><br /><searchLink fieldCode="DE" term="%22Expert+systems%22">Expert systems</searchLink><br /><searchLink fieldCode="DE" term="%22Information+theory%22">Information theory</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Building intelligent tutoring systems presents significant challenges -- one challenge arises because tutoring is concerned with unobservable inner workings of the human brain; another results from the formidable task of knowledge representation and reasoning; still a third is due to the competing theories of teaching and learning. Over the past four decades, the intelligent tutoring systems community has made significant progress. Recently the field has witnessed some important and substantive debates, centered broadly on issues of knowledge representation, tutoring paradigms and deep infrastructures. We broaden the debate and raise new issues that can advance the state of the art in research and practice. We argue that there is little to distinguish constraint-based and cognitive tutors in terms of deep infrastructures. Further, we contend that the most productive way to pursue this debate and to more generally advance the field of intelligent tutors is to a) have the same researchers build tutors using different paradigms, b) use currently defined high standards for evaluation, c) open the knowledge bases of existing tutors and d) make the tutors themselves available for examination and testing by the intelligent tutor community. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Technology, Instruction, Cognition & Learning is the property of Old City Publishing, Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=55233105 |
| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1 Subjects: – SubjectFull: Intelligent tutoring systems Type: general – SubjectFull: Computer assisted instruction Type: general – SubjectFull: Brain Type: general – SubjectFull: Expert systems Type: general – SubjectFull: Information theory Type: general Titles: – TitleFull: Intelligent Tutoring Systems - If You Build (and Open) Them, The Answers Will Come. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: WEITZ, ROB – PersonEntity: Name: NameFull: KODAGANALLUR, VISWANATHAN – PersonEntity: Name: NameFull: ROSENTHAL, DAVID IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: 2010 Type: published Y: 2010 Identifiers: – Type: issn-print Value: 15400182 Numbering: – Type: volume Value: 8 – Type: issue Value: 1 Titles: – TitleFull: Technology, Instruction, Cognition & Learning Type: main |
| ResultId | 1 |
