AI systems could identify math anxiety from student inputs and change feedback
18 Tweet Share Email February 3, 2026 AI systems could identify math anxiety from student inputs and change feedback by University of Adelaide edited by Stephanie Baum , reviewed by Andrew Zinin Stephanie Baum Scientific Editor Meet our editorial team Behind our editorial process Andrew Zinin Lead Editor Meet our editorial team Behind our editorial process Editors' notes This article has been reviewed according to Science X's editorial process and policies .
Topics & Tags
Analysis & Perspectives
Transforming Assessment Paradigms for Authenticity and Rigor in the AI Era
This article explores the essential shift needed in assessment methodologies to ensure they remain authentic and rigorous. It examines how educators can innovate assessment paradigms to meet the challenges and opportunities presented by the pervasive influence of artificial intelligence.
Designing a Comprehensive K-12 AI Literacy Framework for Students and Educators
This article details the design of a comprehensive K-12 AI literacy framework. It addresses the crucial need to equip both students and educators with fundamental AI knowledge, skills, and ethical understanding. The framework aims to seamlessly integrate AI concepts into the curriculum, fostering informed and responsible engagement with artificial intelligence.
Related Articles
Unrestricted generative AI harms high school math learning by acting as a crutch
PsyPost Mental Health Social Psychology Cognitive Science Neuroscience About No Result View All Result Join My Account PsyPost No Result View All Result Home Exclusive Artificial Intelligence Unrestricted generative AI harms high school math learning by acting as a crutch by Eric W. Dolan April 21, 2026 Reading Time: 5 mins read Share on Twitter Share on Facebook A recent study published in the Proceedings of the National Academy of Sciences suggests that giving high school students unrestricted access to
.png)
New Study Shows Pros vs. Cons of Using ChatGPT in Research Process
Search for: Submit Submit Search Submit --> Webmail UCD Access Canvas Quick Links Tools & Resources Events Calendar Newsroom Strauss Health Sciences Library Department A-Z Directory Campus Directory Leadership Faculty & Staff Resources Supporter & Alumni Resources Student Resources Mental Health Resources Campus Map University Policies Give Now CU Campuses CU Anschutz CU Boulder CU Colorado Springs CU Denver CU System CU Online CU Anschutz School of Dental Medicine Graduate School School of Medicine College of Nursing Skaggs School of
Modeling K-12 teachers’ continuance intention to use generative AI: influencing factors and a hybrid SEM-ANN approach
ORIGINAL RESEARCH article Front. Educ. , 13 April 2026 Sec. Teacher Education Volume 11 - 2026 | https://doi.org/10.3389/feduc.2026.1755301 Modeling K-12 teachers’ continuance intention to use generative AI: influencing factors and a hybrid SEM-ANN approach T M Tanjun Ma 1,2 W Z Wenlan Zhang 3 * 1. Faculty of Teacher Development, Shaanxi Normal University, Xi'an, China 2. Xi'an No. 66 Middle School, Xi'an, China 3. Faculty of Education, Shaanxi Normal University, Xi'an, China See more Article metrics View details Abstract K-12