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ERIC Number: EJ1488784
Record Type: Journal
Publication Date: 2025
Pages: 35
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-2199-3246
EISSN: EISSN-2199-3254
Available Date: 2024-10-16
Addressing Design Challenges When Integrating Machine Learning with a Digital Annotation System to Examine Student Proportional Reasoning
Alden J. Edson1; Ashley Fabry1; Ahmad Wachidul Kohar1; Leslie Bondaryk2; Elizabeth Difanis Phillips1
Digital Experiences in Mathematics Education, v11 n1 p42-76 2025
This article reports on a novel approach to integrate artificial intelligence into a digital collaborative platform embedded with a problem-based mathematics curriculum. Using design research methodologies, we developed a new "proof-of-concept" design feature called "student proportional reasoning arrows (SPArrows)." SPArrows enable students and teachers to annotate their proportional reasoning through visual notes on their documented work. SPArrows and associated teacher- and researcher-generated tagging will generate data required to train machine learning to analyze students' proportional reasoning in the digital platform. In this article, we report on the emergent design challenges that led to the development of the digital annotation system. We connect these emergent challenges to the underlying design principles of the digital annotation system for their potential to improve the teaching and learning of proportional reasoning. The integration of the SPArrows digital annotation system into a digital collaborative platform represents an important advancement in the integration of artificial intelligence to support and enhance mathematics education, particularly in the domain of proportional reasoning.
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link-springer-com.bibliotheek.ehb.be/
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Authoring Institution: N/A
Grant or Contract Numbers: 2200763
Author Affiliations: 1Michigan State University, East Lansing, MI, USA; 2The Concord Consortium, Concord, MA, USA