Research

My research interest lies in investigating ways to help learners take a concrete and meaningful approach to an abstract and complex problem in computer science. The content area of my interest centers on computer science concepts and principles; for example, understanding and applying computational thinking concepts or problem-solving algorithms used in computational machines. These subjects are often entangled with unfamiliar notions and notations to novices, making them difficult to understand and often incur misconceptions. Employing approachable representations can address these challenges by helping learners approach the knowledge structure of computer science easily especially when they acquire new concepts and skills or adapt to unfamiliar environments. One of the ways that could provide an accessible representation to learners is to offer visual aids. From graphic organizers to visual programming languages, visual guidance helps learners build a cognitive model by envisioning concrete structures or conceiving ideas in relation to other pertinent elements. Therefore, my area of interest includes the following.

  1. Teaching computer science using accessible representational systems, especially for computational thinking and artificial intelligence at the K-8 level.

  2. Broadening participation in computing and enhancing diversity, equity, and inclusion in computer science education.

  3. Investigating affordances of representational guide in collaborative knowledge construction.

First Author Study

Does Function Follow Form?:
Effects of Different Graphic Organizers in Asynchronous Online Discussions

In this study, the effects of using a graphic organizer in the asynchronous discussion were examined. Thirty-six graduate students participated in online discussions while making graphic organizers in a group. A group of four students engaged with weekly discussions in which they developed collaborative argumentations on instructional cases situated in a dilemma. The student groups collaboratively created a graphic organizer using web 2.0 tools in a discussion. The types of graphic organizers used were t-charts, tree charts, and maps. A t-chart is a table that shows two sides of a subject (e.g., pros vs. cons). A tree chart gets a subject to branch out into multiple, detailed subtopics, showing analytical structure or hierarchy of topics. A map depicts relations of a topic or a node to others. This study aims to reveal the effects of these graphic organizers on learners’ participation and interaction in the discussions, as well as the level of knowledge construction represented in their posts. In addition, learners’ perceptions of their online learning experience with graphic organizers were investigated.

Keywords: asynchronous online learning, threaded discussion, knowledge construction, collaborative learning, graphic organizers, case-based learning, instructional design

Literature Review & Synthesis

Research Projects

AI Goes Rural

Research Assistant
2021 –

  • Project description: Incorporating Artificial Intelligence into the rural middle school curriculum

  • Funded by the Office of the Secretary of Defense

  • PIs: Drs. Kwon, Leftwich, & Glazewski

  • Assisted in the design of the professional development program for the participating teachers

PrimaryAI

Research Assistant
2020 –

  • Project description: Integrating Artificial Intelligence into upper elementary science with immersive problem-based learning

  • NSF#1934128

  • PIs: Drs. Glazewski, Leftwich, Hmelo-Silver, Lester, & Mott

  • Assists in the development of lesson plans, assessment, use-case scenarios for online game

  • Assisted in the writing of research articles about how teachers and students perceive AI

ECEP & CSforIN

Research Assistant
2020 –

  • Project description: Broadening participation in computing for K-12; Expanding Computing Education Pathways 2.0 & CS for Indiana

  • NSF#1822011

  • PI: Dr. Leftwich

  • Conducted document analysis of the ECEP's longitudinal data and created a database tracking the state of CS education across states

  • Performed content analysis of interview data

  • Assisted in the writing of research articles about broadening participation in computing alliances

  • Exploratory data analysis for the CS enrollment data in Indiana

Google Computer Science Education Research Group

Research Assistant
2018 – 2020

  • Project description: A problem-based learning integrated CS curriculum for upper elementary students

  • Funded by Google

  • PI: Dr. Leftwich

  • Assisted in the development of instructional materials for inquiry-based computer science curriculum

  • Devised assessment tools for measuring computational thinking of K-6 students

  • Analyzed assessment results with inferential statistics

  • Analyzed elementary students' CT practice represented in their Scratch programs

CSCL Group

Research Assistant
2018 – 2020

  • Computer-Supported Collaborative Learning Research Group

  • PI: Dr. Kwon

  • Designed case-based learning activities and provided feedback to graduate students

  • Developed video tutorials for instructional design cases

  • Facilitated online discussions in a graduate-level course

  • Conducted surveys, interviews, and quantified content analysis

Library Collection

Collection Assistant
2018–2019

  • Department of the East Asian Studies, Wells Library, Indiana University

  • Supervisor: Dr. Wen-ling Liu

  • Recommended appropriate books for the library’s collection for Korean studies

  • Identified available resources from books and journal databases to support scholarship

