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Improving Student Outcomes through Adaptive Learning Platforms: Experimental Evidence from the Dominican Republic 2023-2024
Baseline, Midline, and Endline Surveys

Dominican Republic, 2023 - 2024
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Reference ID
DOM_2023-2024_CALIE_v01_M
Producer(s)
Carolina Lopez, Astrid Pineda
Collection(s)
Development Research Microdata
Metadata
DDI/XML JSON
Created on
Jul 15, 2026
Last modified
Jul 15, 2026
Page views
3269
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  • Identification
  • Version
  • Coverage
  • Producers and sponsors
  • Sampling
  • Survey instrument
  • Data collection
  • Data Access
  • Disclaimer and copyrights
  • Contacts
  • Metadata production

    • Identification

    Survey ID number

    DOM_2023-2024_CALIE_v01_M
    Title

    Improving Student Outcomes through Adaptive Learning Platforms: Experimental Evidence from the Dominican Republic 2023-2024
    Subtitle

    Baseline, Midline, and Endline Surveys
    Abbreviation or Acronym

    CALIE 2023-24
    Country/Economy
    Name Country code
    Dominican Republic DOM
    Series Information

    This dataset accompanies the paper "Improving Student Outcomes through Adaptive Learning Platforms: Experimental Evidence from the Dominican Republic" (Lopez & Pineda). The data come from a randomized controlled trial conducted in 9 public secondary schools in the Dominican Republic during the 2023–2024 school year. The study evaluated the impact of integrating computer-adaptive learning (CAL) technology into regular mathematics instruction for ninth-grade students across 38 classrooms. A second randomization assigned small-group tutoring to academically at-risk students in treated classrooms. The dataset includes student-level baseline, midline, and endline survey data, administrative records (grades, attendance, dropout), and platform usage data. Pre-registered as AEARCTR-0012383; IRB protocol 24-444 (Teachers College Columbia University).
    Abstract
    Most students in developing countries receive grade-level instruction despite lacking prerequisite skills, widening learning gaps. To address this mismatch, we conducted a randomized controlled trial integrating computer-adaptive learning (CAL) technology into regular classroom instruction for ninth-grade students in the Dominican Republic. We replaced two of seven weekly mathematics hours with an adaptive software that adapts to individual skill levels. CAL improved test scores by 0.28-0.31 standard deviations. However, we find no evidence that adding small-group tutoring enhanced these benefits; if anything, classrooms assigned to receive both interventions showed smaller gains than those receiving CAL alone, though this difference is not statistically significant. We document implementation challenges and explore potential mechanisms, including reduced platform engagement in tutoring classrooms. These results suggest computer-adaptive learning software can be effectively integrated into classroom instruction to improve learning, but combining multiple interventions may produce unintended behavioral responses that diminish their effectiveness.
    Kind of Data

    Sample survey data [ssd]
    Unit of Analysis

    Students

    Version

    Version Description

    This dataset accompanies the paper "Improving Student Outcomes through Adaptive Learning Platforms: Experimental Evidence from the Dominican Republic" (Lopez & Pineda). The data come from a randomized controlled trial conducted in 9 public secondary schools in the Dominican Republic during the 2023–2024 school year. The study evaluated the impact of integrating computer-adaptive learning (CAL) technology into regular mathematics instruction for ninth-grade students across 38 classrooms. A second randomization assigned small-group tutoring to academically at-risk students in treated classrooms. The dataset includes student-level baseline, midline, and endline survey data, administrative records (grades, attendance, dropout), and platform usage data. Pre-registered as AEARCTR-0012383; IRB protocol 24-444 (Teachers College Columbia University).

    Coverage

    Geographic Coverage

    Urban
    Universe

    Ninth-grade students enrolled in public secondary schools in Santo Domingo and Santiago, Dominican Republic, during the 2023–2024 school year. Schools were selected based on having an active computer lab, reliable electricity and internet access, an extended-day format, and at least three ninth-grade classrooms. The sample comprises 38 classrooms across 9 schools.

    Producers and sponsors

    Primary investigators
    Name Affiliation
    Carolina Lopez Development Research Group, World Bank
    Astrid Pineda World Bank Group
    Funding Agency/Sponsor
    Name Abbreviation Role
    Tinker Foundation Primary Founder
    Institute of Education Sciences, U.S. Department of Education IES

    Sampling

    Sampling Procedure

    The study sample was not drawn through probability sampling. Schools were selected purposively based on four criteria: (1) having an active computer lab, (2) reliable electricity and internet access, (3) an extended-day school format, and (4) at least three ninth-grade classrooms, with prior participation in the ALEKS platform program. All eligible ninth-grade classrooms within selected schools were included. Treatment was assigned through a two-stage pairwise randomization at the classroom level: classrooms were ranked by size, paired, and one classroom per pair was randomly assigned to the CAL treatment. Within the CAL group, the same procedure was repeated to assign the tutoring component.

    Survey instrument

    Questionnaires

    Baseline Student Survey (Spanish, Baseline); Baseline Teacher Survey (Spanish, Baseline); Baseline School Survey (Spanish, Baseline); Baseline Tutor Survey (Spanish, Baseline); Midline Student Survey (Spanish, Midline); Midline Math Test (Spanish, Midline); Endline Student Survey (English, Endline); Endline Teacher Survey (English, Endline); Endline Principal Survey (English, Endline); Endline Tutor Survey (English, Endline); Endline Math Test (English, Endline)

    Data collection

    Dates of Data Collection
    Start End Cycle
    2023-09-01 2023-09-30 Baseline
    2023-12-01 2023-12-31 Midline
    2024-05-01 2024-09-30 Endline

    Data Access

    Access authority
    Name Affiliation Email
    Carolina Lopez Development Research Group, World Bank carolina_lopez@worldbank.or
    Astrid Pineda World Bank apineda@worldbank.org
    Confidentiality
    Is signing of a confidentiality declaration required? Confidentiality declaration text
    yes The data were collected under IRB protocol 24-444 approved by the Teachers College Columbia University Institutional Review Board. All participants provided informed consent. Data have been de-identified: names and direct identifiers have been removed. The data contain information on minors (ninth-grade students, approximately 14–16 years of age) and must be treated accordingly.
    Access conditions

    Access to this dataset requires signing a Data Use Agreement (DUA) with the authors. Users may not attempt to re-identify study participants, share the data with third parties, or use the data for purposes other than research. Publications using these data must acknowledge the original study and cite the accompanying paper.
    Citation requirements

    Lopez, Carolina and Astrid Pineda. "Improving Student Outcomes through Adaptive Learning Platforms: Experimental Evidence from the Dominican Republic." Working paper.

    Disclaimer and copyrights

    Disclaimer

    The user of the data acknowledges that the original collectors of the data, the authorized distributors of the data, and the relevant funding agencies bear no responsibility for use of the data or for interpretations or inferences based upon such uses. The findings, interpretations, and conclusions expressed in any work using this dataset are entirely those of the authors and do not necessarily represent the views of the World Bank, its affiliated organizations, or the governments they represent.

    Contacts

    Contacts
    Name Affiliation Email
    Carolina Lopez Development Research Group, World Bank carolina_lopez@worldbank.org
    Astrid Pineda World Bank apineda@worldbank.org

    Metadata production

    DDI Document ID

    DDI_DOM_2023-2024_CALIE_v01_M
    Producers
    Name Abbreviation Affiliation Role
    Development Data Group DECDG World Bank Group Documentation of the survey

    Metadata version

    DDI Document version

    Version 01 (July 2026)
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