"We do rigorous, data-driven research to create educational solutions, diffuse innovation at scale, and advance our body of knowledge in learning and instructional theories."

2024

Haddadian, G., Radmanesh, S., & Haddadian, N. (2024). Construction and validation of a Computerized Formative Assessment Literacy (CFAL) questionnaire for language teachers: An exploratory sequential mixed-methods investigation. Language Testing in Asia, 14(33). https://doi.org/10.1186/s40468-024-00303-2

Kim, M. K., Kim, J., & Heidari, A. (2024). Exploring the multi-dimensional human mind: Model-based and text-based approaches. Assessing Writing, 61, 100878. https://doi.org/10.1016/j.asw.2024.100878

Haddadian, G. & Haddadian, N. (2024). Innovative use of grammarly feedback for improving EFL learners’ speaking: Learners’ perceptions and transformative engagement experiences in focus. The Journal of Applied Instructional Design, 13(2). 

Bae, Y., Kim, J., Davis, A., & Kim, M. K. (2024). A Study on AI-Augmented Concept Learning: Impact on Learner Perceptions and Outcomes in STEM Education. In Lindgren, R., Asino, T. I., Kyza, E. A., Looi, C. K., Keifert, D. T., & Suárez, E. (Eds.), Proceedings of the 18th International Conference of the Learning Sciences - ICLS 2024 (pp. 1450-1453). International Society of the Learning Sciences.

Haddadian, G., Panzade, P., Takabi, D., & Kim, M. K. (2024). Evaluating Private Artificial Intelligence (AI) Curriculum in Computer Science (CS) Education: Insights for Advancing Student-Centered CS Learning. In Lindgren, R., Asino, T. I., Kyza, E. A., Looi, C. K., Keifert, D. T., & Suárez, E. (Eds.), Proceedings of the 18th International Conference of the Learning Sciences - ICLS 2024 (pp. 2271-2272). International Society of the Learning Sciences.

Kim, J., Bae, Y., Stravelakis, J., & Kim, M. K. (2024). Investigating the Influence of AI-Augmented Summarization on Concept Learning, Summarization Skills, Argumentative Essay Writing, and Course Outcomes in Online Adult Education. In Lindgren, R., Asino, T. I., Kyza, E. A., Looi, C. K., Keifert, D. T., & Suárez, E. (Eds.), Proceedings of the 18th International Conference of the Learning Sciences - ICLS 2024 (pp. 2309-2310). International Society of the Learning Sciences.

Kim, J., Lee, T. H., Bae, Y., & Kim, M. K. (2024). A Comparison Between AI and Human Evaluation with a Focus on Generative AI. In Lindgren, R., Asino, T. I., Kyza, E. A., Looi, C. K., Keifert, D. T., & Suárez, E. (Eds.), Proceedings of the 18th International Conference of the Learning Sciences - ICLS 2024 (pp. 1722-1725). International Society of the Learning Sciences.

Kim, M. K., Kim, J., Bae, Y., Morris, W., Holmes, L., & Crossley, S. (2024). How AI Evaluates Learner Comprehension: A Comparison of Knowledge-Based and Large Language Model (LLM)-Based AI Approaches. In Lindgren, R., Asino, T. I., Kyza, E. A., Looi, C. K., Keifert, D. T., & Suárez, E. (Eds.), Proceedings of the 18th International Conference of the Learning Sciences - ICLS 2024 (pp. 1311-1314). International Society of the Learning Sciences.

2023

Bae, Y., Kim, J., & Kim, M. (2023). Clustering cognitive engagement changes in a longitudinal traced discussion data from an online course. In Damșa, C., Borge, M., Koh, E., & Worsley, M. (Eds.). Proceedings of the 17th International Conference on Computer-Supported Collaborative Learning - CSCL 2023 (pp. 297-300). Montreal, Canada: International Society of the Learning Sciences.

Kim, J., Haddadian, G., & Kim, M. (2023). An investigation of knowledge-based AI vs. human evaluation in academic summary evaluation: Similarities, dissimilarities, and being toward mutual understandings. In Blikstein, P., Van Aalst, J., Kizito, R., & Brennan, K. (Eds.). Proceedings of the 17th International Conference of the Learning Sciences - ICLS 2023 (pp. 994-997). Montreal, Canada: International Society of the Learning Sciences.

Kim, M., Kim, N., Haddadian, G., & Heidari, A. (2023). A test of learning progress models using an AI-enabled knowledge representation system. In Blikstein, P., Van Aalst, J., Kizito, R., & Brennan, K. (Eds.). Proceedings of the 17th International Conference of the Learning Sciences - ICLS 2023 (pp. 986-989). Montreal, Canada: International Society of the Learning Sciences.

