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Applying the Virtual-Representational-Abstract Integrated Instructional Sequence to Teaching Subtraction with Regrouping.

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Title: Applying the Virtual-Representational-Abstract Integrated Instructional Sequence to Teaching Subtraction with Regrouping.
Authors: Bouck, Emily C.1 ecb@msu.edu, Long, Holly1, Harris, Megan1, Whorley, Abby
Source: Education & Training in Autism & Developmental Disabilities. Mar2024, Vol. 59 Issue 1, p45-58. 14p.
Subject Terms: *Middle school students, *Research personnel, *Developmental disabilities, *Intellectual disabilities, *Problem solving
Abstract: Researchers determined virtual manipulatives, on their own or as part of an instructional sequence, to be an evidence-based practice for students with intellectual and developmental disabilities (IDD; Long et al., 2022). Yet, the majority of research looking at virtual manipulative-based instructional sequences involves the phases learned in a specific order rather than an integrated fashion, which researchers suggested may be more effective and efficient (Root et al., 2021; Strickland & Maccini, 2012). This single-case design study explored use of the virtual-representational-abstract integrated (VRI) instructional sequence to teach three middle school students with IDD to solve computational subtraction with regrouping problems. Researchers found a functional relation between the intervention package of the VRA-I instructional sequence and corrective feedback for incorrect probe answers and student accuracy. Researchers also found mixed results for each student with regards to generalization to solving word problems involving subtraction with regrouping. [ABSTRACT FROM AUTHOR]
Copyright of Education & Training in Autism & Developmental Disabilities is the property of Council for Exceptional Children, Division on Autism & Developmental Disabilities 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: Applying the Virtual-Representational-Abstract Integrated Instructional Sequence to Teaching Subtraction with Regrouping.
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  Data: <searchLink fieldCode="JN" term="%22Education+%26+Training+in+Autism+%26+Developmental+Disabilities%22">Education & Training in Autism & Developmental Disabilities</searchLink>. Mar2024, Vol. 59 Issue 1, p45-58. 14p.
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  Data: Researchers determined virtual manipulatives, on their own or as part of an instructional sequence, to be an evidence-based practice for students with intellectual and developmental disabilities (IDD; Long et al., 2022). Yet, the majority of research looking at virtual manipulative-based instructional sequences involves the phases learned in a specific order rather than an integrated fashion, which researchers suggested may be more effective and efficient (Root et al., 2021; Strickland & Maccini, 2012). This single-case design study explored use of the virtual-representational-abstract integrated (VRI) instructional sequence to teach three middle school students with IDD to solve computational subtraction with regrouping problems. Researchers found a functional relation between the intervention package of the VRA-I instructional sequence and corrective feedback for incorrect probe answers and student accuracy. Researchers also found mixed results for each student with regards to generalization to solving word problems involving subtraction with regrouping. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Education & Training in Autism & Developmental Disabilities is the property of Council for Exceptional Children, Division on Autism & Developmental Disabilities 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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              Text: Mar2024
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