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The Feasibility of Technology to Support Data-Driven Decision Making in Early Head Start Classrooms

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Title: The Feasibility of Technology to Support Data-Driven Decision Making in Early Head Start Classrooms
Language: English
Authors: Rebecca E. Davis (ORCID 0000-0003-3430-4515), Jay Buzhardt, Dale Walker, Dwight W. Irvin, Susan Higgins, Yagmur Seven, Charles R. Greenwood
Source: Journal of Special Education Technology. 2026 41(1):16-29.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 14
Publication Date: 2026
Sponsoring Agency: Institute of Education Sciences (ED)
Contract Number: R324A170141
Document Type: Journal Articles
Reports - Research
Education Level: Early Childhood Education
Descriptors: Technology Uses in Education, Evidence Based Practice, Decision Making, Social Services, Early Intervention, Federal Programs, Early Childhood Teachers, Early Childhood Education, Progress Monitoring, Infants, Toddlers, Educational Technology
Laws, Policies and Program Identifiers: Early Head Start
DOI: 10.1177/01626434251317982
ISSN: 0162-6434
2381-3121
Abstract: Educators have struggled to implement research-based practices effectively, particularly in early childhood settings where data-driven decision making (DDDM) is important for guiding practice. Implementation of DDDM is hindered by a lack of progress monitoring assessments, guidelines for how to use data to inform intervention decisions, and professional development for educators. To address these challenges, tools like the Individual Growth and Development Indicators (IGDIs) and the Making Online Decisions (MOD) system have been developed, demonstrating significant benefits in enhancing education outcomes when used effectively. The purpose of this study was to investigate the feasibility of the MOD to enhance DDDM for young children performing below benchmark in Early Head Start. Findings indicated that the MOD increased the frequency of progress monitoring, high implementation fidelity, and sustainability after research support was discontinued. Educator satisfaction was generally high, but suggestions were made for improvements. Limitations, implications for practice, and future directions are discussed.
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2026
Accession Number: EJ1496890
Database: ERIC
FullText Text:
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  Data: The Feasibility of Technology to Support Data-Driven Decision Making in Early Head Start Classrooms
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  Data: <searchLink fieldCode="AR" term="%22Rebecca+E%2E+Davis%22">Rebecca E. Davis</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3430-4515">0000-0003-3430-4515</externalLink>)<br /><searchLink fieldCode="AR" term="%22Jay+Buzhardt%22">Jay Buzhardt</searchLink><br /><searchLink fieldCode="AR" term="%22Dale+Walker%22">Dale Walker</searchLink><br /><searchLink fieldCode="AR" term="%22Dwight+W%2E+Irvin%22">Dwight W. Irvin</searchLink><br /><searchLink fieldCode="AR" term="%22Susan+Higgins%22">Susan Higgins</searchLink><br /><searchLink fieldCode="AR" term="%22Yagmur+Seven%22">Yagmur Seven</searchLink><br /><searchLink fieldCode="AR" term="%22Charles+R%2E+Greenwood%22">Charles R. Greenwood</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Special+Education+Technology%22"><i>Journal of Special Education Technology</i></searchLink>. 2026 41(1):16-29.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: 14
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  Data: <searchLink fieldCode="EL" term="%22Early+Childhood+Education%22">Early Childhood Education</searchLink>
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  Data: <searchLink fieldCode="SU" term="%22Early+Head+Start%22">Early Head Start</searchLink>
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  Data: 10.1177/01626434251317982
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  Data: 0162-6434<br />2381-3121
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  Label: Abstract
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  Data: Educators have struggled to implement research-based practices effectively, particularly in early childhood settings where data-driven decision making (DDDM) is important for guiding practice. Implementation of DDDM is hindered by a lack of progress monitoring assessments, guidelines for how to use data to inform intervention decisions, and professional development for educators. To address these challenges, tools like the Individual Growth and Development Indicators (IGDIs) and the Making Online Decisions (MOD) system have been developed, demonstrating significant benefits in enhancing education outcomes when used effectively. The purpose of this study was to investigate the feasibility of the MOD to enhance DDDM for young children performing below benchmark in Early Head Start. Findings indicated that the MOD increased the frequency of progress monitoring, high implementation fidelity, and sustainability after research support was discontinued. Educator satisfaction was generally high, but suggestions were made for improvements. Limitations, implications for practice, and future directions are discussed.
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  Data: 2026
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  Data: EJ1496890
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        Value: 10.1177/01626434251317982
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      – Text: English
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        PageCount: 14
        StartPage: 16
    Subjects:
      – SubjectFull: Technology Uses in Education
        Type: general
      – SubjectFull: Evidence Based Practice
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      – SubjectFull: Decision Making
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      – SubjectFull: Social Services
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      – SubjectFull: Early Head Start
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      – TitleFull: The Feasibility of Technology to Support Data-Driven Decision Making in Early Head Start Classrooms
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