2022

Kim, J., Lee, M., Park, J., Kim, J., & Sohn, E. (2022). Effects of a Cognitive Flexibility Hypertext Learning Environment for University Software Education. Journal of Korea Multimedia Society, 25(12), 1698–1713.

Lee, M., Kim, S., Choi, S. Y., & Kim, J. (2022). Does the International Baccalaureate Diploma Program (IBDP) contribute to Whole-Person Development? The Rise of the IBDP in Asia and its implications for education reform. In Centering Whole-Child Development in Global Education Reform (pp. 83–101). Routledge.

Kim, M., & Kim, N. (2022). AI-supported scaffolding for writing academic arguments. In C. Chinn, E. Tan, C. Chan, & Y. Kali (Eds.), Proceedings of the 16th International Conference of the Learning Sciences-ICLS2022 (pp. 1129-1132). Hiroshima, Japan: International Society of the Learning Sciences. https://www.dropbox.com/s/ws5sdcfi72aykj1/ICLS2022%20Proceedings.pdf?dl=0  

Bundrage, C. & Mapson, K. (2022). Design and Development of an Online Professional Development Course on Culturally Responsive Pedagogy Using the ADDIE Model. In E. Langran (Ed.), Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 248-256). San Diego, CA, United States: Association for the Advancement of Computing in Education (AACE). Retrieved April 29, 2022 from https://www.learntechlib.org/primary/p/220742/.

Kim, N., & Kim, M. (2022). Teacher's perceptions of using an artificial intelligence-based educational tool. Frontiers in Education, 7(755914), 1-13. https://doi.org/10.3389/feduc.2022.755914

Kim, M., Kim, N. & Heidari, A. (2022). Learner experience in Artificial Intelligence scaffolded argumentation. Assessment and Evaluation in Higher Education. Advance online publication. http://doi.org/10.1080/02602938.2022.2042792

