@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{humburg_dragnic-cindric_hmelo-silver_glazewski_lester_danish_2024, title={Integrating Youth Perspectives into the Design of AI-Supported Collaborative Learning Environments}, volume={14}, ISSN={["2227-7102"]}, DOI={10.3390/educsci14111197}, abstractNote={This study highlights how middle schoolers discuss the benefits and drawbacks of AI-driven conversational agents in learning. Using thematic analysis of focus groups, we identified five themes in students’ views of AI applications in education. Students recognized the benefits of AI in making learning more engaging and providing personalized, adaptable scaffolding. They emphasized that AI use in education needs to be safe and equitable. Students identified the potential of AI in supporting teachers and noted that AI educational agents fall short when compared to emotionally and intellectually complex humans. Overall, we argue that even without technical expertise, middle schoolers can articulate deep, multifaceted understandings of the possibilities and pitfalls of AI in education. Centering student voices in AI design can also provide learners with much-desired agency over their future learning experiences.}, number={11}, journal={EDUCATION SCIENCES}, author={Humburg, Megan and Dragnic-Cindric, Dalila and Hmelo-Silver, Cindy E. and Glazewski, Krista and Lester, James C. and Danish, Joshua A.}, year={2024}, month={Nov} } @article{acosta_lee_bae_feng_rowe_glazewski_hmelo-silver_mott_lester_2024, title={Recognizing Multi-Party Epistemic Dialogue Acts During Collaborative Game-Based Learning Using Large Language Models}, ISSN={["1560-4306"]}, DOI={10.1007/s40593-024-00436-8}, abstractNote={Abstract Understanding students’ multi-party epistemic and topic based-dialogue contributions, or how students present knowledge in group-based chat interactions during collaborative game-based learning, offers valuable insights into group dynamics and learning processes. However, manually annotating these contributions is labor-intensive and challenging. To address this, we develop an automated method for recognizing dialogue acts from text chat data of small groups of middle school students interacting in a collaborative game-based learning environment. Our approach utilizes dual contrastive learning and label-aware data augmentation to fine-tune large language models’ underlying embedding representations within a supervised learning framework for epistemic and topic-based dialogue act classification. Results show that our method achieves a performance improvement of 4% to 8% over baseline methods in two key classification scenarios. These findings highlight the potential for automated dialogue act recognition to support understanding of how meaning-making occurs by focusing on the development and evolution of knowledge in group discourse, ultimately providing teachers with actionable insights to better support student learning.}, journal={INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE IN EDUCATION}, author={Acosta, Halim and Lee, Seung and Bae, Haesol and Feng, Chen and Rowe, Jonathan and Glazewski, Krista and Hmelo-Silver, Cindy and Mott, Bradford and Lester, James C.}, year={2024}, month={Nov} } @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{gupta_carpenter_min_mott_glazewski_hmelo-silver_lester_2023, title={Enhancing Stealth Assessment in Collaborative Game-Based Learning with Multi-task Learning}, volume={13916}, ISBN={["978-3-031-36271-2"]}, ISSN={["1611-3349"]}, DOI={10.1007/978-3-031-36272-9_25}, journal={ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2023}, author={Gupta, Anisha and Carpenter, Dan and Min, Wookhee and Mott, Bradford and Glazewski, Krista and Hmelo-Silver, Cindy E. and Lester, James}, year={2023}, pages={304–315} } @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} }