AI Detects Math Anxiety Through Student Inputs and Adapts Feedback
Understanding Math Anxiety and the Role of AI
Math anxiety is a significant challenge for students around the world. It is an emotional response characterized by fear, tension, and apprehension when faced with mathematical problems or tests. In some cases, this anxiety can be so severe that it limits a student’s learning and performance. While personalized support is widely recognized as the most effective way to address math anxiety, many teachers struggle to provide this level of attention in busy classrooms.
New research from Adelaide University suggests that artificial intelligence (AI) could play a crucial role in helping students overcome math anxiety. By analyzing a student’s inputs and identifying signs of anxiety or disengagement during learning, AI systems can adapt their responses to help counteract negative emotional experiences associated with math before these feelings escalate.
How AI Can Help Address Math Anxiety
Lead researcher Dr. Florence Gabriel explains that AI has the potential to transform how math anxiety is supported by offering timely, tailored interventions. These interventions can guide students through learning and build their well-being.
“Tailored AI models have the potential to change the way students engage with math,” Dr. Gabriel says. “By helping students set realistic, motivating goals aligned with their individual capabilities, and by responding with encouragement when signs of frustration appear, AI can help students feel more competent, motivated, and in control of their learning.”
The research proposes a new model of mathematics learning where emotional development is treated as central to the design of AI rather than secondary. Key recommendations suggest that AI could support learning by:
- Tailoring learning activities: Adjusting the difficulty of math tasks in real time to balance challenge and success.
- Providing emotionally intelligent feedback: Recognizing patterns of frustration or disengagement and responding in constructive, personalized ways.
- Supporting student autonomy: Enabling goal-setting and personalized learning pathways that give students greater control.
- Helping teachers: Offering real-time insights to support more targeted emotional and instructional interventions for students who need it most.
The Broader Implications of AI in Education
More than a third of adults and children experience math anxiety. Those with the greatest math anxiety can perform almost four years behind those with lower levels of math anxiety. This highlights the urgent need for solutions that can effectively address this issue.
Co-researcher Dr. John Kennedy emphasizes the need to develop and refine AI models that are better suited to the realities of education. “Current AI models are trained to provide users with answers they’re happy with, but this can bypass the cognitive processes of learning,” Dr. Kennedy says. “When students rely on tools that simply generate answers, they only learn how to prompt the system rather than how to think through a problem.”
Dr. Kennedy adds that there is a need to move beyond the basic use of AI and towards tools designed from the ground up for education. These tools should understand local contexts, diverse learning goals, and the emotional dimensions of learning. This requires a shift in the way researchers work: away from asking what AI can do for educators, and towards asking how educators can shape AI for the benefit of all learners.
The Future of Educational AI
Effective educational AI should not only break problems into simpler steps but also tailor the type of hints it gives and the emotional tone of its responses to support positive attitudes to learning. That might include recognizing delays in responses, deleted text, or patterns of hesitation during problem-solving. But this requires a different approach to training the AI compared to what is commonly used today.
“When AI can adapt to a learner’s emotional state as well as their cognitive needs, it brings us closer to truly supportive and intuitive learning tools,” Dr. Kennedy explains.
A Working Example of AI in the Classroom
The research team has made available an AI Math tutor that provides a working example of what AI can currently do in the classroom using simple prompts. This tool demonstrates the potential of AI to enhance learning and support students facing math anxiety.
For more information, you can refer to the study titled “Pragmatic AI in education and its role in mathematics learning and teaching” published in npj Science of Learning.
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