2021
Kim, M. (2021). A design experiment on technology-based learning progress feedback in a graduate-level online course. Human Behavior and Emerging Technologies. Advanced online. http://doi.org/10.1002/hbe2.308
Ran, H., Kim, N. J., & Secada, W. (2021, Online First). Technology roles: Meta-analysis on effects of technology on students' mathematics achievement in K-12 classrooms. Journal of Computer-Assisted Learning.
Kim, N. J. & Kim, S. W. (2021). Utilization of TV as an aid for value creation in future education. Journal of the Korea Society of Computer and Information, 26(10), 61-76.
Kim, M., & McCarthy, K. S. (2021). Using graph centrality as a global index to assess students’ mental model structure development during summary writing. Educational Technology Research & Development (ETRD), 69, 971-1002. https://link.springer.com/article/10.1007/s11423-021-09942-1
Kim, M., Lee, I., & Kim, S. (2021). A longitudinal examination of temporal and iterative relationships among learner engagement dimensions during online discussion. Journal of Computers in Education, 8, 63-86. https://doi.org/10.1007/s40692-020-00171-8
Kim, N. J., Park, J., Lee, S., & Timpilis, D. (2021). Impact of prior knowledge, learning style, and problem nature on students performance in a flipped engineering mathematics class, International Journal of Engineering Education, 37(4), 960-974.
Kim, N. J., Vicentini, C., & Belland, B. R. (2021). Influence of scaffolding on information literacy and argumentation skills in virtual field trips and problem-based learning for scientific problem-solving, International Journal of Science and Mathematics Education, 1-22.
Giancaspro, J. & Kim, N. J. (2021). Student-Parent Teams: A 10-year retrospective study of an undergraduate research experience, International Journal of Continuing Engineering Education and Life-Long Learning, 31(4), 419-438.
Belland, B. R., & Kim, N. J. (2021). Predicting high school students’ argumentation skill using information literacy and trace data, The Journal of Educational Research, 1-34.
2020
Kim, M., & McCarthy, K. S. (2020). Improving summary writing through formative feedback in a technology-enhanced learning environment. Journal of Computer Assisted Learning, 1-21. Advance online publication. http://dx.doi.org/10.1111/jcal.12516
Kim, M., Gaul, C., Bundrage, C, & Madathany, R. (2020). Technology supported reading comprehension: A design research of Student Mental Model Analyzer for Research and Teaching (SMART) technology. Interactive Learning Environments. Advance online publication. https://doi.org/10.1080/10494820.2020.1838927
Kim, M., & Margulieux, L. (2020). A case study of the short-term exposure to hybrid learning. International Journal of Learning Technology, 15(1), 66-81. https://doi.org/10.1504/IJLT.2020.107665
Gaul, C. & Kim, M. (2020). Learner participation regulation supported by long-term peer moderation and participation feedback during asynchronous discussions. Journal of Computers in Education, 7, 295–331. https://doi.org/10.1007/s40692-020-00158-5
Kim, M., Lee, I., & Wang, Y. (2020). How students emerge as learning leaders in small group online discussions: The role of leadership styles and learner engagement. Journal of Computer Assisted Learning, 36(5), 610-624. https://onlinelibrary.wiley.com/doi/full/10.1111/jcal.12431
Li, H., Kim, M., & Xiong, Y. (2020). Individual learning vs. interactive learning: A cognitive diagnostic analysis of MOOC students' learning behaviors. American Journal of Distance Learning, 34(2), 121-136. https://doi.org/10.1080/08923647.2019.1697027
Kim, M., & Kim, S. (2020). Dynamic learner engagement in a wiki-enhanced writing course. Journal of Computing in Higher Education, 32(3), 582–606. https://doi.org/10.1007/s12528-019-09248-5
Kim, M., Wang, Y., & Ketenci, T. (2020). Who are the learning leaders? Piloting a Leader Identification Method (LIM). Computers in Human Behavior, 105, 106-205. https://doi.org/10.1016/j.chb.2019.106205
Kim, M. & Ketenci, T. (2020). The role of expressed emotions in an online discussion: Leveraging a machine learning approach. Journal of Research on Technology in Education. 52(1), 95-112. https://doi.org/10.1080/15391523.2019.1697861
Kim, N. J., Belland, B. R., Lefler, M., Andreasen, L., Walker, A., & Axelrod, D. (2020). Comparison of computer-based scaffolding targeting individuals versus groups in complex problem solving: Meta-analysis. Educational Psychology Review, 32, 415-461.
Kolovou, M. & Kim, N. J. (2020). Effects of Implementing an integrative Drama-Inquiry Learning Model in a Science Classroom, The Journal of Educational Research, 113(3), 191-203.
Belland, B., Weiss, D. M., & Kim, N. J., (2020). High school students’ agentic responses to modeling during problem-based learning, The Journal of Educational Research, 113(5), 374-383.
Kim, M., & McCarthy, K. (2020). Summary writing as a process of building a solid mental model: A global index to describe knowledge structure change. In M. Gresalfi, & I. S. Horn (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020 (pp. 74-81). Nashville, Tennessee: International Society of the Learning Sciences.
Kim, M., Heidari, A., & McCarthy, K. (2020). Reading comprehension and mental model development: A cross-validation of methods and technologies to assess student understanding of the text. In M. Gresalfi, & I. S. Horn (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020 (pp. 561-564). Nashville, Tennessee: International Society of the Learning Sciences.
Gaul, C. & Kim, M. (2020). Conceptualizing computational thinking pedagogical content knowledge: An exploratory study. In D. Schmidt-Crawford (Ed.), Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 14-23). Online: Association for the Advancement of Computing in Education (AACE). Retrieved April 27, 2020 from https://www.learntechlib.org/primary/p/215726/.
Ketenci, T., Kumar, K. & Kim, M. (2020). Emotion analysis for discussion board posts. In D. Schmidt-Crawford (Ed.), Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 777-783). Online: Association for the Advancement of Computing in Education (AACE).
