Emerging research technologies in the field of education are aimed at applying contemporary scientific methods to facilitate the generation of diverse research data and thereby augmenting research precision, operational effectiveness and efficiency. These emerging educational research technologies facilitate a deeper understanding of teaching and learning processes and cognitive characteristics. By analyzing a wide spectrum of data, they offer valuable insights for instructional practices, thereby contributing to better alignment with the societal needs and enabling the provision of more effective and personalized educational planning.

    The special issue focuses on how mathematics education can harness emerging research technologies and aims to collect empirical or theoretical research papers in various domains related to mathematics education. We seek to enrich the understanding of issues such as teacher training and professional development, on-site teaching, and student cognitive learning. The emerging educational research technologies that we invite for submission encompass the following, but not excluding, areas:   

1.  Neuroscience-Related Technologies: These technologies involve the use of Event-Related Potential (ERP) techniques for monitoring brainwave activities through electroencephalography (EEG) and the use of functional Magnetic Resonance Imaging (fMRI) to understand brain activities by measuring changes in regional cerebral blood oxygenation using magnetic fields and radio waves.

2. Eye-Tracking Research Technologies: This category comprises tracking and recording eye movements to gain insights into visual processing, attention distribution, and factors related to vision, cognition, interests, and decision-making when individuals engage with graphics, text, or other types of visual information.

3. Virtual Reality (VR) and Augmented Reality (AR): These technologies offer immersive learning experiences, such as geometry instruction in virtual reality, or support for students with learning disabilities in their mathematical learning.

4. Machine Learning and Artificial Intelligence: These technologies are used to design personalized learning packages and automated assessments.

5. Big Data Analytics: By utilizing extensive educational databases, these technologies help construct mathematics models and identify trends, offering improved references for educational planning and policies.

    We welcome submissions of empirical research, literature reviews, or commentary articles that explore the impact of emerging research technologies on mathematics education. For comprehensive details regarding manuscript submission, please refer to the submission requirements and writing guidelines provided by this journal.