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Conrad Borchers; Jeroen Ooge; Cindy Peng; Vincent Aleven – Grantee Submission, 2025
Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Learner Controlled Instruction, Learning Analytics

Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages

Devika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics

Ha Tien Nguyen; Conrad Borchers; Meng Xia; Vincent Aleven – Grantee Submission, 2024
Intelligent tutoring systems (ITS) can help students learn successfully, yet little work has explored the role of caregivers in shaping that success. Past interventions to support caregivers in supporting their child's homework have been largely disjunct from educational technology. The paper presents prototyping design research with nine middle…
Descriptors: Middle School Mathematics, Intelligent Tutoring Systems, Caregivers, Caregiver Attitudes
Mingyu Feng; Neil Heffernan; Kelly Collins; Cristina Heffernan; Robert F. Murphy – Grantee Submission, 2023
Math performance continues to be an important focus for improvement. The most recent National Report Card in the U.S. suggested student math scores declined in the past two years possibly due to COVID-19 pandemic and related school closures. We report on the implementation of a math homework program that leverages AI-based one-to-one technology,…
Descriptors: Homework, Artificial Intelligence, Computer Assisted Instruction, Feedback (Response)
Husni Almoubayyed; Rae Bastoni; Susan R. Berman; Sarah Galasso; Megan Jensen; Leila Lester; April Murphy; Mark Swartz; Kyle Weldon; Stephen E. Fancsali; Jess Gropen; Steve Ritter – Grantee Submission, 2023
We present a recent randomized field trial delivered in Carnegie Learning's MATHia's intelligent tutoring system to a sample of 12,374 learners intended to test whether rewriting content in a selection of so-called "word problems" improves student mathematics performance within this content, especially among students who are emerging as…
Descriptors: Word Problems (Mathematics), Intelligent Tutoring Systems, Mathematics Achievement, English Learners
Ethan Prihar; Morgan Lee; Mia Hopman; Adam Tauman Kalai; Sofia Vempala; Allison Wang; Gabriel Wickline; Aly Murray; Neil Heffernan – Grantee Submission, 2023
Large language models have recently been able to perform well in a wide variety of circumstances. In this work, we explore the possibility of large language models, specifically GPT-3, to write explanations for middle-school mathematics problems, with the goal of eventually using this process to rapidly generate explanations for the mathematics…
Descriptors: Mathematics Instruction, Teaching Methods, Artificial Intelligence, Middle School Students
Amy Adair; Ellie Segan; Janice Gobert; Michael Sao Pedro – Grantee Submission, 2023
Developing models and using mathematics are two key practices in internationally recognized science education standards, such as the Next Generation Science Standards (NGSS). However, students often struggle with these two intersecting practices, particularly when developing mathematical models about scientific phenomena. Formative…
Descriptors: Artificial Intelligence, Mathematical Models, Science Process Skills, Inquiry
Benjamin D. Nye; Aaron Shiel; Ibrahim Burak Olmez; Anirudh Mittal; Jason Latta; Daniel Auerbach; Yasemin Copur-Gencturk – Grantee Submission, 2021
Despite the critical role of teachers in the educational process, few advanced learning technologies have been developed to support teacher-instruction or professional development. This lack of support is particularly acute for middle school math teachers, where only 37% felt well prepared to scaffold instruction to address the needs of diverse…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Faculty Development, Abstract Reasoning
Christine Mulhern – Grantee Submission, 2020
Choosing where to apply to college is a complex problem with long-term consequences, but many students lack the guidance necessary to make optimal choices. I show that a technology which provides low-cost personalized college admissions information to over forty percent of high schoolers significantly alters college choices. Students shift…
Descriptors: College Choice, College Admission, Artificial Intelligence, Computer Software
Holstein, Kenneth; McLaren, Bruce M.; Aleven, Vincent – Grantee Submission, 2019
Involving stakeholders throughout the creation of new educational technologies can help ensure their usefulness and usability in real-world contexts. However, given the complexity of learning analytics (LA) systems, it can be challenging to meaningfully involve non-technical stakeholders throughout their design and development. This article…
Descriptors: Learning Analytics, Technology Uses in Education, Artificial Intelligence, Stakeholders
John Sabatini; Arthur C. Graesser; John Hollander; Tenaha O'Reilly – Grantee Submission, 2023
We argue in this paper that there is currently no adequate theoretical framework or model that spans the twelve odd year trajectory from non-reader to proficient reader, nor addresses fine-grain skill acquisition, mastery and integration. The target construct itself, reading proficiency, as often operationalized as an endpoint of formal secondary…
Descriptors: Literacy Education, Intelligent Tutoring Systems, Decision Making, Standards
Walter L. Leite; Samrat Roy; Nilanjana Chakraborty; George Michailidis; A. Corinne Huggins-Manley; Sidney K. D'Mello; Mohamad Kazem Shirani Faradonbeh; Emily Jensen; Huan Kuang; Zeyuan Jing – Grantee Submission, 2022
This study presents a novel video recommendation system for an algebra virtual learning environment (VLE) that leverages ideas and methods from engagement measurement, item response theory, and reinforcement learning. Following Vygotsky's Zone of Proximal Development (ZPD) theory, but considering low affect and high affect students separately, we…
Descriptors: Artificial Intelligence, Video Technology, Technology Uses in Education, Program Effectiveness
Chen, Zhanwen; Li, Shiyao; Rashedi, Roxanne; Zi, Xiaoman; Elrod-Erickson, Morgan; Hollis, Bryan; Maliakal, Angela; Shen, Xinyu; Zhao, Simeng; Kunda, Maithilee – Grantee Submission, 2020
Modern social intelligence includes the ability to watch videos and answer questions about social and theory-of-mind-related content, e.g., for a scene in "Harry Potter," "Is the father really upset about the boys flying the car?" Social visual question answering (social VQA) is emerging as a valuable methodology for studying…
Descriptors: Visual Stimuli, Questioning Techniques, Social Cognition, Video Technology
Michelle P. Banawan; Jinnie Shin; Tracy Arner; Renu Balyan; Walter L. Leite; Danielle S. McNamara – Grantee Submission, 2023
Academic discourse communities and learning circles are characterized by collaboration, sharing commonalities in terms of social interactions and language. The discourse of these communities is composed of jargon, common terminologies, and similarities in how they construe and communicate meaning. This study examines the extent to which discourse…
Descriptors: Algebra, Discourse Analysis, Semantics, Syntax
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