Research Portfolio
I believe impactful policy research must: (1) employ rigorous, transparent methods, (2) engage directly with implementation contexts, and (3) produce tools and frameworks that empower decision-makers. My work moves from conceptual frameworks through empirical testing to practical implementation.
Current Research Themes
1. AI in Education: From Policy to Practice
Research Question: How can generative AI and machine learning be responsibly integrated into educational systems to enhance learning while addressing equity concerns?
Methodological Approach:
Experimental design of AI interventions
Natural language processing of educational content
Causal inference methods for impact evaluation
Participatory design with educators and students
Key Contributions:
Developed Ceibal’s first generative AI chatbot for learning support in computational thinking
Created evidence synthesis frameworks for AI policy decisions
Designed monitoring systems for algorithmic fairness in EdTech
2. Gender Equity in STEM Education
Research Question: What systemic and perceptual barriers explain persistent gender gaps in computational thinking and STEM participation, and which interventions effectively address them?
Methodological Approach:
Longitudinal survey analysis with gender-disaggregated data
Experimental studies of teacher perceptions and bias
Network analysis of participation patterns
Meta-analysis of intervention effectiveness
Key Contributions:
Pioneered the “relative risk” metric for quantifying gender gaps across competencies
Developed Uruguay’s first real-time gender equity dashboard for STEM
Created comprehensive knowledge base synthesizing 250+ research documents
3. Digital Capital and EdTech Evaluation
Research Question: How can we move beyond access metrics to measure the actual development of digital capabilities through educational technology programs?
Methodological Approach:
Framework development and validation
Mixed-methods program evaluation
Digital trace data analysis
Cost-effectiveness analysis
Key Contributions:
Developed “Digital Capital” framework adopted for Uruguay’s micro:bit program
Created innovative metrics for technology usage intensity
Designed monitoring systems that connect device usage to learning outcomes
Explore digital capital research →
Methodological Expertise
Quantitative Methods
Causal Inference: RCTs, quasi-experimental designs, difference-in-differences, instrumental variables
Machine Learning: Predictive analytics, NLP, heterogeneous treatment effects
Statistical Modeling: Multilevel modeling, structural equation modeling, missing data analysis
Data Visualization: Interactive dashboards (R Shiny), geospatial analysis, network graphs
Mixed-Methods Approaches
Qualitative Integration: Expert interviews, focus groups, participatory design
Survey Design: Multi-wave longitudinal studies, psychometric validation
Research-Practice Partnerships: Co-design with policymakers and educators
Implementation Science: Fidelity measurement, scaling frameworks
Selected Ongoing Projects
1. Ceibal AI Observatory
Timeline: 2024-2026
Role: Lead Designer and Research Director
Objective: Establish Latin America’s first observatory dedicated to monitoring AI’s impact on education, with special attention to equity dimensions.
Methods: Systematic evidence reviews, NLP of policy documents, experimental pilots, international benchmarking.
2. Gender Bias in Computational Thinking Education
Timeline: 2023-2025 (Longitudinal)
Role: Principal Investigator
Objective: Track evolution of teacher perceptions and gender gaps across Uruguay’s national computational thinking curriculum.
Methods: Multi-wave teacher surveys, student performance data analysis, experimental vignette studies, classroom observations.
3. Digital Capital Measurement Framework
Timeline: 2024-2025
Role: Framework Developer
Objective: Create validated instruments to measure digital capital development across socioeconomic groups.
Methods: Instrument development and validation, factor analysis, measurement invariance testing, predictive validation.
4. Generative AI for Personalized Learning
Timeline: 2024
Role: Research Lead
Objective: Evaluate effectiveness of AI chatbots in supporting diverse learners in computational thinking courses.
Methods: A/B testing, learning analytics, qualitative user feedback analysis, equity impact assessment.
Research Infrastructure & Tools
Data Platforms
Gender & STEM Dashboard: Real-time monitoring of 50+ equity indicators
Evidence Synthesis Platforms: Curated research databases on AI and EdTech
Interactive Knowledge Hubs: Digital publications with embedded analytics
Methodological Resources
R Packages: Custom tools for education data analysis
Survey Instruments: Validated scales for measuring perceptions and outcomes
Analytic Templates: Reproducible workflows for common education research tasks
Capacity Building
Workshop Materials: Training on machine learning, causal inference, and gender analysis
Technical Manuals: Guides for computational reproducibility
Open Educational Resources: Teaching materials for data science in education
International Collaborations & Networks
Research Consortia
- ARC Summit (Wales): Participation in international network on educational equity
Policy Networks
Ceibal Foundation: Research-practice partnership on absenteeism and AI
ANII Uruguay: Evaluation panels for education research funding
Research Impact & Translation
Policy Influence
Direct Policy Input: Research directly informing Uruguay’s education technology strategy
Tool Adoption: Dashboards and frameworks used in Ceibal
Capacity Building
Training Programs: Workshops for teachers on data-driven decision making
Methodological Mentorship: Supporting education researchers in advanced methods
Open Science Advocacy: Promoting transparency and reproducibility in education research
Public Engagement
Media Outreach: Regular contributions to public discourse on education and technology
Stakeholder Workshops: Engaging teachers, parents, and students in research process
Digital Dissemination: Interactive research summaries for broad audiences
Publications by Theme
For detailed publication lists, see:
I welcome collaboration on:
PhD Supervision: Topics in education technology, gender equity, or policy evaluation
Research Partnerships: Joint projects with universities, NGOs, or government agencies
Consulting: Methodological support for complex education evaluations
Speaking Engagements: Workshops on research methods or substantive findings
Contact: robano@gwu.edu
Research updates are posted quarterly. Last updated: December 27, 2025