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Examining Measures and Methods for Determining Students' Responsiveness to Data-Based Early Writing Instruction.

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Title: Examining Measures and Methods for Determining Students' Responsiveness to Data-Based Early Writing Instruction.
Authors: An, Jechun1 (AUTHOR), McMaster, Kristen1 (AUTHOR) mcmas004@umn.edu, Choi, Seohyeon1 (AUTHOR), Bell, Lalinne1 (AUTHOR), Guha, Manjary1 (AUTHOR), Shanahan, Emma2 (AUTHOR), Lembke, Erica3 (AUTHOR)
Source: Scientific Studies of Reading. May/Jun2026, Vol. 30 Issue 3, p277-302. 26p.
Subject Terms: *Curriculum-based assessment, *Self-efficacy in teachers, *Teaching methods, *Emergent literacy, *Special education, *Limited English-proficient students
Abstract: Purpose: We examined approaches to determining students' responsiveness to data-based instruction (DBI) in early writing across methods (final status and growth) and measures (proximal writing curriculum-based measures and a distal standardized writing measure), as well as student- and teacher-level predictors of responsiveness. Method: The analytic sample included 57 teachers and their 131 students (2.5 mean grade-level, 33.6% female, 61.0% White) who (a) were identified as having intensive early writing needs, (b) were enrolled in the treatment condition of a larger randomized control trial and thus participated in early writing DBI, and (c) had available screening, pre- and post-test, and progress monitoring data. We compared the number and percentage of students identified as more or less responsive to 20 weeks of DBI across methods and measures. Then, we examined whether students' responsiveness could be predicted by different student- or teacher-level factors using hierarchical logistic regression. Results: Findings suggested that initial performance was the most consistently significant predictor of students' responsiveness to DBI across the models, and that student factors (special education/English language learner eligibility) and one teacher factor (self-efficacy) sometimes appeared to play a role. Conclusion: Overall, the proportion of more versus less responsive students varied depending on the methods and measures used to determine responsiveness, as did predictors of responsiveness. Implications for selecting measures and methods to identify students' responsiveness to DBI in early writing for further research and practice are discussed. [ABSTRACT FROM AUTHOR]
Copyright of Scientific Studies of Reading is the property of Taylor & Francis Ltd 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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  Data: Examining Measures and Methods for Determining Students' Responsiveness to Data-Based Early Writing Instruction.
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  Data: <searchLink fieldCode="AR" term="%22An%2C+Jechun%22">An, Jechun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22McMaster%2C+Kristen%22">McMaster, Kristen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mcmas004@umn.edu</i><br /><searchLink fieldCode="AR" term="%22Choi%2C+Seohyeon%22">Choi, Seohyeon</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bell%2C+Lalinne%22">Bell, Lalinne</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guha%2C+Manjary%22">Guha, Manjary</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shanahan%2C+Emma%22">Shanahan, Emma</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lembke%2C+Erica%22">Lembke, Erica</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Scientific+Studies+of+Reading%22">Scientific Studies of Reading</searchLink>. May/Jun2026, Vol. 30 Issue 3, p277-302. 26p.
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  Data: *<searchLink fieldCode="DE" term="%22Curriculum-based+assessment%22">Curriculum-based assessment</searchLink><br />*<searchLink fieldCode="DE" term="%22Self-efficacy+in+teachers%22">Self-efficacy in teachers</searchLink><br />*<searchLink fieldCode="DE" term="%22Teaching+methods%22">Teaching methods</searchLink><br />*<searchLink fieldCode="DE" term="%22Emergent+literacy%22">Emergent literacy</searchLink><br />*<searchLink fieldCode="DE" term="%22Special+education%22">Special education</searchLink><br />*<searchLink fieldCode="DE" term="%22Limited+English-proficient+students%22">Limited English-proficient students</searchLink>
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  Data: Purpose: We examined approaches to determining students' responsiveness to data-based instruction (DBI) in early writing across methods (final status and growth) and measures (proximal writing curriculum-based measures and a distal standardized writing measure), as well as student- and teacher-level predictors of responsiveness. Method: The analytic sample included 57 teachers and their 131 students (2.5 mean grade-level, 33.6% female, 61.0% White) who (a) were identified as having intensive early writing needs, (b) were enrolled in the treatment condition of a larger randomized control trial and thus participated in early writing DBI, and (c) had available screening, pre- and post-test, and progress monitoring data. We compared the number and percentage of students identified as more or less responsive to 20 weeks of DBI across methods and measures. Then, we examined whether students' responsiveness could be predicted by different student- or teacher-level factors using hierarchical logistic regression. Results: Findings suggested that initial performance was the most consistently significant predictor of students' responsiveness to DBI across the models, and that student factors (special education/English language learner eligibility) and one teacher factor (self-efficacy) sometimes appeared to play a role. Conclusion: Overall, the proportion of more versus less responsive students varied depending on the methods and measures used to determine responsiveness, as did predictors of responsiveness. Implications for selecting measures and methods to identify students' responsiveness to DBI in early writing for further research and practice are discussed. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Scientific Studies of Reading is the property of Taylor & Francis Ltd 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.)
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        Value: 10.1080/10888438.2026.2618101
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      – SubjectFull: Self-efficacy in teachers
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              Text: May/Jun2026
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              Y: 2026
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