About

Paulo Blikstein is an associate professor at Teachers College, Columbia University, where he directs the Transformative Learning Technologies Lab. His research focuses on how new technologies can deeply transform the learning of science, engineering, and mathematics. He creates and researches cutting-edge educational technologies, such as computer modeling, robotics, digital fabrication, and rapid prototyping, to develop hands-on learning environments in which children learn science and mathematics by building sophisticated projects and devices. Additionally, he applies data-mining and machine learning techniques for the assessment of hands-on, project-based learning. Blikstein has spearheaded initiatives like the FabLearn project, which involves building advanced digital fabrication labs in middle and high schools across four continents. He was also the Founder and Principal Investigator of the Lemann Center for Brazilian Education at Stanford, a decade-long initiative aimed at transforming public education in Brazil. His professional experience includes a position at Stanford University from 2008 to 2018, where he served as an Assistant Professor of Education and Computer Science, and as the Director of the Transformative Learning Technologies Lab and the Lemann Center for Educational Innovation in Brazil. His scholarly interests encompass technology in teaching and learning, computer modeling in social and behavioral sciences, science and mathematics education, and active engagement with professional organizations dedicated to educational data mining, learning analytics, and STEM education.

Research topics

• Computer Science
• Sociology
• Engineering
• Engineering ethics
• Pedagogy
• Political Science
• Psychology
• Artificial Intelligence
• Humanities
• Mathematics education
• Management science
• Data science
• Philosophy
• Mathematics
• Knowledge management
• Public relations
• Human–computer interaction

Selected publications

• Unpacking Blocks in Domain-Specific Modeling Environments to Support Science and Computing Learning

  2026-02-13

  articleOpen accessSenior author

  Programming computational models is a key practice that supports both scientific and computational learning. Block-based, domain-specific programming environments have made this practice more accessible but may constrain what students can design compared to general-purpose or text-based languages. This poster reports on the classroom use of block unpacking—a feature that allows high-level primitives to be opened, inspected, and modified—within a domain-specific modeling environment. We implemented unpacking in a four-day high school biology unit on eutrophication, where students programmed models to represent interactions among algae, bacteria, fish, nutrients, and oxygen. From the 16 students who participated, we analyzed 36 unpacking modifications made by five focal students, classifying each as a parameter change or a code structure change, and examining whether these modifications were informed by scientific reasoning. Our findings show that unpacking let students move beyond fixed domain-specific primitives, producing diverse and more expressive models. Some introduced new mechanisms, such as photosynthesis, while others focused on optimizing or debugging simulations. Importantly, more complex edits did not always correspond to deeper scientific reasoning. This study highlights unpacking as a mid-level design strategy that can expand student agency and flexibility in block-based modeling. We discuss implications for designing programming environments and instructional supports that balance ease of entry with opportunities to engage meaningfully in computing practices.

  PublisherDOI

• Modality Matters: Exploring and Capturing Students’ Mechanistic Reasoning During Computational Modeling in Science Education

  Contributions from science education research · 2026-01-01

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  PublisherDOI

• Designing MoDa: A new tool for science learning through data-based computational modeling

  International Journal of Child-Computer Interaction · 2026-04-03

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  PublisherDOI

• Anchoring Computing in Social Studies Through Co-Designed Objects-to-Think-With

  2026-02-13

  articleOpen accessSenior author

  Brazil has recently advanced efforts to integrate computing into K-12 education through new national standards. This movement creates opportunities but also raises challenges about how computing can connect meaningfully to other subjects. One promising approach is to design learning experiences where students build computational artifacts to reason about disciplinary concepts. This poster reports early results from a multi-year collaboration with Brazilian teachers to integrate computing into middle-school History and Geography. Through co-design sessions and classroom trials with more than 20 teachers, we explored ways to enrich disciplinary inquiry while keeping computing aligned with local curriculum goals. A key outcome is the identification of four ''objects-to-think-with'' — tangible artifacts that anchor social studies concepts and computing practices. These include computational graphs to compare historical revolts, interactive maps for testing alternative regionalizations of the Americas, a classroom meteorological station for monitoring local climate data, and interactive chatbots that present reimagined medieval timelines. Each object bridges disciplinary reasoning with computing ideas such as modeling, data representation, and visualization. We outline the co-design process that led to these objects and illustrate their classroom use, offering a practical strategy for teachers seeking to implement Brazil's new computing standards in authentic ways.

  PublisherDOI

• What is Data? Youths’ Conceptualizations and Criteria within a Project-Based Data Science Camp

  Proceedings. · 2025-06-10

  articleOpen accessSenior author

  Data is ubiquitous in young people's daily lives, yet its meaning and purpose are continually changing in relation to context, infrastructure, and intent.In this pilot study, we explore five 11-to 12-year olds' conceptualizations and criteria for what makes something "data."Analyzing semi-structured interviews as part of an embedded assessment where young people were presented with five different data visualizations, we find shifts and consistencies in their conceptualizations and criteria for including or excluding something as data, elevating the attributes of the data (numeracy, increasing volume) and the inferred intents of data producers (related to collection practices and purported purpose) in their decision making.These findings point to the complexity of defining data's properties and functionalities and the need to develop taken-as-shared expectations and definitions of what data is and can be within educational contexts among youth, researchers, and educators.

