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• K. G. Seeber and D. Kerzel, "Cognitive load in simultaneous interpreting: Model meets data, " International Journal of Bilingualism, vol. 16, no. 2, pp. 228-242, 2012.
• P. van der Wel and H. van Steenbergen, "Pupil dilation as an index of effort in cognitive control tasks: A review, " Psychonomic Bulletin & Review, vol. 25, pp. 2005-2015, 2018.
• O. Kang and T. Wheatley, "Pupil dilation patterns reflect the contents of consciousness, " Consciousness and Cognition, vol. 35, pp. 128-135, 2015.
• -, "Pupil dilation patterns spontaneously synchronize across individuals during shared attention, " Journal of Experimental Psychology: General, vol. 146, no. 4, pp. 569-576, 2017.
• J. W. de Gee, T. Knapen, and T. H. Donner, "Decision-related pupil dilation reflects upcoming choice and individual bias, " Proceedings of the National Academy of Sciences, vol. 111, no. 5, pp. E618-E625, 2014.
• J. Sweller, J. J. G. Van Merrienboer, and F. G. W. C. Paas, "Cognitive Architecture And Instructional Design, " Educational Psychology Review, vol. 10, pp. 251-296, 1998.
• N. Vaughan, B. Gabrys, and V. N. Dubey, "An overview of self-adaptive technologies within virtual reality training, " Computer Science Review, vol. 22, pp. 65-87, 2016.
• K.-C. Siu, B. J. Best, J. W. Kim, D. Oleynikov, and F. E. Ritter, "Adaptive Virtual Reality Training to Optimize Military Medical Skills Acquisition and Retention, " Military Medicine, vol. 181, no. 5 Suppl, pp. 214-220, 2016.
• C. I. Aguilar Reyes, D. Wozniak, A. Ham, and M. Zahabi, "Design and evaluation of an adaptive virtual reality training system, " Virtual Reality, vol. 27, no. 3, pp. 2509-2528, 2023.
• M. S. Aquino, F. F. De Souza, and A. C. Frery, "Vepersonal: an infrastructure of virtual reality components to generate web adaptive environments, " in Proc. 11th Brazilian Symposium on Multimedia and the Web, 2005, pp. 1-8.
• C. Baker and S. H. Fairclough, "Adaptive virtual reality, " in Current Research in Neuroadaptive Technology. Elsevier, 2022, pp. 159-176.
• C. McDonald, M. Davis, and C. Benson, "Using Evidence-Based Learning Theories to Guide the Development of Virtual Simulations, " Clinical Social Work Journal, vol. 49, no. 2, pp. 197-206, 2021.
• P. Ramakrishnan, B. Balasingam, and F. Biondi, "Cognitive load estimation for adaptive human-machine system automation, " in Learning control, D. Zhang and B. Wei, Eds. Elsevier, 2021, pp. 35-58.
• U. Lahiri, E. Bekele, E. Dohrmann, Z. Warren, and N. Sarkar, "Design of a virtual reality based adaptive response technology for children with autism, " IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 21, no. 1, pp. 55-64, 2012.
• C. Tremmel, C. Herff, T. Sato, K. Rechowicz, Y. Yamani, and D. J. Krusienski, "Estimating Cognitive Workload in an Interactive Virtual Reality Environment Using EEG, " Frontiers in Human Neuroscience, vol. 13, 2019.
• J. T. Doswell and A. Skinner, "Augmenting Human Cognition with Adaptive Augmented Reality, " in Proc. International Conference on Augmented Cognition (AC). Springer, 2014, pp. 104-113.
• B. John, P. Raiturkar, A. Banerjee, and E. Jain, "An Evaluation of Pupillary Light Response Models for 2D Screens and VR HMDs, " in Proc. 24th ACM Symposium on Virtual Reality Software and Technology (VRST), 2018.
• H. Chen, A. Dey, M. Billinghurst, and R. W. Lindeman, "Exploring Pupil Dilation in Emotional Virtual Reality Environments, " in Proc. International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments (ICAT-EGVE), 2017.
• J. Lee, N. De Jong, J. Donkers, H. Jarodzka, and J. Van Merriënboer, "Measuring Cognitive Load in Virtual Reality Training via Pupillometry, " IEEE Transactions on Learning Technologies, pp. 1-7, 2023.
• P. Stark, T. Appel, M. J. Olbrich, and E. Kasneci, "Pupil Diameter during Counting Tasks as Potential Baseline for Virtual Reality Experiments, " in Proc. Symposium on Eye Tracking Research and Applications (ETRA), 2023, pp. 1-7.
• A. Hebbar, S. Vinod, A. K. Shah, A. Pashilkar, and P. Biswas, "Cognitive load estimation in VR flight simulator, " Journal of Eye Movement Research, vol. 15, no. 3, 2022.
• J. Orlosky, B. Huynh, and T. Hollerer, "Using Eye Tracked Virtual Reality to Classify Understanding of Vocabulary in Recall Tasks, " in Proc. IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), 2019, pp. 66-73.
• L. J. Zheng, J. Mountstephens, and J. Teo, "Four-class emotion classification in virtual reality using pupillometry, " Journal of Big Data, vol. 7, pp. 1-9, 2020.
• M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, M. Devin, S. Ghemawat, I. Goodfellow, A. Harp, G. Irving, M. Isard, Y. Jia, R. Jozefowicz, L. Kaiser, M. Kudlur, J. Levenberg, D. Mané, R. Monga, S. Moore, D. Murray, C. Olah, M. Schuster, J. Shlens, B. Steiner, I. Sutskever, K. Talwar, P. Tucker, V. Vanhoucke, V. Vasudevan, F. Viégas, O. Vinyals, P. Warden, M. Wattenberg, M. Wicke, Y. Yu, and X. Zheng, "TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems, " 2015. [Online]. Available: https://www.tensorflow.org/
• J. Botev, K. Drewing, H. Hamann, Y. Khaluf, P. Simoens, and A. Vatakis, "ChronoPilot -Modulating Time Perception, " in Proc. IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), 2021, pp. 215-218.