Publications

My research focuses on Artificial Intelligence in Education (AIED), learning analytics, affective computing, and adaptive systems. I develop and evaluate AI models that measure learner engagement, motivation, and performance, translating cognitive and affective theory into deployable learning technologies.

My work combines empirical experimentation, statistical modelling, and system development, contributing both foundational research and applied AI systems across education, serious games, and multimodal learning environments.

Selected Publications in AI in Education
  1. de Freitas, S., Rebolledo-Mendez, G., Liarokapis, F., & Magoulas, G. (2010). Learning as immersive experiences: Using the four-dimensional framework for designing and evaluating immersive learning experiences in a virtual world. British Journal of Educational Technology, 41(1), 69-85. [584 citations]

Introduced and empirically validated the four-dimensional framework for designing and evaluating immersive learning experiences, providing a structured methodology to analyse complex human interaction in virtual environments.

  1. Rebolledo-Mendez, G., Dunwell, I., & Martínez-Mirón, E.A. (2009). Assessing NeuroSky’s usability to detect attention levels in an assessment exercise. Human-Computer Interaction: New Trends, 13th Int. Conf., 2009, pp. 252. [261 citations]

Evaluated the feasibility and limitations of consumer-grade EEG devices for real-time attention modelling, contributing early evidence on integrating physiological signals into adaptive human–AI interaction.

  1. Rebolledo-Mendez, G., Avramides, K., & De Freitas, S. (2009). Societal impact of a serious game on raising public awareness: The case of FloodSim. ACM SIGGRAPH Symposium on Video Games, 2009, pp. 15-22. [168 citations]

Demonstrated, at population scale, how simulation-based serious games can influence public awareness and engagement with complex policy issues, highlighting both the potential and limits of simplified AI-mediated representations of social systems.

  1. du Boulay, B., Avramides, K., Luckin, R., & Rebolledo-Mendez, G. (2010). Towards systems that care: A conceptual framework based on motivation, metacognition and affect. International Journal of Artificial Intelligence in Education, 20(3), 197-229. [113 citations]

Developed a foundational conceptual framework integrating motivation, metacognition, and affect, articulating how intelligent systems can reason about and respond to learners’ internal states beyond cognition alone.

  1. Rebolledo-Mendez, G., du Boulay, B., & Luckin, R. (2006). Motivating the learner: An empirical evaluation. Int. Conf. on Intelligent Tutoring Systems, 2006, Lecture Notes in Computer Science, vol. 4053, Springer, Berlin, Heidelberg. pp. 545-554. [85 citations]

Provided early empirical evidence that modelling motivational variables such as effort, confidence, and independence enables intelligent tutoring systems to adapt feedback and improve learning outcomes, particularly for disengaged learners.

  1. Rebolledo-Mendez, G., Reyes, A., & Paszkowicz, S. (2014). Developing a body sensor network to detect emotions during driving. IEEE Transactions on Intelligent Transportation Systems, 15(4), 1850-1854. [74 citations]

Proposed and validated a real-world architecture combining physiological sensing and vehicular systems to detect emotional states during driving, illustrating how affective signals can inform safety-critical AI interventions.

Recent Papers (2020-2024)

My recent research focuses on affect, cognitive load, and adaptation in intelligent systems, with particular attention to how emotional and contextual factors influence human interaction with AI-driven technologies.

  1. Cai, M., Rebolledo-Mendez, G., Arevalo, G., Tang, S.S., Abdullah, Y.A., & Demmans Epp, C. (2024). Toward Supporting Adaptation: Exploring Affect’s Role in Cognitive Load when Using a Literacy Game. Proc. of the CHI Conf. on Human Factors in Computing Systems, pp. 1-17.
  1. Rebolledo-Mendez, G., Huerta-Pacheco, N.S., Baker, R.S., & Du Boulay, B. (2022). Meta-Affective Behaviour within an Intelligent Tutoring System for Mathematics. Int. J. of Artificial Intelligence in Education, 32(1).
  1. Melendez-Armenta, R.A., Rebolledo-Mendez, G., & Huerta-Pacheco, N.S. (2022). Typifying Students’ Help-Seeking Behavior in an Intelligent Tutoring System for Mathematics. Ingenieria e Investigacion, 42(2).
  1. Garcia-Ruiz, M.A., Kapralos, B., & Rebolledo-Mendez, G. (2021). An overview of olfactory displays in education and training. Multimodal Technologies and Interaction, 5(10).
  1. Huerta-Pacheco, N.S., Rebolledo-Mendez, G., Aguirre, V., Hernandez-Gonzalez, S., & Lara-Munoz, E.M. (2019). Relevance of cultural dimensions in affective cognitive behavior during interaction with an intelligent tutoring system. CEUR Workshop Proceedings, 2354.

A complete publication list, citation metrics, and co-author networks are available via my academic profiles below.