  PublisherOA PDFDOI

• Towards a Learning Sciences-Informed Framework for Investigating “Twisted” Knowledge Construction on Social Media

  Proceedings. · 2025-06-10

  articleOpen accessSenior author

  This paper proposes a framework to investigate a phenomenon we term twisted knowledge construction on social media from a Learning Sciences perspective.We first analyze and then draw connections between literature from four fields of scholarship, with varying levels of connection to the Learning Sciences: social media from the perspective of Internet and Communication Studies; foundational theories of learning; social media as contexts for learning; and epistemic cognition with an emphasis on emotions.We articulate these connections as a loop-like system supported by the socio-technical affordances of social media.This system is fueled by ideologically motivated content and interactions that shape knowledge construction, whose affective and repertoire-based outcomes loop back into itself, leading to a cycle of distorted knowledge construction.Considerations for future research are proposed from a Learning Sciences perspective.

  PublisherOA PDFDOI

• Datafying Spaces and Places: Synergies and Disconnects between Youth-Authored Maps and Data Visualizations

  Proceedings. · 2025-06-10

  articleOpen accessSenior author

  Research on informal learning often elevates the knowledge that youth develop in their daily interactions, relationships, and movement across their homes and communities.Youth-authored geographies -whether in drawings, maps, or photographs -offer one rich perspective into this knowledge.We extend analytic techniques developed for youth geographies to another kind of youth-authored representation: data visualizations.Specifically, we use Davis and Barsoum's (2022) framework to identify ways that the spatial/temporal layers, hierarchies, relationships, and rhythms of phenomena that youth elevate within their communities are reflected or obscured within visualizations they create of sensor data collected in those spaces.We also emphasize annotations as a powerful tool for youth to surface these elements.We propose that awareness of these synergies and disconnects could inform data science education that leverages youth's everyday knowledge.

  PublisherOA PDFDOI

• Authorship Networks in Learning Sciences Research on Disinformation, Data Science, and Social Media

  Proceedings. · 2025-06-10

  articleOpen accessSenior author

  We present a pilot study examining three years of conference papers in the proceedings of the International Society of the Learning Sciences (ISLS) Annual Meetings from 2022 to 2024 to explore the connections and collaborations among authors in three fields of investigation: data science instruction, misinformation/disinformation, and social media.We found initial evidence of a cyclical pattern indicating that at times, sub-communities collaborate, while at other times, they operate more independently in isolation.

  PublisherOA PDFDOI

• A Multi-Method Approach for Exploring Programming Trajectories Through Log Data: Insights from Data Visualization Tasks

  Journal of Science Education and Technology · 2025-04-10 · 1 citations

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  PublisherDOI

• Taking on “Big Problems”: Spatial Scales in Youth Work at a Data Science Camp

  Proceedings. · 2025-06-10

  articleOpen accessSenior author

  Data science education (DSE) has recently gained increased attention.We present a framework for analyzing youth-authored community data science investigations and illustrate our framework with case studies demonstrating the benefits of scaffolding learners' trajectories across spatial scales.Our findings suggest that "sliding" between personal, community, and global scales supports reasoning about complex problems, offering insights for educators to support youth in tackling "big problems" and making sense of their world through data.

  PublisherOA PDFDOI

Recent grants

• CAREER: Bifocal Modeling: A New Famework for the Learning of Advanced STEM Content in High-school

  NSF · $629k · 2011–2018

• From Access to Sustainability: Investigating Ways to Foster Sustainable Use of Computational Modeling in K-12 Science Classrooms

  NSF · $2.0M · 2020–2025

Frequent coauthors

• Marcelo Worsley

  30 shared

• Tamar Fuhrmann

  Columbia University

  28 shared

• Uri Wilensky

  Northwestern University

  23 shared

• Engin Bumbacher

  20 shared

• Bertrand Schneider

  17 shared

• Leah F. Rosenbaum

  Columbia University

  17 shared

• C. Patrick Proctor

  Boston College

  16 shared

• Cassia Fernandez

  Columbia University

  15 shared

Labs

• Transformative Learning Technologies LabPI

Education

• B.S., Metallurgical Engineering

  University of São Paulo (Brazil)

  1998

• Other, Electronic Engineering

  University of São Paulo (Brazil)

  2000

• M.S., Media Arts & Sciences

  MIT Media Lab, Future of Learning Group

  2002

• Ph.D., Learning Sciences

  Northwestern University

  2009

Awards & honors

• 2016 - AERA Div. C Jan Hawkins Early Career Award
• 2015 - Dean’s Distinguished Visiting Fellow, Harvard Graduat…
• 2011 - NSF CAREER Award: “Bifocal modeling: a new approach f…