Modeling Basic Writing Processes From Keystroke Logs.
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| Title: | Modeling Basic Writing Processes From Keystroke Logs. |
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| Authors: | Guo, Hongwen1, Deane, Paul D.1, van Rijn, Peter W.1, Zhang, Mo1, Bennett, Randy E.1 |
| Source: | Journal of Educational Measurement. Summer2018, Vol. 55 Issue 2, p194-216. 23p. |
| Subject Terms: | *Basic writing (Remedial education), *Composition (Language arts), *Fluency (Language learning), *Outcome-based education, Keyboarding |
| Abstract: | Abstract: The goal of this study is to model pauses extracted from writing keystroke logs as a way of characterizing the processes students use in essay composition. Low‐level timing data were modeled, the interkey interval and its subtype, the intraword duration, thought to reflect processes associated with keyboarding skills and composition fluency. Heavy‐tailed probability distributions (lognormal and stable distributions) were fit to individual students' data. Both density functions fit reasonably well, and estimated parameters were found to be robust across prompts designed to assess student proficiency for the same writing purpose. In addition, estimated parameters for both density functions were statistically significantly associated with human essay scores after accounting for total time spent writing the essay, a result consistent with cognitive theory on the role of low‐level processes in writing. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Educational Measurement is the property of Wiley-Blackwell 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: 129956127 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Modeling Basic Writing Processes From Keystroke Logs. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Guo%2C+Hongwen%22">Guo, Hongwen</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Deane%2C+Paul+D%2E%22">Deane, Paul D.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22van+Rijn%2C+Peter+W%2E%22">van Rijn, Peter W.</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Mo%22">Zhang, Mo</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Bennett%2C+Randy+E%2E%22">Bennett, Randy E.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Educational+Measurement%22">Journal of Educational Measurement</searchLink>. Summer2018, Vol. 55 Issue 2, p194-216. 23p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Basic+writing+%28Remedial+education%29%22">Basic writing (Remedial education)</searchLink><br />*<searchLink fieldCode="DE" term="%22Composition+%28Language+arts%29%22">Composition (Language arts)</searchLink><br />*<searchLink fieldCode="DE" term="%22Fluency+%28Language+learning%29%22">Fluency (Language learning)</searchLink><br />*<searchLink fieldCode="DE" term="%22Outcome-based+education%22">Outcome-based education</searchLink><br /><searchLink fieldCode="DE" term="%22Keyboarding%22">Keyboarding</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract: The goal of this study is to model pauses extracted from writing keystroke logs as a way of characterizing the processes students use in essay composition. Low‐level timing data were modeled, the interkey interval and its subtype, the intraword duration, thought to reflect processes associated with keyboarding skills and composition fluency. Heavy‐tailed probability distributions (lognormal and stable distributions) were fit to individual students' data. Both density functions fit reasonably well, and estimated parameters were found to be robust across prompts designed to assess student proficiency for the same writing purpose. In addition, estimated parameters for both density functions were statistically significantly associated with human essay scores after accounting for total time spent writing the essay, a result consistent with cognitive theory on the role of low‐level processes in writing. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Educational Measurement is the property of Wiley-Blackwell 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=129956127 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/jedm.12172 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 194 Subjects: – SubjectFull: Basic writing (Remedial education) Type: general – SubjectFull: Composition (Language arts) Type: general – SubjectFull: Fluency (Language learning) Type: general – SubjectFull: Outcome-based education Type: general – SubjectFull: Keyboarding Type: general Titles: – TitleFull: Modeling Basic Writing Processes From Keystroke Logs. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Guo, Hongwen – PersonEntity: Name: NameFull: Deane, Paul D. – PersonEntity: Name: NameFull: van Rijn, Peter W. – PersonEntity: Name: NameFull: Zhang, Mo – PersonEntity: Name: NameFull: Bennett, Randy E. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Summer2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 00220655 Numbering: – Type: volume Value: 55 – Type: issue Value: 2 Titles: – TitleFull: Journal of Educational Measurement Type: main |
| ResultId | 1 |