  • Designed a display poster for the East Asian Department

Evaluating ODA Education Programs

Senior Researcher
2017–2018

  • Strategic development of ASEAN+3 Center for the Gifted in Science

  • PI: Dr. Suyoung Lee at Seoul National University of Education

  • Funded by the Korea Foundation for the Advancement of Science & Creativity

  • Project description: Evaluating educational official development assistance programs of Korea for southeast Asian countries

  • Assisted interviews, transcribed, and analyzed interview data

  • Conducted literature review

Publications

Journal Articles

Published

  1. Koressel, J., Ottenbreit-Leftwich, A. T., Jantaraweragul, K., Jeon, M., Warner, J., & Brown, M. (2022). Investigating CS teacher licensure in Indiana [Special Issue]. TechTrends, 66, 412–422. https://doi.org/10.1007/s11528-022-00726-9

  2. Kwon, K., Jeon, M., Guo, M., Yan, G., Kim, J., Ottenbreit-Leftwich, A. T., & Brush, T. A. (2021). Computational Thinking practices: Lessons learned from a problem-based curriculum in primary education. Journal of Research on Technology in Education, 1–18. https://doi.org/10.1080/15391523.2021.2014372

  3. Kwon, K., Ottenbreit-Leftwich, A. T., Brush, T., Jeon, M., & Yan, G. (2021). Integration of problem-based learning in elementary computer science education: Effects on computational thinking and attitudes. Educational Technology Research & Development, 69(5), 2761–2787. https://doi.org/10.1007/s11423-021-10034-3

  4. Ottenbreit-Leftwich, A. T., Dunton, S., Fletcher, C., Childs, J., Jeon, M., Biggers, M., DeLyser, L. A., Goodhue, J., Richardson, D., Peterfreund, A., Guzdial, M., Adrion, R., Ericson, B., Fall, R., & Abramenka, V. (2022). How to change a state: Broadening participation in K-12 computer science education. Policy Futures in Education. https://doi.org/10.1177/14782103221123363

  5. Ottenbreit-Leftwich, A. T., Glazewski, K., Jeon, M., Jantaraweragul, K., Hmelo-Silver, C., Scribner, A., Lee, S., Mott, B., & Lester, J. (2022). Lessons learned for AI education with elementary students and teachers [Special issue]. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-022-00304-3

  6. Ottenbreit-Leftwich, A. T., Kwon, K., Brush, T., Karlin, M., Jeon, M., Jantaraweragul, K., Guo, M., Nadir, H., Gok, F., & Bhattacharya, F. (2021). The Impact of an issue-centered problem-based learning curriculum on 6th grade girls’ understanding of and interest in computer science. Computers & Education Open, 2, 100057. https://doi.org/10.1016/j.caeo.2021.100057

Submitted for Review

  1. Jeon, M., Kwon, K., & Bae, H. (Revise and resubmit). Effects of different graphic organizers in asynchronous online discussions. Educational Technology Research & Development.

  2. Jeon, M., Koressel, J., Ottenbreit-Leftwich, A. T., & Jantaraweragul, K. (Under review). Indiana high schools' Computer Science enrollment and disparity indices: On gender, ethnicity, locale, and economic status. Computer Science Education.

  3. Jeon, M., & Kwon, K. (Under review). Parallel instructions of text-based and block-based programming: On novice programmers’ computational thinking practices. Educational Studies.

  4. Kwon, K., Jeon, M., Zhou, C., Kim, K., & Brush, T. (Under review). Embodied learning for computational thinking in early primary education. Journal of Research on Technology in Education

Manuscripts in Preparation

  1. Jeon, M., Jantaraweragul, K., Ottenbreit-Leftwich, A. T., Glazewski, K., Hmelo-Silver, C., Mott, B., Lester, J., & Kim, H. An inquiry-based artificial intelligence curriculum for upper elementary students: A design case of PrimaryAI.

  2. Jeon, M., Ottenbreit-Leftwich, A. T., Koressel, J., & Brown, M. Indicators contributing to Computer Science enrollment: Based on high schools in Indiana.

  3. Jeon, M., Kwon, K., Ottenbreit-Leftwich, A. T., & Glazewski, K. A project-based AI literacy program for middle school students: On conceptual understanding and productive dispositions.

  4. Jeon, M., Kwon, K., Ottenbreit-Leftwich, A. T., & Glazewski, K. Exploring AI-infused problem-solving of middle schoolers: Using multimodal transcription.

