"Our Mission is to Build on Theories of Learning and Instruction to Create Innovative Learning Environments that Maximize Learner Capacity to Achieve Learning Goals"

Hyunkyu Han joins as a graduate research associate.

Hyunkyu Han joins as a graduate research associate.

January 22, 2024

Let's welcom Hyunkyu, our new graduate research associate.  

Hyunkyu joins our lab. She earned a Master's in Educational Technology from Yonsei University, South Korea and an undergrad in Elementary Education from Gongju National University. Currently, she is an elementary school teacher in South Korea. Her research interests involve leveraging AI to create personalized learning environments that cater to the needs of learners and implementing AI-augmented active learning strategies.

Hyunkyu particularly focuses on the NSF-IUSE project in which she will lead the design of AI-augmented pre-classroom learning activities and strategies. The goal is to facilitate learners' smooth transition from pre-classroom to in-classroom learning and from self-paced to collaborative and hands-on learning in large-sized introductory physics courses.

Dr. Min Kyu Kim presented generative AI-based application development projects.

Dr. Min Kyu Kim presented generative AI-based application development projects.

December 8, 2023

The director, Dr. Min Kyu Kim, presented generative AI-based application development projects at the NSF-ALOE Use-Inspired AI meeting (Dec. 4, 2023) and the first  AI ALOE's Year 3 Executive Advisory Board Meeting (Dec. 8, 2023).

Dr. Kim introduced our two-track approach. We have continuously enhanced the current SMART (track 1), while concurrently developing a new application that fully harnesses generative AI LLMs (track 2). New features, empowered by generative AI, have been modularly developed, allowing some to be applied to SMART improvements. The W.R.I.T.E., Writing and Reasoning Intelligent Tutor for Education system, not only leverages SMART but also incorporates entirely different AI techniques, extending its applicability to various learning tasks. Our goal is to complete the initial WRITE development by the end of year 3.

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AI2 Lab's 2023 Thanksgiving Party at Dr. Kim's House

AI2 Lab's 2023 Thanksgiving Party at Dr. Kim's House

November 27, 2023

As part of our tradition, we had a great time at Dr. Kim's house during the 2023 Thanksgiving party! We celebrated our achievements throughout the year. During the lab feast event each semester, Dr. Kim showcased his culinary talents. This time, he prepared Korean-flavored roast beef along with several other dishes. Unfortunately, we realized that we hadn't taken a picture of the table. We couldn't wait to enjoy the delicious beef!

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AI2 members presented papers at 2023 AECT conference, October 15, 2023 -  October 19, 2023

AI2 members presented papers at 2023 AECT conference, October 15, 2023 - October 19, 2023

October 30, 2023

At the 2023 Association for Educational Communication and Technology (AECT) convention, the AI2 members—Lia, Jinho, Yoojin, and our director, Dr. Kim—presented research papers from the NSF AI ALOE and NSF SaTC projects. Our graduate associates achieved remarkable success in their presentations and subsequent Q&A sessions. Through our projects, we demonstrated AI's potential to transform education by designing and implementing AI-augmented teaching and learning experiences, such as personalized learning in higher education and adult education.  See the details of the papers below. 

Bae, Y., Kim, J., Haddadian, G., Davis, A., & Kim, M. (October 2023). The impact of an AI-based educational tool, with a focus on technology acceptance and metacognitive awareness of adult learners. The 2023 Association for Educational Communications and Technology (AECT) Conference, Orlando, FL. 

Abstract: This study examines whether AI-powered scaffolding during pre-classroom activities provides an advantage to students in an undergraduate-level Biology course. The study deployed Student Mental Model Analyzer for Research and Teaching (SMART), an AI-based formative assessment and feedback platform, to help students summarize reading materials. We observed the use of SMART had a positive effect on learners' perceived usefulness of technology, and the number of key concepts and density of summaries predicted learners' perceived technology usefulness. 

Haddadian, G., Kim, J., Bae, Y., & Kim, M. (October 2023). A Comprehensive Model of AI Literacy from a Developmental Perspective. The 2023 Association for Educational Communications and Technology (AECT) Conference, Orlando, FL. 

Abstract: We proposed a comprehensive model of AI literacy from a developmental perspective and demonstrate its potential as an analytic framework. Built upon the literature, we proposed a model that consists of cognitive and non-cognitive domains and supplemented our discussion with an empirical study which has used the model to analyze the AI literacy development in two college-level online courses. The empirical study demonstrates the potential of the proposed model to help research AI literacy development.

Haddadian, G., Panzade, P., Takabi, D., & Kim, M. (October 2023). A Design Study of Problem-Centered Instruction (PCI) for Private Artificial Intelligence (AI) Curriculum Development. The 2023 Association for Educational Communications and Technology (AECT) Conference, Orlando, FL. 

Abstract: This design study examines a pilot test that implemented PCI for private AI curriculum in Computer Science (CS) education to identify the strengths and weaknesses of the curricular activities. The results indicated the feedback received from both the instructor and the students was generally positive. However, the study identified several areas of concern that indicate the need for further improvement. The study concludes by presenting the lessons learned and recommendations for enhancing the curriculum.

Kim, J., Bae, Y., Haddadian, G., Morris, W., Crossley, S., Holmes, L., Stravelakis, J., & Kim, M. (October 2023). AI-augmented summarization: Impact on online adult learners’ concept learning, discussion quality, and achievement. The 2023 Association for Educational Communications and Technology (AECT) Conference, Orlando, FL. 

Abstract: This study aims to investigate how an AI-augmented summarization tool called the Student Mental Model Analyzer for Research and Teaching (SMART) impacts concept learning, discussion quality, and the achievement of adult learners. Findings from 21 participants in an undergraduate-level English course indicated that using SMART helped learners build a solid understanding of the readings and achieve higher end-of-year final scores. The results suggest the potential of using AI-augmented summarization tools to enhance learning outcomes.

Kim, J., Bae, Y., Haddadian, G., & Kim, M. (October 2023). Leveraging Machine Learning to Automatically Evaluate Cognitive Engagement in Asynchronous Online Discussions. The 2023 Association for Educational Communications and Technology (AECT) Conference, Orlando, FL. 

Abstract: This study focuses on developing machine learning models to automatically evaluate cognitive engagement in asynchronous online discussions. To this end, the bidirectional encoder representations from transformers (BERT) was finetuned and trained, resulting in an accuracy of 72%. The developed model was utilized to evaluate a previously uncoded dataset, which was then analyzed in terms of learning clusters and trajectories. This research demonstrates the potential of using BERT for cognitive engagement assessment.