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Development and validation of a rapid and precise online sentence reading efficiency assessment.

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Title: Development and validation of a rapid and precise online sentence reading efficiency assessment.
Authors: Yeatman, Jason D.1,2,3 (AUTHOR) jyeatman@stanford.edu, Tran, Jasmine E.1,3 (AUTHOR), Burkhardt, Amy K.4 (AUTHOR), Ma, Wanjing Anya1 (AUTHOR), Mitchell, Jamie L.1,2 (AUTHOR), Yablonski, Maya1,3 (AUTHOR), Gijbels, Liesbeth5 (AUTHOR), Townley-Flores, Carrie1 (AUTHOR), Richie-Halford, Adam1,3 (AUTHOR)
Source: Frontiers in Education. 2024, p1-14. 14p.
Subject Terms: *Artificial intelligence, *Silent reading, *Test validity, *Dyslexia, Psychometrics
Abstract: Introduction: The speed at which students can accurately read and understand connected text is at the foundation of reading development. Timed reading measures go under a variety of names (e.g., reading fluency, reading efficiency, etc) and involve different levels of demands on comprehension, making it hard to interpret the extent to which scores reflect differences in reading efficiency versus comprehension. Methods: Here we define a new measure of silent sentence reading efficiency (SRE) and explore key aspects of item development for an unproctored, online SRE assessment (ROAR-SRE). In doing so, we set forth an argument for developing sentences that are simple assertions, with an unambiguous answer, requiring minimal background knowledge and vocabulary. We then run a large-scale validation study to document convergent validity between ROAR-SRE and other measures of reading. Finally we validate the reliability and accuracy of using artificial intelligence (AI) to generate matched test forms. Results: We find that a short, one-minute SRE assessment is highly correlated with other reading measures and has exceptional reliability. Moreover, AI can automatically generate test forms that are matched to manually-authored test forms. Discussion: Together these results highlight the potential for regular screening and progress monitoring at scale with ROAR-SRE. [ABSTRACT FROM AUTHOR]
Copyright of Frontiers in Education is the property of Frontiers Media S.A. 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
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DbLabel: Education Research Complete
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PubType: Academic Journal
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  Data: Development and validation of a rapid and precise online sentence reading efficiency assessment.
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  Data: <searchLink fieldCode="AR" term="%22Yeatman%2C+Jason+D%2E%22">Yeatman, Jason D.</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> jyeatman@stanford.edu</i><br /><searchLink fieldCode="AR" term="%22Tran%2C+Jasmine+E%2E%22">Tran, Jasmine E.</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Burkhardt%2C+Amy+K%2E%22">Burkhardt, Amy K.</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ma%2C+Wanjing+Anya%22">Ma, Wanjing Anya</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mitchell%2C+Jamie+L%2E%22">Mitchell, Jamie L.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yablonski%2C+Maya%22">Yablonski, Maya</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gijbels%2C+Liesbeth%22">Gijbels, Liesbeth</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Townley-Flores%2C+Carrie%22">Townley-Flores, Carrie</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Richie-Halford%2C+Adam%22">Richie-Halford, Adam</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Frontiers+in+Education%22">Frontiers in Education</searchLink>. 2024, p1-14. 14p.
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  Data: Introduction: The speed at which students can accurately read and understand connected text is at the foundation of reading development. Timed reading measures go under a variety of names (e.g., reading fluency, reading efficiency, etc) and involve different levels of demands on comprehension, making it hard to interpret the extent to which scores reflect differences in reading efficiency versus comprehension. Methods: Here we define a new measure of silent sentence reading efficiency (SRE) and explore key aspects of item development for an unproctored, online SRE assessment (ROAR-SRE). In doing so, we set forth an argument for developing sentences that are simple assertions, with an unambiguous answer, requiring minimal background knowledge and vocabulary. We then run a large-scale validation study to document convergent validity between ROAR-SRE and other measures of reading. Finally we validate the reliability and accuracy of using artificial intelligence (AI) to generate matched test forms. Results: We find that a short, one-minute SRE assessment is highly correlated with other reading measures and has exceptional reliability. Moreover, AI can automatically generate test forms that are matched to manually-authored test forms. Discussion: Together these results highlight the potential for regular screening and progress monitoring at scale with ROAR-SRE. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Frontiers in Education is the property of Frontiers Media S.A. 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=181927086
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              Text: 2024
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