  5. Kwon, K., Bae, H., Jeon, M., & Rutkowski, L. Structural equation modeling to examine the effects of metacognitive instructions for self-regulated learning.

  6. Kwon, K., Kim, K., Jeon, M., Zhou, C., & Brush, T. Learners' strategies for spatial reasoning and computational thinking.

Conference Presentations

  1. Jeon, M., Jantaraweragul, K., Glazewski, K., Ottenbreit-Leftwich, A., Chakraburty, S., Scribner, A., Hmelo-Silver, C., Mott, B., & Lester, J. (2022, September 14-16). PrimaryAI: Where life sciences, artificial intelligence, and computer science converge [ICT demonstration]. The European Association for Research on Learning and Instruction (EARLI) 2022 Joint SIG 20 and SIG 26 Conference, Utrecht, Netherlands.

  2. Ottenbreit-Leftwich, A., Glazewski, K., Jeon, M., Jantaraweragul, K.,Hmelo-Silver, C., Scribner, A., Lee, S., Mott, B., & Lester, J. (2022, July 8-13). Principles for AI Education for Elementary Grades Students [Poster]. Innovation and Technology in Computer Science Education (ITiCSE) 2022 Conference, Dublin, Ireland.

  3. Glazewski, K., Ottenbreit-Leftwich, A., Jantaraweragul, K., Jeon, M., Hmelo-Silver, C., Scribner, A., Lee, S., Mott, B., & Lester, J. (2022, July 8-13). PrimaryAI: Co-Designing Immersive Problem-Based Learning for Upper Elementary Student Learning of AI Concepts and Practices [Poster]. Innovation and Technology in Computer Science Education (ITiCSE) 2022 Conference, Dublin, Ireland.

  4. Jeon, M., Koressel, J., Jantaraweragul, K., & Ottenbreit-Leftwich, A. (2022, October 24-28). Indiana High School’s Computer Science Enrollment and Disparity Indices: On Gender, Ethnicity, Locale, and Economic Status [Concurrent session]. 2022 AECT Convention, Las Vegas, NV.

  5. Jeon, M., Kwon, K., Ottenbreit-Leftwich, A., Glazewski, K., Closser, F., Bae, H., & Kim, K. (2022, October 24-28). Developing a Student-centered AI Literacy Curriculum for Rural Middle School Students [Poster session]. 2022 AECT Convention, Las Vegas, NV.

  6. Jantaraweragul, K., Jeon, M., Lee, H., Glazewski, K., Ottenbreit-Leftwich, A., Hmelo-Silver, C., Scribner, A., Mott, B., & Lester, J. (2022, October 24-28). PrimaryAI: A Problem-Based Learning Approach to Teaching Elementary Students Artificial Intelligence and Animal Conservation [Showcase]. 2022 AECT Convention, Las Vegas, NV.

  7. Kim, K., Ottenbreit-Leftwich, A., Kwon, K., Glazewski, K., Closser, F., Bae, H., & Jeon, M. (2022, October 24-28). Design Considerations of Synchronous Online AI Professional Development for Middle School Teachers [Concurrent session]. 2022 AECT Convention, Las Vegas, NV.

  8. Koressel, J., Jeon, M., Jantaraweragul, K., & Ottenbreit-Leftwich, A. (2022, March 4). Indiana High School’s Computer Science Enrollment and Disparity Indices: On Gender, Ethnicity, Locale, and Economic Status [Paper session]. 2022 IST Conference, Online.

  9. Zhou, C., Kim, K., Jeon, M., Kwon, K., & Brush, T. (2022, March 4). Developing Computational Thinking with Programming Robots Through Collaborative Embodied Learning in Elementary School Classrooms [Paper session]. 2022 IST Conference, Online.

  10. Kim, K., Bae, H., Jeon, M., Closser, F., Kwon, K., Ottenbreit-Leftwich, A., & Glazewski, K. (2022, March 4). Design Considerations of Synchronous Online AI Professional Development for Middle School Teachers [Paper session]. 2022 IST Conference, Online.

  11. Jeon, M. & Kwon, K. (2022, April 21-26). Parallel Instructions of Text-based and Block-based Programming: On Novice Programmers’ Computational Thinking Practices [Paper session]. 2022 AERA Annual Meeting, San Diego, CA.

  12. Closser, F., Kwon, K., Ottenbreit-Leftwich, A. T., Glazewski, K., Acharya, R., Dalkilic, M., Bae, H., Jeon, M., & Kim, K. (2022, January 13). AI Goes Rural. Indiana STEM Education Conference, West Lafayette, IN.

