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Using an AI-Based Chatbot to Support the Learning of Algebraic Factoring.

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Title: Using an AI-Based Chatbot to Support the Learning of Algebraic Factoring.
Authors: Amezcua, Mirelle Zavala1, Aguilar, Mario Sánchez1
Source: Ohio Journal of School Mathematics. Spring2026, Vol. 102, p48-59. 12p.
Subject Terms: *Educational technology, *Self-regulated learning, *Intelligent tutoring systems, *Educational support, *Academic support programs, *Engineering students, Chatbots, Factorization
Abstract: This article reports on the design, implementation, and evaluation of FACTY, a GPT-based chatbot developed to support undergraduate students in learning algebraic factoring. The study involved ten first-year engineering students who interacted with FACTY over four stages, including diagnostic and final assessments, autonomous practice, and post-intervention interviews. Guided by a framework of feedback levels in mathematics instruction, the analysis examines the nature of FACTY's responses and their relationship to student learning outcomes. Findings indicate that the chatbot predominantly provides process-level and self-regulation-level feedback, both of which are acknowledged in the literature as critical for fostering deep and autonomous learning. Two case studies illustrate contrasting results: one student achieved substantial improvement, while another made limited progress due to foundational gaps in algebra. Interview data revealed positive perceptions of FACTY's constant availability, adaptability, and nonjudgmental interaction style. The study concludes that FACTY can serve as a complement to classroom instruction, particularly when integrated with teacher oversight and used to promote critical engagement with AI-generated feedback. [ABSTRACT FROM AUTHOR]
Copyright of Ohio Journal of School Mathematics is the property of Ohio Council of Teachers of Mathematics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: <searchLink fieldCode="JN" term="%22Ohio+Journal+of+School+Mathematics%22">Ohio Journal of School Mathematics</searchLink>. Spring2026, Vol. 102, p48-59. 12p.
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  Data: This article reports on the design, implementation, and evaluation of FACTY, a GPT-based chatbot developed to support undergraduate students in learning algebraic factoring. The study involved ten first-year engineering students who interacted with FACTY over four stages, including diagnostic and final assessments, autonomous practice, and post-intervention interviews. Guided by a framework of feedback levels in mathematics instruction, the analysis examines the nature of FACTY's responses and their relationship to student learning outcomes. Findings indicate that the chatbot predominantly provides process-level and self-regulation-level feedback, both of which are acknowledged in the literature as critical for fostering deep and autonomous learning. Two case studies illustrate contrasting results: one student achieved substantial improvement, while another made limited progress due to foundational gaps in algebra. Interview data revealed positive perceptions of FACTY's constant availability, adaptability, and nonjudgmental interaction style. The study concludes that FACTY can serve as a complement to classroom instruction, particularly when integrated with teacher oversight and used to promote critical engagement with AI-generated feedback. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Ohio Journal of School Mathematics is the property of Ohio Council of Teachers of Mathematics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Spring2026
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