@article{mott_gupta_vandenberg_chakraburty_ottenbreit-leftwich_hmelo-silver_scribner_lee_glazewski_lester_2024, title={AI Planning is Elementary: Introducing Young Learners to Automated Problem Solving}, DOI={10.1145/3649405.3659503}, journal={PROCEEDINGS OF THE 2024 CONFERENCE INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, VOL 2, ITICSE 2024}, author={Mott, Bradford and Gupta, Anisha and Vandenberg, Jessica and Chakraburty, Srijita and Ottenbreit-Leftwich, Anne and Hmelo-Silver, Cindy and Scribner, Adam and Lee, Seung and Glazewski, Krista and Lester, James}, year={2024}, pages={811–811} }
 @article{feng_bae_glazewski_hmelo-silver_brush_mott_lee_lester_2024, title={Exploring facilitation strategies to support socially shared regulation in a problem-based learning game}, volume={27}, ISSN={["1436-4522"]}, DOI={10.30191/ETS.202407_27(3).SP08}, number={3}, journal={EDUCATIONAL TECHNOLOGY & SOCIETY}, author={Feng, Chen and Bae, Haesol and Glazewski, Krista and Hmelo-Silver, Cindy E. and Brush, Thomas A. and Mott, Bradford W. and Lee, Seung Y. and Lester, James C.}, year={2024}, month={Jul}, pages={318–334} }
 @article{katuka_chakraburty_lee_dhama_earle-randell_celepkolu_boyer_glazewski_hmelo-silver_mcklin_2024, title={Integrating Natural Language Processing in Middle School Science Classrooms: An Experience Report}, DOI={10.1145/3626252.3630881}, abstractNote={With the increasing prevalence of large language models (LLMs) such as ChatGPT, there is a growing need to integrate natural language processing (NLP) into K-12 education to better prepare young learners for the future AI landscape. NLP, a sub-field of AI that serves as the foundation of LLMs and many advanced AI applications, holds the potential to enrich learning in core subjects in K-12 classrooms. In this experience report, we present our efforts to integrate NLP into science classrooms with 98 middle school students across two US states, aiming to increase students' experience and engagement with NLP models through textual data analyses and visualizations. We designed learning activities, developed an NLP-based interactive visualization platform, and facilitated classroom learning in close collaboration with middle school science teachers. This experience report aims to contribute to the growing body of work on integrating NLP into K-12 education by providing insights and practical guidelines for practitioners, researchers, and curriculum designers.}, journal={PROCEEDINGS OF THE 55TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, SIGCSE 2024, VOL. 1}, author={Katuka, Gloria Ashiya and Chakraburty, Srijita and Lee, Hyejeong and Dhama, Sunny and Earle-Randell, Toni and Celepkolu, Mehmet and Boyer, Kristy Elizabeth and Glazewski, Krista and Hmelo-Silver, Cindy and McKlin, Tom}, year={2024}, pages={639–645} }
 @article{bae_feng_glazewski_hmelo-silver_chen_mott_lee_lester_2023, title={Co-designing a Classroom Orchestration Assistant for Game-based PBL Environments}, ISSN={["1559-7075"]}, DOI={10.1007/s11528-023-00903-4}, journal={TECHTRENDS}, author={Bae, Haesol and Feng, Chen and Glazewski, Krista and Hmelo-Silver, Cindy E. and Chen, Yuxin and Mott, Bradford W. and Lee, Seung Y. and Lester, James C.}, year={2023}, month={Nov} }
 @article{ottenbreit-leftwich_glazewski_hmelo-silver_jantaraweragul_chakraburty_jeon_scribner_lee_mott_lester_2023, title={Is Elementary AI Education Possible?}, DOI={10.1145/3545947.3576308}, abstractNote={As artificial intelligence (AI) technology becomes increasingly pervasive, it is critical that students recognize AI and how it can be used. There is little research exploring learning capabilities of elementary students and the pedagogical supports necessary to facilitate students' learning. PrimaryAI was created as a 3rd-5th grade AI curriculum that utilizes problem-based and immersive learning within an authentic life science context through four units that cover machine learning, computer vision, AI planning, and AI ethics. The curriculum was implemented by two upper elementary teachers during Spring 2022. Based on pre-test/post-test results, students were able to conceptualize AI concepts related to machine learning and computer vision. Results showed no significant differences based on gender. Teachers indicated the curriculum engaged students and provided teachers with sufficient scaffolding to teach the content in their classrooms. Recommendations for future implementations include greater alignment between the AI and life science concepts, alterations to the immersive problem-based learning environment, and enhanced connections to local animal populations.}, journal={PROCEEDINGS OF THE 54TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, VOL 2, SIGCSE 2023}, author={Ottenbreit-Leftwich, Anne and Glazewski, Krista and Hmelo-Silver, Cindy and Jantaraweragul, Katie and Chakraburty, Srijita and Jeon, Minji and Scribner, Adam and Lee, Seung and Mott, Bradford and Lester, James}, year={2023}, pages={1364–1364} }