  13. Jeon, M., Kwon, K., & Bae, H. (2021, November 2-6). Effects of Graphic Organizers in Asynchronous Online Discussion [Roundtable session]. 2021 AECT Convention, Chicago, IL.

  14. Phillips, T., Jeon, M., Jantaraweragul, K., & Kwon, K. (2021, November 2-6). An Exploration of the Relationship Between Social Media Usage and Undergraduate School Satisfaction [Roundtable session]. 2021 AECT Convention, Chicago, IL.

  15. Kwon, K., Jeon, M., Nadir, H., Sankaranarayanan, R., Gok, S., Chavez, N., & Lee, H. (2021, November 2-6). Embodied Learning for Computational Thinking Education [Concurrent session]. 2021 AECT Convention, Chicago, IL.

  16. Phillips, T., & Jeon, M. (2021, November 2-6). A Gentle Introduction to Neural Networks for Natural Language Processing with R [Workshop canceled]. 2021 AECT Convention, Chicago, IL.

  17. Jantaraweragul, K., Jeon, M., Glazewski, K., Ottenbreit-Leftwich, A., Hmelo-Silver, C., Lee, S., Mott, B., & Lester, J. (2021, August 17-19). The Participatory Co-Design of a Problem-Based Learning Artificial Intelligence Elementary Curriculum [Roundtable session]. 2021 International PBL Conference, Online.

  18. Jeon, M., Dunton, S., Ottenbreit-Leftwich, A., Peterfreund, A., Fletcher, C., Biggers, M., Richardson, D., Childs, J., Delyser, L. A., & Goodhue, J. (2021, July 14-16). Be An Advocate for Broadening Participation in Computing [Conference session]. 2021 CSTA Annual Conference, Online.

  19. Koressel, J., Jeon, M., Ottenbreit-Leftwich, A., & Kwon, K. (2021, July 14-16). Indiana's CS Story [Mini session]. 2021 CSTA Annual Conference, Online.

  20. Guo, M., Ge, Y., Kim, J., Jeon, M., Kwon, K., Ottenbreit-Leftwich, A., & Brush, T. (2021, April 8-12). Coding Patterns and Techniques in Sixth Graders’ Block-based Programming Projects [Poster session]. 2021 AERA Annual Meeting, Online.

  21. Jeon, M., Koressel, J., Ottenbreit-Leftwich, A., Peterfreund, A., Dunton, S., Xavier, J., Fletcher, C., Zarch, R., Biggers, M., Richardson, D., Childs, J., DeLyser, L., A., & Goodhue, J. (2021, March 13-20). Document Analysis of ECEP Longitudinal Data: A Case Study with Indiana [Poster session]. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (p. 1314). https://doi.org/10.1145/3408877.3439655

  22. Ottenbreit-Leftwich, A., Glazewski, K., Jeon, M., Hmelo-Silver, C., Mott, B., Lee, S., & Lester, J. (2021, March 13-20). How do Elementary Students Conceptualize Artificial Intelligence? [Poster session]. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (pp. 1261-1261). https://doi.org/10.1145/3408877.3439642

  23. Jeon, M., Kwon, K., & Bae, H. (2021, March 5). Effects of Graphic Organizers in Asynchronous Online Discussions [Paper session]. 2021 IST Conference, Online.

  24. Jeon, M., & Kwon, K. (2020, October 29-30). Novice Programmers’ Understanding and Implementations of CS Concepts: Focusing on the Problem Solving Represented in the Programming Environments with Different Modalities [Conference session]. 2020 AECT Convention, Online.

  25. Kwon, K., Ottenbreit-Leftwich, A., Brush, T. & Jeon, M. (2020, April 17-21). Effects of Problem-Based Learning Curriculum for Computer Science Education in an Elementary School [Conference session]. 2020 AERA Annual Meeting, San Francisco, CA. http://tinyurl.com/wl5lak9 (Conference Canceled).

  26. Kwon, K., Ottenbreit-Leftwich, A., Brush, T., Jeon, M., Zhu, M., & Gok, F. (2019, October 21-25). Exploring 6th-grade Students’ CT Concepts and Practices [Conference session]. 2019 AECT Convention, Las Vegas, NV.

