Dr Marie-Luce Bourguet, PhD

Profile

Dr. Marie-Luce Bourguet is a Senior Lecturer (Associate Professor) in Computer Science at the School of Electronic Engineering and Computer Science at Queen Mary University of London. She teaches on the Joint Programme between QMUL and Beijing University of Posts and Telecommunications (BUPT).

She is Director of the EECS Educational Scholarship Centre (ESC) and Co-Director of the Centre for Academic Inclusion in Science and Engineering (CAISE).

She is a Senior Fellow of the Higher Education Academy (HEA) and a Senior Member of IEEE.

Teaching

Multimedia Fundamentals (BUPT joint programme)

This module is an introduction to the representation, analysis and processing of digital multimedia. It covers topics such as sampling and quantisation, colour models, sound, image and video representations, compression and encoding, elements of psychoacoustics, elements of vision, JPEG, MPEG, MP3, and elements of digital broadcasting. The main methods of delivery are a mix of asynchronous activities (interactive videos, online quizzes, exercises), synchronous sessions (live lectures and tutorials) and labs.

Interactive Media Design and Production (BUPT joint programme)

The module provides principles and techniques of interactive media design and production using conventional media processing tools. It covers the following topics: elements of cognitive psychology, visual perception, human factors in multimedia design, design principles, and design process, animation and interactivity, colour perception, use of the media, usability and heuristic evaluation, image formats, digital and web video, principles of video interaction. JavaScript, HTML5, and CSS are also used to produce interactive multimedia content in the labs via mini-projects.

3D Graphics Programming Tools (BUPT joint programme)

Research

Research Interests:

I work at the intersection of HCI, multimedia signal processing, pervasive computing, artificial intelligence and user experience.

Currently, I am applying techniques from computer vision and multimodal interaction to the development of innovations in educational technology.

Publications

• Bourguet M-L (2024). Demonstrating the impact of study regularity on academic success using learning analytics. Proceedings of the 14th Learning Analytics and Knowledge Conference

  
  

  DOI: 10.1145/3636555.3636845

  
  

  QMRO:
• Savickaite S, Oyebisi J, Stockman T et al. . Instructional Design and Authoring of Accessible and Inclusive Extended Reality Learning Experiences.

  
  

  DOI: 10.59668/2033.18642

  
  

  QMRO:
• Bourguet ML, Pedrosa D, Peña-Rios A et al. (2024). Preface.

  
  

  DOI:

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/98403
• Oyebisi J, Bourguet M-L, Stockman T (2024). Work-in-Progress—Creating Immersive Learning Experiences with Generative AI: A Case Study in Dental Education. Academic Proceedings of the 10th International Conference of the Immersive Learning Research Network (iLRN2024)

  
  

  DOI: 10.56198/u6c0wofmv

  
  

  QMRO:
• Bourguet M-L, Omfalos E (2024). Work-in-Progress—Student’s Co-creation of Collaborative Learning Spaces on the Metaverse. Academic Proceedings of the 10th International Conference of the Immersive Learning Research Network (iLRN2024)

  
  

  DOI: 10.56198/u6c0w5uqt

  
  

  QMRO:
• Bourguet ML (2023). Methodology for the Participatory Design of a Learner-Facing Analytics Dashboard.

  
  

  DOI:

  
  

  QMRO:
• Shu Q, luan Z, Poslad S et al. (2023). MCAPR: Multi-modality Cross Attention for Camera Absolute Pose Regression.

  
  

  DOI: 10.1007/978-3-031-44210-0_35

  
  

  QMRO:
• Savickaite S, Bourguet M-L (2023). Immersive Learning and Inclusivity: Raising Awareness, Identifying Opportunities and Challenges, and Adapting Practice. Practitioner Proceedings of the 9th International Conference of the Immersive Learning Research Network (iLRN2023)

  
  

  DOI: 10.56198/itig2drk1

  
  

  QMRO:
• Bourguet M-L (2022). Measuring Learners’ Self-regulated Learning Skills from Their Digital Traces and Learning Pathways.

  
  

  DOI: 10.1007/978-3-031-16290-9_42

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/98401
• Bourguet M-L, Urakami J, Venture G (2022). Data-driven Behavioural and Affective Nudging of Online Learners: System Architecture and Design.

  
  

  DOI: 10.1007/978-3-031-11647-6_117

  
  

  QMRO: https://qmro.qmul.ac.uk/xmlui/handle/123456789/98384