"Our Mission is to Build on Theories of Learning and Instruction to Create Innovative Learning Environments that Maximize Learner Capacity to Achieve Learning Goals"
Jinho Kim and Lia Haddadian present lastest work at AI-ALOE
August 19, 2022
On August 19, 2022, there was an National Science Foundation (NSF) visit meeting at AI-ALOE with NSF Program Director, James Dolon. With it being approximately a year since the start of the AI-ALOE project, researchers and graduate students discussed their work with agendas such as virtual assistants, participatory design, technology infrasturcure, self-directed learning, learning analytics, personalized learnning, machine teaching and mutual theory of mind.
Our two project GRAs, Jinho Kim and Lia Haddadian attended in-person to present the findings. At the morning session, Jinho spoke about how the Student Mental Model Analyzer for Research and Teaching (SMART) has been implemented in the pervious semester. During the afternoon session, Jinho presented how textul data is analyzed and evaulated in SMART. Lia showed how SMART can be used as a personalized learning tool.
Book Chapter Publication
July 19, 2022
Our graduate research associate, Jinho Kim, has a newly published book chapter discussing the effects of the International Baccalaureate Diploma Program (IBDP) on whole-person development.
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.
Link to Chapter Introduction
In Asia, the International Baccalaureate Diploma Program (IBDP) is gradually perceived as a pedagogically progressive, internationally validated, high-quality curriculum that is designed to support whole-child/youth development. While there is a growing, positive sentiment about the IBDP in conjunction with whole-person development, little is known about how successful the IBDP is in facilitating whole-person development in school. In this chapter, we review what research tells us about how the IBDP plays out in whole-person development. We found that the research literature largely supports the proposition that the IBDP contributes to whole-person development by facilitating students’ creativity, critical thinking skills, international mindedness, communication, collaboration, and self-management skills. Especially when compared with non-IBDP students and/or graduates, this tendency seems more evident. Our review suggests that the IBDP as a pedagogically well-balanced curriculum may work for whole-person development across different cultural contexts, including Asia. In this regard, we conclude that the reform idea of introducing the IBDP to local school systems in some countries in Asia is worth pursuing. At the same time, however, we provide several caveats for the reform idea, based on the limitations of the existing research literature.
NSF SaTC Project: Pilot Test on Saturday, June 25, 2022
June 25, 2022
We pilot-tested the Private AI curriculum at the conference room, 25 Park Place, on Saturday, June 25, 2022. 29 undergraduate and graduate CS students participated in the pilot test. Our two project GRAs, Prajwal Panzade and Lia Haddadian, developed the test module, Privacy-Preserving Machine Learning (PPML), using Differential Privacy with the focus, Differential Privacy & TensorFlow. Akshita Maradapu Vera Venkata sai, a 4th-year Ph.D. student in the Department of Computer Science at Georgia State University, was recruited to lecture the module.
The CS curriculum “Private AI” consists of 10 modules that teach students to use specific techniques to address various privacy challenges in AI systems. We designed each module based on the principles of Problem-Centered Instruction (PCI) that feature a series of learning activities: real-world problem scenarios, instructor-led instruction, individual assignments supported by worked examples, crowd-based hands-on lab activities in pairs, and debriefing lessons learned. The data collection includes pre-and post-test, a survey, video recordings of hands-on lab activities, audio recordings of the debriefing session, instructor interview, and student interviews.
Min Kyu Kim and Nam Ju Kim presented at the 16th International Conference of the Learning Sciences
June 9, 2022
Co-directors, Drs. Min Kyu Kim and Nam Ju Kim presented a short paper at the 16th International Conference of the Learning Sciences on June 9th, 2022. Due to the pandemic, the ICLS meeting was held virtually. They had developed the initial work into two journal publications since the proposal submission to ICSL. (This post includes two published articles associated).
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.
Despite the importance of writing academic arguments, instructors often lack enough time and knowledge to provide prompt support adaptive to individual students' discipline-specific arguments. AI techniques can enable automated and adaptive educational scaffolding. In this study, we created a test version of the Artificial Intelligent-Supported Scaffolding (AISS) system that provides scaffolds in the form of alternative writing examples that human experts would write. Our mix-methods data gathered from 14 students enrolled in two sections of the same graduate-level online course revealed that the students leveraged AI-generated scaffolds to build a more substantial claim with elaborated ideas in a cohesive text structure. The current study's findings demonstrated the potential of AI to provide personalized scaffolding for writing academic arguments.
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. DOI: 10.1080/02602938.2022.2042792