About

Joey Huang is an assistant professor of Learning, Design, & Technology at North Carolina State University. Her academic background includes a Ph.D. in Learning and Developmental Sciences with a minor in Qualitative and Quantitative Research Methodology from Indiana University Bloomington, as well as an M.A. in Educational Psychology from The University of Texas at Austin. Coming from a background in educational psychology and computing, her research focuses on the intersection of the learning sciences, computational thinking, and educational technology. She specializes in designing engaging STEM learning experiences, including AI-enabled educational environments and augmented reality systems for workforce upskilling. Her work emphasizes creating personalized, interactive, and hands-on learning experiences for K–12 and undergraduate students, supporting pathways into STEM fields. Her research investigates collaborative learning, learner motivation and agency, and learning outcomes in technology-enhanced settings, with a particular interest in how learners co-design with AI in STEAM contexts.

Research topics

• Artificial Intelligence
• Computer Science
• Multimedia
• Human–computer interaction
• Computer vision
• Engineering
• Optics
• Operating system
• Simulation
• Mechanical engineering
• Physics

Selected publications

• Humanizing AI for Education: Conversations with the JLS 2026 Special Issue Contributors

  Proceedings. · 2025-06-10 · 1 citations

  articleOpen access

  This symposium will bring together the eight invited contributors for the 2026 special issue of the Journal of the Learning Sciences (JLS), which explores how educational researchers can humanize their designs of AI tools and activities for education.Each contributing author brings a unique perspective on what it means to humanize AI for education, working with different contexts, ages, and learning outcomes.Papers focus on a variety of layers of AI, including designing effective AI tools for learning, understanding how existing AI activities influence the learning process, and developing learners' literacies around ethical AI.In this session, authors will engage with attendees in rich conversations around how we should thoughtfully and ethically design AI futures in the learning sciences that center the needs of teachers, learners, their families, and their communities. Symposium overviewThere is an urgent need to thoughtfully integrate human-centered learning theories into the design and teaching of AI, highlighted by the public conversations occurring in governmental, educational, and industry sectors that seek to establish shared norms for how and why AI tools are used (e.g., The White House, 2023; UNESCO, 2023; Software & Industry Information Association, 2023).At the center of these discussions is a tension between technocentric views of AI that seek to improve the effectiveness and expand the reach of AI innovations and human-centered approaches that instead focus on the ethical, social, and pedagogical aspects of how AI impacts our classrooms and our world (Selwyn, 2024;Akgun & Greenhow, 2022).In this session, eight author teams who

  PublisherOA PDFDOI

• Tangled in Code: Exploring the Intersection of Rope Weaving and Computational Thinking (Poster 30)

  2025-01-01

  article1st authorCorresponding
  PublisherDOI

• BOARD # 289: NSF-Supported DUE: Introducing Robotics through a Weaving-Based Undergraduate Curriculum: Towards Breaking STEM Stereotypes

  2025-08-21

  article
  PublisherDOI

• Progress on clinical optoretinography using dualspectrometer OCT in healthy eyes and eyes with birdshot chorioretinopathy

  2025-12-18

  article
  PublisherDOI

• Weaving Collaboration: Promoting Effective Interdisciplinary Learning with a Robotic Loom

  Computer-supported collaborative learning/˜The œComputer-Supported Collaborative Learning Conference · 2025-06-10

  articleOpen access

  This study investigates the conditions that foster effective interdisciplinary collaboration-defined as the integration of knowledge, practices, and perspectives from different disciplines-through qualitative analysis of project-based learning in higher education.Grounded in theories from the Learning Sciences and Computer-Supported Collaborative Learning, we analyze how knowledge transfer and leadership dynamics mediate interdisciplinary engagement in a course combining robotics, mathematics, and textile arts.Systematic analysis of qualitative data from 23 undergraduate students across six groups reveals three distinct patterns of collaborative engagement.Our findings show that successful collaboration hinges on (1) fluid leadership transitions that leverage diverse expertise and (2) structured opportunities for knowledge exchange.Groups with distributed leadership and consistent knowledge-sharing practices produced higher-quality projects than those with centralized leadership.These findings contribute to theoretical understandings of interdisciplinary learning and offer practical guidelines for designing collaborative learning environments in higher education.