Kim, M., Lee, I. & Wang, Y. (2020, Apr 17 - 21) How Students Emerge as Learning Leaders in a Small-Group Online Discussion: The Role of Leadership Styles and Learner Engagement [Paper Session]. AERA Annual Meeting San Francisco, CA http://tinyurl.com/vhbhqau (Conference Canceled)
Gaul, C. J., Kim, M., Bundrage, C. N. & Madathany, R. (2020, Apr 17 - 21) Technology-supported reading comprehension: A design research of the Student Mental Model Analyzer for Research and Teaching (SMART) [Paper Session]. AERA Annual Meeting San Francisco, CA http://tinyurl.com/uq37trk (Conference Canceled)
Gaul, C. J., & Kim, M. (2020, Apr 17 - 21). Design research on learner participation feedback within peer-moderated asynchronous online discussions [Paper Session]. AERA Annual Meeting San Francisco, CA http://tinyurl.com/wy8bj25 (Conference Canceled)
2019
Kim, M., Gaul, C., Kim, S., & Madathany, R. (2019). Advance in detecting key concepts as an expert model: Using Student Mental Model Analyzer for Research and Teaching (SMART). Technology, Knowledge and Learning, 25(4), 953-976. https://doi.org/10.1007/s10758-019-09418-5
Kim, M., & Ketenci, T. (2019). Learner participation profiles in an asynchronous online collaboration context. Internet and Higher Education, 41. 62-76. (The 2020 AECT RTD Outstanding Empirical Journal Article Award)
Kim, N. J., Belland, B. R., & Axelrod, D. (2019). Scaffolding for optimal challenge in K-12 problem-based learning. Interdisciplinary Journal of Problem-based Learning, 13(1), 1-23.
Belland, B. R., Gu, J., Kim, N. J., Piland, J., & Weiss, D. M. (2019). Exploring epistemological approaches and beliefs of middle school students in problem-based learning. Journal of Educational Research, 112(6), 643-655.
Belland, B. R., Weiss, D. M., Kim, N. J., Piland, J., & Gu, J. (2019). An examination of credit recovery students’ use of computer-based scaffolding in a problem-based, scientific inquiry unit. International Journal of Science and Mathematics Education, 17(2), 273-293.
Wang, Y., & Kim, M. (2019). Identify learning leaders in collaborative learning: Using social network analysis to develop and compare two methodological approaches. In K. Lund, G. Niccolai, E. Lavoue, C. Hmelo-Silver, G. Gweon, & M. Baker (Eds.) The 13th International Conference on Computer Supported Collaborative Learning (pp.883-885). Lyon, France.
2018
Kim, N. J., Belland, B. R., & Walker, A. E. (2018). Effectiveness of computer-based scaffolding in the context of problem-based learning for STEM education: Bayesian meta-analysis. Educational Psychology Review, 30(2), 397-429.
Kim, K., Kim, N. J., Seo, J., & Kim, S. W. (2018). Utilization of computer pointing game for improving visual perception ability of children with severe intellectual disability. Journal of the Korea Society of Computer and Information, 23(4), 41-49.
2017
Kim, M., Xie, K., & Cheng, S. (2017). Building teacher competency for digital content evaluation. Teaching and Teacher Education, 66, 309-324. https://doi.org/10.1016/j.tate.2017.05.006
Xie, K., Kim, M., & Cheng, S. (2017). Teacher professional development through digital content evaluation. Educational Technology Research and Development, 65(4), 1067-1103. https://doi.org/10.1007/s11423-017-9519-0
Belland, B. R., Walker, A. E., & Kim, N. J. (2017). Bayesian network meta-analysis to synthesize the influence of contexts of scaffolding use on cognitive outcomes in STEM education. Review of Educational Research, 87(6), 1042-1081. The Outstanding Journal Article Award (2018), Research and Theory Division, Association for Educational Communications & Technology.
Belland, B. R., Walker, A. E., Kim, N. J., & Lefler, M. (2017). Synthesizing results from empirical research on computer-based scaffolding in STEM education: A meta-analysis. Review of Educational Research, 87(2), 309-344. The Outstanding Journal Article Award (2017), Research and Theory Division, Association for Educational Communications & Technology
2016
Kim, M., Zouaq, A., & Kim, S. (2016). Automatic detection of expert models: The exploration of expert modeling methods applicable to technology-based assessment and instruction. Computers & Education, 101, 55-69. https://doi.org/10.1016/j.compedu.2016.05.007
Belland, B. R., Gu, J., Kim, N. J., & Turner, D. J. (2016). An ethnomethodological perspective on how middle school students addressed a water quality problem. Educational Technology Research & Development, 64, 1135–1161.
Lee, J. E., Recker, M., Choi, H., Hong, W. J., Kim, N. J., Lee, K., … & Recker, M. (2016). Applying data mining methods to understand user interactions within learning management systems: Approaches and lessons learned. Journal of Educational Technology Development and Exchange, 8(2), 99-116.
Selected Earlier Articles
Kim, M. (2015). Models of learning progress in solving complex problems: expertise development in teaching and learning. Contemporary Educational Psychology. 42. 1-16. https://doi.org/10.1016/j.cedpsych.2015.03.005
Kim, M., Kim, S., Khera, O., & Getman, J. (2014). The experience of three flipped classrooms in an urban university: An exploration of design principles. Internet and Higher Education, 22, 37-50. http://dx.doi.org/10.1016/j.iheduc.2014.04.003 (The 2015 AECT D&D Outstanding Journal Article Award, Indianapolis, Indiana; One of the Most Downloaded and Cited Articles in 2017)
Kim, M. (2013). Concept map engineering: Methods and tools based on the semantic relation approach. Educational Technology Research and Development, 61(6), 951-978. https://doi.org/10.1007/s11423-013-9316-3
Kim, M. (2012). Theoretically grounded guidelines for assessing learning progress: Cognitive changes in ill-structured complex problem-solving contexts. Educational Technology Research and Development, 60(4), 601-622. https://doi.org/10.1007/s11423-012-9247-4
Kim, M. (2012). Cross-validation study on methods and technologies to assess mental models in a complex problem-solving situation. Computers in Human Behavior, 28 (2), 703-717. https://doi.org/10.1016/j.chb.2011.11.018 (Outstanding Journal Article Award, 2012 AECT Annual Meeting, Louisville, KY; 2014 Editor’s Choice in Computers in Human Behavior)