Staff profile

Biography:

Ms. Khulood Alharbi is a PhD student in the Department of Computer Science at Durham University. She joined the Innovative Computing Group in April 2019. Her research focus is identifying and tracking behaviour changes using deep learning algorithms and the their impact on pedagogical efficacy. It includes descriptive data analytics, predictive, as well as prescriptive data analytics. 

• Machine learning
• Deep learning
• Learning Analytics
• E-learning

Conference Paper

• Alharbi, K., Cristea, A. I., Shi, L., Tymms, P., & Brown, C. (2021). Agent-based Classroom Environment Simulation: the Effect of Disruptive Schoolchildren’s Behaviour versus Teacher Control over Neighbours. In I. Roll, M. Danielle, S. Sergey, L. Rose, & D. Vania (Eds.), Artificial Intelligence in Education Lecture Notes in Computer Science (48-53). https://doi.org/10.1007/978-3-030-78270-2_8
• Alharbi, K., Cristea, A. I., Shi, L., Tymms, P., & Brown, C. (2021). Agent-based Simulation of the Classroom Environment to Gauge the Effect of Inattentive or Disruptive Students. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (211-223). https://doi.org/10.1007/978-3-030-80421-3_23
• Alharbi, K., Alrajhi, L., Cristea, A. I., Bittencourt, I. I., Isotani, S., & James, A. (2020). Data-Driven Analysis of Engagement in Gamified Learning Environments: A Methodology for Real-Time Measurement of MOOCs. In V. Kumar, & C. Troussas (Eds.), Intelligent Tutoring Systems (142-151). https://doi.org/10.1007/978-3-030-49663-0_18