  27. Ottenbreit-Leftwich, A., Brush, T., Kwon, K., Karlin, M., Jeon, M., Jantaraweragul, K., Abramenka-Lachheb, V., Nadir, H., Guo, M., Zhu, M., Alghamdi, K., Yan, Y., Gates, L., Gok, F., Estell, D., Roberts, M., & Dalkilic, M. (2019, October 21-25). Inspiring the Next Generation of Learners: Using Socially Relevant Computer Science (CS) Problem-based Learning Curriculum at the 6th Grade Level [Conference session]. 2019 AECT Convention, Las Vegas, NV.

Awards & Grants

  • Annual Women’s Research Poster Competition, First Place, $200, Center of Excellence for Women & Technology (CEWiT), Indiana University, 2022

  • Student Conference Travel Fund Award, $300, Center For Research on Learning and Technology, Indiana University, 2022

  • IST/AVC Memorial Fellowship, $5,000, Instructional Systems Technology, Indiana University, 2022

  • Jerrold E. Kemp IST Fellowship, $1,500, Instructional Systems Technology, Indiana University, 2022

  • L. C. and Sharon Larson Fellowship, $500, Instructional Systems Technology, Indiana University, 2022

  • Jerrold E. Kemp IST Fellowship, $1,345, Instructional Systems Technology, Indiana University, 2021

  • IU GPSG Travel Awards $245, Graduate & Professional Student Government, Indiana University, 2021

  • CSEdGrad Research Projects $5,000, SageFox Consulting Group LLC., 2020

  • Webb IST Fellowship $4,000, Instructional Systems Technology, Indiana University, 2020

  • Jerrold E. Kemp IST Fellowship $2,022, Instructional Systems Technology, Indiana University, 2020

  • L. C. Larson Award $525, Instructional Systems Technology, Indiana University, 2019

  • L. C. and Sharon Larson Fellowship $550, Instructional Systems Technology, Indiana University, 2019

  • Fulbright Scholarship $50,490, U. S. Department of State, 2018-2020

Methodological Competencies

Qualitative inquiry

  1. EDUC-Y611 Qualitative Inquiry in Education

  2. EDUC-R690 Application of Research Methods to IST Issues

  3. Participated in qualitative inquiry during research group projects

  • Assisted interview, conducted thematic analysis, and wrote a research article (PrimaryAI, 2020)

  • Thematic & content analysis of the student writings, conducted and analyzed interviews (CSCL, 2020)

  • Thematic analysis of interview data, document analysis (ECEP, 2019)

  • Observed undergraduate computer science classes, wrote observation notes and research articles (EDUC-W220, 2019)

  • Observed upper elementary computer science classes, wrote observation notes for research, and assisted in the writing of research articles (Google Computer Science Education Research Group, 2018-2019)

  1. Participated in qualitative inquiry during class projects

  • Video analysis for Human-Centered Robotics class (EDUC-R685 Learning Through Problem Solving, 2019)

Quantitative inquiry
Master in Applied Statistics

  1. STAT-S520 Introduction to Statistics

  2. STAT-S610 Introduction Statistical Computing

  3. STAT-S625 Nonparametric Theory Data Analysis

  4. STAT-S670 Exploratory Data Analysis

  5. STAT-S631 Applied Linear Models I

  6. STAT-S632 Applied Linear Models II

  7. STAT-S690 Statistical Consulting

  8. EDUC-Y645 Covariance Structure Analysis

  9. EDUC-Y639 Multilevel Modeling

  10. EDUC-Y604 Multivariate Analysis in Education Research (Transfer)

  11. EDUC-P501 Statistical Method Applied to Education (Transfer)

  12. EDUC-Y502 Intermediate Statistics Applied to Education (Transfer)

  13. SPH-H750 Quantitative Methods II for Public Health Research (Sit-in after the instructor's approval)

  14. DataCamp's Online Data Scientist Track (15 courses): Certificates

Theories of Instructional Design & Educational Psychology

Instructional Design

  1. EDUC-R511 Instructional Technology Foundations I

  2. EDUC-R521 Instructional Design & Development I

  3. EDUC-R541 Instructional Development & Production I

  4. EDUC-R561 Evaluation in the Instructional Development Process

  5. EDUC-R621 Analysis for Instruction and Performance Improvement

  6. EDUC-R711 Readings in Instructional Systems Technology

Educational Psychology

  1. EDUC-P545 Educational Motivation

  2. EDUC-R546 Instructional Techniques to Facilitate Thinking, Collaboration, and Motivation

  3. EDUC-R685 Learning Through Problem-solving

  4. EDUC-P640 Thinking & Learning in Social Contexts