Outputs (6)

Explainable artificial intelligence and advanced feature selection methods for predicting gas concentration in longwall mining (2025)
Journal Article
Chang, H., Wang, X., Cristea, A. I., Meng, X., Hu, Z., & Pan, Z. (2025). Explainable artificial intelligence and advanced feature selection methods for predicting gas concentration in longwall mining. Information Fusion, 118, Article 102976. https://doi.org/10.1016/j.inffus.2025.102976

Accurate prediction of gas concentrations at longwall mining faces is critical for safety production, yet current methods still face challenges in interpretability and reliability. This study aims to enhance prediction accuracy and model interpretabi... Read More about Explainable artificial intelligence and advanced feature selection methods for predicting gas concentration in longwall mining.

Reducing University Students’ Exam Anxiety via Mindfulness-Based Cognitive Therapy in VR with Real-Time EEG Neurofeedback (2024)
Presentation / Conference Contribution
Pan, Z., Cristea, A. I., & Li, F. W. B. (2024, July). Reducing University Students’ Exam Anxiety via Mindfulness-Based Cognitive Therapy in VR with Real-Time EEG Neurofeedback. Presented at AIED 2024: Artificial Intelligence in Education, Recife, Brazil

This research aims to develop and evaluate a novel approach to reduce university students’ exam anxiety and teach them how to better manage it using a personalised, emotion-informed Mindfulness-Based Cognitive Therapy (MBCT) method, delivered within... Read More about Reducing University Students’ Exam Anxiety via Mindfulness-Based Cognitive Therapy in VR with Real-Time EEG Neurofeedback.

Virtual Reality (VR) in Safety Education: A Case Study of Mining Engineering (2024)
Presentation / Conference Contribution
Chang, H., Pan, Z., & Cristea, A. I. (2024, July). Virtual Reality (VR) in Safety Education: A Case Study of Mining Engineering. Presented at AIED 2024: Artificial Intelligence in Education, Recife, Brazil

Safety education and training are vital in the mining industry. However, traditional training relies on passive modalities, such as lectures, videos and brochures. These suffer from sever limitations - poor reproducibility, inefficient resource utili... Read More about Virtual Reality (VR) in Safety Education: A Case Study of Mining Engineering.

Towards Neuro-Enhanced Education: A Systematic Review of BCI-Assisted Development for Non-academic Skills and Abilities (2024)
Presentation / Conference Contribution
Pan, Z., & Cristea, A. I. (2024, June). Towards Neuro-Enhanced Education: A Systematic Review of BCI-Assisted Development for Non-academic Skills and Abilities. Presented at ITS 2024: Generative Intelligence and Intelligent Tutoring Systems, Thessaloniki, Greece

Students’ success in the 21st century demands not only strong academic skills but also well-developed Non-academic Skills and Abilities (NaSAs) such as critical thinking, concentration, and emotion regulation. The emerging field of Brain-Computer Int... Read More about Towards Neuro-Enhanced Education: A Systematic Review of BCI-Assisted Development for Non-academic Skills and Abilities.

Fine-grained Main Ideas Extraction and Clustering of Online Course Reviews (2022)
Book Chapter
Xiao, C., Shi, L., Cristea, A., Li, Z., & Pan, Z. (2022). Fine-grained Main Ideas Extraction and Clustering of Online Course Reviews. In M. Rodrigo, N. Matsuda, A. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education (294-306). Springer, Cham. https://doi.org/10.1007/978-3-031-11644-5_24

Online course reviews have been an essential way in which course providers could get insights into students’ perceptions about the course quality, especially in the context of massive open online courses (MOOCs), where it is hard for both parties to... Read More about Fine-grained Main Ideas Extraction and Clustering of Online Course Reviews.

SimStu-Transformer: A Transformer-Based Approach to Simulating Student Behaviour (2022)
Book Chapter
Li, Z., Shi, L., Cristea, A., Zhou, Y., Xiao, C., & Pan, Z. (2022). SimStu-Transformer: A Transformer-Based Approach to Simulating Student Behaviour. In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (348-351). Springer, Cham. https://doi.org/10.1007/978-3-031-11647-6_67

Lacking behavioural data between students and an Intelligent Tutoring System (ITS) has been an obstacle for improving its personalisation capability. One feasible solution is to train “sim students”, who simulate real students’ behaviour in the ITS.... Read More about SimStu-Transformer: A Transformer-Based Approach to Simulating Student Behaviour.