  PublisherOA PDFDOI

• Crafting Computational Thinking with Rope Weaving

  Computer-supported collaborative learning/˜The œComputer-Supported Collaborative Learning Conference · 2025-06-10

  articleOpen access1st authorCorresponding

  This study explores how integrating computational thinking (CT) with weaving can make CT more accessible and engaging.Nineteen undergraduates participated in a rope weaving activity to recreate patterns, test structures, and connect math to tangible materials.Analysis of reflections and video data revealed students applying CT practices like pattern recognition and algorithmic thinking.Findings highlight the value of tactile, craft-based activities in supporting CT learning and bridging abstract concepts with real-world, embodied experiences.

  PublisherOA PDFDOI

• Parsing the Use of Computational Concepts with Scratch Projects

  Computer-supported collaborative learning/˜The œComputer-Supported Collaborative Learning Conference · 2024-06-10 · 1 citations

  articleOpen access1st authorCorresponding

  Studies in learning sciences have examined the learning of computational thinking through project-based learning.The application of computational concepts has been proven to be related to specific project types.Although studies have suggested the value of examining the relationship between computational concepts and project type, few have addressed the nuances regarding how different project types support specific concepts, as well as how educators could use to inform instructional design.This study examined students' group projects to understand how computational concepts associate with specific project types.The implications of the findings inform how educators can better design the instructional and learning objectives to facilitate computational thinking through project-based learning.

  PublisherOA PDFDOI

• Deepening children’s STEM learning through making and creative writing

  International Journal of Child-Computer Interaction · 2024-04-10 · 5 citations

  article1st authorCorresponding
  PublisherDOI

• Weaving with Ropes to Parse Mathematical Abstraction

  Proceedings. · 2024-06-10

  article
  PublisherDOI

• LearnIoTVR: An End-to-End Virtual Reality Environment Providing Authentic Learning Experiences for Internet of Things

  2023-04-19 · 26 citations

  articleOpen access

  The rapid growth of Internet-of-Things (IoT) applications has generated interest from many industries and a need for graduates with relevant knowledge. An IoT system is comprised of spatially distributed interactions between humans and various interconnected IoT components. These interactions are contextualized within their ambient environment, thus impeding educators from recreating authentic tasks for hands-on IoT learning. We propose LearnIoTVR, an end-to-end virtual reality (VR) learning environment which helps students to acquire IoT knowledge through immersive design, programming, and exploration of real-world environments empowered by IoT (e.g., a smart house). The students start the learning process by installing virtual IoT components we created in different locations inside the VR environment so that the learning will be situated in the same context where the IoT is applied. With our custom-designed 3D block-based language, students can program IoT behaviors directly within VR and get immediate feedback on their programming outcome. In the user study, we evaluated the learning outcomes among students using LearnIoTVR with a pre- and post-test to understand to what extent does engagement in LearnIoTVR lead to gains in learning programming skills and IoT competencies. Additionally, we examined what aspects of LearnIoTVR support usability and learning of programming skills compared to a traditional desktop-based learning environment. The results from these studies were promising. We also acquired insightful user feedback which provides inspiration for further expansions of this system.

  PublisherOA PDFDOI

Frequent coauthors

• Kylie Peppler

  17 shared

• Samantha Speer

  7 shared

• Cindy E. Hmelo‐Silver

  6 shared

• Carolyn Penstein Rosé

  6 shared

• Nickolina Yankova

  5 shared

• Karthik Ramani

  Purdue University System

  5 shared

• Ringo Ng

  Oregon Health & Science University

  5 shared

• Rebecca Jordan

  University of Connecticut

  5 shared

Education

• Ph.D. in Learning and Developmental Sciences

  Indiana University Bloomington

• M.A. in Educational Psychology

  The University of Texas at Austin

Awards & honors

• ACM CHI Honorable Mention
• ISLS Best Paper nomination
• AERA’s Best Paper