IIT Madras researchers identify physiological markers to predict and manage test anxiety in students

This study examines how the brain and heart interact in students who experience anxiety during exams, providing a scientific foundation for early identification and the development of personalised coping strategies. According to the National Council of Educational Research and Training (NCERT, 2022), test anxiety affects an estimated 81 per cent of Indian students.

This condition can significantly impair academic performance and long-term mental health. While some students can perform well under pressure, others may resort to avoidance behaviour, finding it difficult to cope effectively.

Venkatesh Balasubramanian from the Department of Engineering Design at IIT Madras led the research team to investigate the reasons behind this phenomenon, emphasizing the importance of objective physiological data over self-reported perceptions.

“They discovered that when the brain-heart communication network breaks down during stress, certain students are more likely to experience heightened anxiety and avoidance, revealing a clear biological distinction between adaptive and maladaptive test responses,” he told PTI.

“The study’s breakthrough lies in integrating two physiological markers: Frontal Alpha Asymmetry (FAA)—a brain-based indicator of emotional regulation—and Heart Rate Variability (HRV)—a measure of the heart’s adaptive control. Together, these signals help identify students predisposed to anxiety,” he added.

Balasubramanian explained that the team discovered those with a negative FAA pattern exhibited significantly weaker heart regulation during stress, indicating that their predisposition to anxiety could impair the heart’s ability to maintain balance in evaluative situations.

“This nuanced understanding transforms how we view academic stress—not as a purely psychological issue, but as one grounded in measurable physiological interactions,” he said.

Swathy Parameswaran, Research Scholar, IIT Madras, informed that these insights open up immense possibilities for practical applications. By training artificial intelligence systems on these psycho-physiological markers, it could soon become possible to develop non-invasive, real-time monitoring tools that alert educators and mental health professionals to students at risk, without waiting for visible signs of distress.

“The findings also support the design of personalised stress management and behavioural interventions that could be embedded within school and university wellness programs, offering proactive support rather than reactive treatment,” she said.

Although preliminary, the study, conducted with 52 participants, marks a critical step towards integrating neuroscience with educational psychology.

The team now aims to scale the research by involving larger and more diverse participant groups and exploring additional factors like sleep patterns and activity levels to refine predictive models. Advanced techniques, such as EEG-based connectivity mapping, will also be employed to deepen the understanding of heart-brain dynamics under stress.

(with inputs from PTI)