Dataset-Driven Research to Support Learning and Knowledge Analytics.
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| Title: | Dataset-Driven Research to Support Learning and Knowledge Analytics. |
|---|---|
| Authors: | Verbert, Katrien1 katrien.verbert@cs.kuleuven.be, Manouselis, Nikos2,3 nikosm@ieee.org, Drachsler, Hendrik4 hendrik.drachsler@ou.nl, Duval, Erik1 erik.duval@cs.kuleuven.be |
| Source: | Educational Technology & Society. Jul2012, Vol. 15 Issue 3, p133-148. 16p. |
| Subject Terms: | *Learning, *Algorithms, *Information technology, *Electronic data processing, *Education, *Research |
| Abstract: | In various research areas, the availability of open datasets is considered as key for research and application purposes. These datasets are used as benchmarks to develop new algorithms and to compare them to other algorithms in given settings. Finding such available datasets for experimentation can be a challenging task in technology enhanced learning, as there are various sources of data that have not been identified and documented exhaustively. In this paper, we provide such an analysis of datasets that can be used for research on learning and knowledge analytics. First, we present a framework for the analysis of educational datasets. Then, we analyze existing datasets along the dimensions of this framework and outline future challenges for the collection and sharing of educational datasets. [ABSTRACT FROM AUTHOR] |
| Copyright of Educational Technology & Society is the property of International Forum of Educational Technology & Society (IFETS) 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: 79816970 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Dataset-Driven Research to Support Learning and Knowledge Analytics. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Verbert%2C+Katrien%22">Verbert, Katrien</searchLink><relatesTo>1</relatesTo><i> katrien.verbert@cs.kuleuven.be</i><br /><searchLink fieldCode="AR" term="%22Manouselis%2C+Nikos%22">Manouselis, Nikos</searchLink><relatesTo>2,3</relatesTo><i> nikosm@ieee.org</i><br /><searchLink fieldCode="AR" term="%22Drachsler%2C+Hendrik%22">Drachsler, Hendrik</searchLink><relatesTo>4</relatesTo><i> hendrik.drachsler@ou.nl</i><br /><searchLink fieldCode="AR" term="%22Duval%2C+Erik%22">Duval, Erik</searchLink><relatesTo>1</relatesTo><i> erik.duval@cs.kuleuven.be</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Educational+Technology+%26+Society%22">Educational Technology & Society</searchLink>. Jul2012, Vol. 15 Issue 3, p133-148. 16p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Learning%22">Learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Information+technology%22">Information technology</searchLink><br />*<searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br />*<searchLink fieldCode="DE" term="%22Education%22">Education</searchLink><br />*<searchLink fieldCode="DE" term="%22Research%22">Research</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In various research areas, the availability of open datasets is considered as key for research and application purposes. These datasets are used as benchmarks to develop new algorithms and to compare them to other algorithms in given settings. Finding such available datasets for experimentation can be a challenging task in technology enhanced learning, as there are various sources of data that have not been identified and documented exhaustively. In this paper, we provide such an analysis of datasets that can be used for research on learning and knowledge analytics. First, we present a framework for the analysis of educational datasets. Then, we analyze existing datasets along the dimensions of this framework and outline future challenges for the collection and sharing of educational datasets. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Educational Technology & Society is the property of International Forum of Educational Technology & Society (IFETS) 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=79816970 |
| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 133 Subjects: – SubjectFull: Learning Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Information technology Type: general – SubjectFull: Electronic data processing Type: general – SubjectFull: Education Type: general – SubjectFull: Research Type: general Titles: – TitleFull: Dataset-Driven Research to Support Learning and Knowledge Analytics. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Verbert, Katrien – PersonEntity: Name: NameFull: Manouselis, Nikos – PersonEntity: Name: NameFull: Drachsler, Hendrik – PersonEntity: Name: NameFull: Duval, Erik IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2012 Type: published Y: 2012 Identifiers: – Type: issn-print Value: 11763647 Numbering: – Type: volume Value: 15 – Type: issue Value: 3 Titles: – TitleFull: Educational Technology & Society Type: main |
| ResultId | 1 |
