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Classroom-Based Experimentation in a Digital Learning Platform

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Title: Classroom-Based Experimentation in a Digital Learning Platform
Language: English
Authors: April Murphy, Digital Promise, Empirical Education Inc., Institute of Education Sciences (ED)
Source: Digital Promise. 2026.
Availability: Digital Promise. 1001 Connecticut Avenue NW Suite 935, Washington DC 20036. Tel: 202-450-3675; e-mail: contact@digitalpromise.org; Web site: https://digitalpromise.org/
Peer Reviewed: N
Page Count: 13
Publication Date: 2026
Document Type: Reports - Evaluative
Education Level: Elementary Education
Grade 6
Intermediate Grades
Middle Schools
Grade 7
Junior High Schools
Secondary Education
Grade 8
Descriptors: Electronic Learning, Educational Technology, Technology Uses in Education, Educational Research, Mathematics Education, Grade 6, Grade 7, Grade 8, Mathematics Instruction, Classroom Environment, Intervention, Educational Experiments
Geographic Terms: Delaware, South Dakota, Texas
Abstract: Educational research often struggles to balance laboratory-style control with the real-world scale of authentic classrooms. This paper explores how classroom-embedded, digitally integrated experimentation addresses this tension by generating actionable evidence directly within digital learning environments. Using Carnegie Learning's MATHia intelligent tutoring system alongside UpGrade--an open-source A/B testing platform--the author highlights three diverse field trials encompassing nearly 100 experiments and hundreds of thousands of students. These include an XPRIZE study on localized personalization, an IES-funded reading readability initiative leveraging Large Language Models (LLMs), and an ongoing project evaluating targeted metacognitive prompts. From these large-scale applications, three foundational insights emerge for optimizing digital education research: seamlessly weaving interventions into daily instruction to eliminate teacher burden, capturing real-time learning metrics through intrinsic system-generated data, and prioritizing small, theory-driven manipulations to isolate specific cognitive mechanisms. While logistical constraints like sequence-dependent timing and varying state curricula present ongoing challenges, the paper concludes that embedding rigorous, focused experiments into adaptive software offers a scalable, non-disruptive framework. This approach simultaneously advances learning science theory and drives iterative, evidence-based development in educational technology.
Abstractor: As Provided
IES Funded: Yes
Entry Date: 2026
Accession Number: ED682372
Database: ERIC
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=ED682372
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PubType: Report
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  Data: Classroom-Based Experimentation in a Digital Learning Platform
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  Data: <searchLink fieldCode="AR" term="%22April+Murphy%22">April Murphy</searchLink><br /><searchLink fieldCode="AR" term="%22Digital+Promise%22">Digital Promise</searchLink><br /><searchLink fieldCode="AR" term="%22Empirical+Education+Inc%2E%22">Empirical Education Inc.</searchLink><br /><searchLink fieldCode="AR" term="%22Institute+of+Education+Sciences+%28ED%29%22">Institute of Education Sciences (ED)</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Digital+Promise%22"><i>Digital Promise</i></searchLink>. 2026.
– Name: Avail
  Label: Availability
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  Data: Digital Promise. 1001 Connecticut Avenue NW Suite 935, Washington DC 20036. Tel: 202-450-3675; e-mail: contact@digitalpromise.org; Web site: https://digitalpromise.org/
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  Label: Peer Reviewed
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  Data: N
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  Label: Page Count
  Group: Src
  Data: 13
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  Label: Publication Date
  Group: Date
  Data: 2026
– Name: TypeDocument
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  Data: Reports - Evaluative
– Name: Audience
  Label: Education Level
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  Data: <searchLink fieldCode="EL" term="%22Elementary+Education%22">Elementary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Grade+6%22">Grade 6</searchLink><br /><searchLink fieldCode="EL" term="%22Intermediate+Grades%22">Intermediate Grades</searchLink><br /><searchLink fieldCode="EL" term="%22Middle+Schools%22">Middle Schools</searchLink><br /><searchLink fieldCode="EL" term="%22Grade+7%22">Grade 7</searchLink><br /><searchLink fieldCode="EL" term="%22Junior+High+Schools%22">Junior High Schools</searchLink><br /><searchLink fieldCode="EL" term="%22Secondary+Education%22">Secondary Education</searchLink><br /><searchLink fieldCode="EL" term="%22Grade+8%22">Grade 8</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Electronic+Learning%22">Electronic Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Technology%22">Educational Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Research%22">Educational Research</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematics+Education%22">Mathematics Education</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+6%22">Grade 6</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+7%22">Grade 7</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+8%22">Grade 8</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematics+Instruction%22">Mathematics Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Classroom+Environment%22">Classroom Environment</searchLink><br /><searchLink fieldCode="DE" term="%22Intervention%22">Intervention</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Experiments%22">Educational Experiments</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Delaware%22">Delaware</searchLink><br /><searchLink fieldCode="DE" term="%22South+Dakota%22">South Dakota</searchLink><br /><searchLink fieldCode="DE" term="%22Texas%22">Texas</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Educational research often struggles to balance laboratory-style control with the real-world scale of authentic classrooms. This paper explores how classroom-embedded, digitally integrated experimentation addresses this tension by generating actionable evidence directly within digital learning environments. Using Carnegie Learning's MATHia intelligent tutoring system alongside UpGrade--an open-source A/B testing platform--the author highlights three diverse field trials encompassing nearly 100 experiments and hundreds of thousands of students. These include an XPRIZE study on localized personalization, an IES-funded reading readability initiative leveraging Large Language Models (LLMs), and an ongoing project evaluating targeted metacognitive prompts. From these large-scale applications, three foundational insights emerge for optimizing digital education research: seamlessly weaving interventions into daily instruction to eliminate teacher burden, capturing real-time learning metrics through intrinsic system-generated data, and prioritizing small, theory-driven manipulations to isolate specific cognitive mechanisms. While logistical constraints like sequence-dependent timing and varying state curricula present ongoing challenges, the paper concludes that embedding rigorous, focused experiments into adaptive software offers a scalable, non-disruptive framework. This approach simultaneously advances learning science theory and drives iterative, evidence-based development in educational technology.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
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  Label: IES Funded
  Group: SrcInfo
  Data: Yes
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2026
– Name: AN
  Label: Accession Number
  Group: ID
  Data: ED682372
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=ED682372
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    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
    Subjects:
      – SubjectFull: Electronic Learning
        Type: general
      – SubjectFull: Educational Technology
        Type: general
      – SubjectFull: Technology Uses in Education
        Type: general
      – SubjectFull: Educational Research
        Type: general
      – SubjectFull: Mathematics Education
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      – SubjectFull: Grade 6
        Type: general
      – SubjectFull: Grade 7
        Type: general
      – SubjectFull: Grade 8
        Type: general
      – SubjectFull: Mathematics Instruction
        Type: general
      – SubjectFull: Classroom Environment
        Type: general
      – SubjectFull: Intervention
        Type: general
      – SubjectFull: Educational Experiments
        Type: general
      – SubjectFull: Delaware
        Type: general
      – SubjectFull: South Dakota
        Type: general
      – SubjectFull: Texas
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    Titles:
      – TitleFull: Classroom-Based Experimentation in a Digital Learning Platform
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