Researcher Profile | Man (Echo) Su
Research | STEM Learning Technologies

Man (Echo) Su

I investigate how to support students from linguistically and culturally diverse backgrounds in understanding complex STEM concepts through interactive simulations, intelligent tutoring systems, AI-supported pedagogical agents, and educational games.

About

This profile page is designed in a modern, light visual style inspired by the structure and themes of mansu.net — with clear navigation across research, teaching, publications, and ongoing academic work.

Main Research Topics

Interactive Simulations for STEM

Designing and evaluating simulation-based approaches that support conceptual understanding in science and mathematics.

AI-Supported Pedagogical Agents

Building teachable and tutoring agents that scaffold reasoning, feedback, and inquiry learning in digital environments.

Equity in Learning Technologies

Focusing on culturally and linguistically inclusive learning experiences for students from diverse backgrounds.

Featured Projects

Research

AlgeSPACE

Exploring spatial and algebraic reasoning through immersive, interactive learning tasks.

Research

PAIR-C

Collaborative problem-solving and support structures for equitable participation in STEM settings.

Research

ACT / Climate Earth

Simulation-rich learning around climate and systems thinking with learner-centered instruction.

Research

Dr. Discovery / Catch a Mimic

Question-asking and inquiry support in museum and informal learning contexts through digital tools.

Teaching

  • Thesis Topics in Learning Sciences and Educational Technology
  • Seminar Design for Simulation-based Instruction
  • Climate Simulator Classroom Integration
  • Flocking Dynamics and EpiSimulator Learning Activities

Publications

  • Interactive simulation design principles for diverse STEM classrooms
  • AI-supported pedagogical agents in inquiry-based environments
  • Digital teaching scenarios in museums and immersive settings
  • Collaborative learning analytics and equity-focused interventions

News & Updates

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Ask Dr. Discovery 

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The Ask Dr. Discovery project is an intuitive, user-friendly smartphone app that encourages museum visitors to engage deeply with museum content by posing questions to a virtual scientist-astronaut called Dr. Discovery (Dr. D), who provides answers and fun mini-challenges. The questions that visitors ask Dr. D are gathered anonymously in a large database. An analytics system analyzes the data and provides continuous evaluation data to museum staff, helping them make just-in-time tweaks (or longer-term changes) to exhibits and content as current events and visitor needs and interests change. By enhancing the visitor experience and improving museum access to data for evaluation and data-driven decision-making, Ask Dr. Discovery has both a direct and indirect impact on museums and visitors of all types. 

Highlights

1. My recent work focuses on examing museum visitors' question-asking quality via the Dr. D app.

  • The question-asking coding framework derived from this study can contribute to assessing museum visitors' question-asking quality. 

  • Visitors’ question-asking quality was influenced by app modes and by museum environments: visitors’ question-asking quality was significantly higher when using the gamified version of the app (Game Mode) compared to a non-gamified version (Ask Mode) in a linear exhibit.

  • Question-asking quality can be significantly influenced by instrumental factors (such as app performance in answering questions) and socio-contextual factors (such as visitor group inquiry frequency).

Click the image to view an interactive poster about the study

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2.  I also examine the use of the Dr. D app in the following aspects: 

  • Use the ICAP framework to investigate the impact of a gamified Dr. D app on museum visitor group interactions. 

    • ​The app encouraged sharing of information among group members. In addition, users of a gamified version of the app were significantly more likely to report engaging in a group discussion during question-asking than groups using a non-game version of the app. We also found that group collaboration levels depended on the group-designated primary user of the app. Whenever a child or the group collaboratively asked the most questions, group discussion frequency was significantly higher. 

  • Explore the feasibility of forming detailed inferences about museum visitor behavior based on analysis of data collected via the Dr. D app.

    • ​Analysis of this data supported the act of intuiting visitor movement through museum exhibit halls without the use of costly tracking or location technology by leveraging question keyword content, knowledge of exhibit hall layout, and question timestamp information. Additionally, data on question topic frequency enabled us to infer visitor engagement levels with specific exhibit hall content. 

  • Investigate the impact of the Dr. D app on visitor engagement with science museum content.  

    • Users of the Game Mode of the app asked nearly twice as many questions on average as participants using the Ask Mode. Demographic variables, including gender, age, and race/ethnicity were not found to influence the rate of question asking in either mode. These results indicate that employing simple game mechanics in apps for museum visitors may lead to strong positive impacts on visitor engagement with museum content.

This project is funded by NSF Grant Awards number 1438825

 PI: Judd Bowman, Co-PI: Brian Nelson

© Man Su

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