B. Z. Allison and C. Neuper, Could anyone use a BCI?, Brain-computer interfaces, pp.35-54, 2010.

I. Arroyo, B. P. Woolf, J. M. Royer, and M. Tai, Affective Gendered Learning Companions, In: AIED, vol.200, pp.41-48, 2009.

A. Biasiucci, Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke, Nature communications, vol.9, issue.1, p.2421, 2018.

B. Paul, Praat, a system for doing phonetics by computer, Glot international, vol.5, 2002.

B. Laurent, L. Fabien, and L. Anatole, Two brains, one game: design and evaluation of a multiuser BCI video game based on motor imagery, IEEE Transactions on Computational Intelligence and AI in games, vol.5, issue.2, pp.185-198, 2013.

T. Carlson and M. Jose-del-r, Brain-controlled wheelchairs: a robotic architecture, IEEE Robotics & Automation Magazine, vol.20, issue.1, pp.65-73, 2013.

R. B. Cattell, H. Cattell, and . Ep, Personality structure and the new fifth edition of the 16PF. Educational and Psychological Measurement, vol.55, pp.926-963, 1995.

C. Chou, T. Chan, and C. Lin, Redefining the learning companion: the past, present, and future of educational agents, Computers & Education, vol.40, issue.3, pp.255-269, 2003.

D. Sidney, O. Andrew, W. Claire, and H. Patrick, Gaze tutor: A gaze-reactive intelligent tutoring system, International Journal of humancomputer studies, vol.70, issue.5, pp.377-398, 2012.

B. R. Duffy, Anthropomorphism and the social robot. Robotics and autonomous systems, vol.42, pp.177-190, 2003.

D. Carol and S. , Messages that motivate: How praise molds students' beliefs, motivation, and performance (in surprising ways). In: Improving academic achievement, pp.37-60, 2002.

E. Paul, Facial expression and emotion, American psychologist, vol.48, issue.4, p.384, 1993.

S. H. Fairclough, Fundamentals of physiologicalcomputing, Interacting with Computers, vol.21, issue.1-2, pp.133-145, 2009.

J. Frey, R. Gervais, S. Fleck, F. Lotte, and M. Hachet, Teegi: tangible EEG interface, Proceedings of the 27th annual ACM symposium on User interface software and technology, pp.301-308, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01025621

E. Friedrich, . Vc, C. Neuper, and R. Scherer, Whatever Works: A Systematic User-Centered Training Protocol to Optimize Brain-Computer Interfacing Individually, PloS one, vol.8, issue.9, p.76214, 2013.

G. Gaetano and D. , Investigating the role of combined acoustic-visual feedback in onedimensional synchronous brain computer interfaces, a preliminary study, vol.5, p.81, 2012.

R. Gervais, J. Frey, A. Gay, F. Lotte, M. Hachet et al., Tenth International Conference on Tangible, vol.16, pp.227-235, 2016.

S. Graham and B. Weiner, Theories and principles of motivation. Handbook of educational psychology, vol.4, pp.63-84, 1996.

H. Jean, F. Fabien, K. Jonathan, M. Charles, and B. Rémi, The EduFlow model: A contribution toward the study of optimal learning environments, Flow Experience, pp.127-143, 2016.

E. Hornecker, The role of physicality in tangible and embodied interactions. interactions, vol.18, pp.19-23, 2011.

A. M. Isen, K. A. Daubman, and G. P. Nowicki, Positive affect facilitates creative problem solving, Journal of personality and social psychology, vol.52, issue.6, p.1122, 1987.

K. Izuma, D. N. Saito, and N. Sadato, Processing of social and monetary rewards in the human striatum, Neuron, vol.58, issue.2, pp.284-294, 2008.

P. A. Jaques, R. M. Vicari, S. Pesty, and J. Bonneville, Applying affective tactics for a better learning, In: ECAI, vol.16, p.109, 2004.

C. Jeunet, E. Jahanpour, and F. Lotte, Why standard brain-computer interface (BCI) training protocols should be changed: an experimental study, Journal of neural engineering, vol.13, issue.3, p.36024, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01302154

C. Jeunet, B. N'kaoua, and F. Lotte, Towards a cognitive model of mi-bci user training, 7th International BCI Conference, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01519476

J. Camille, L. Fabien, and N. Bernard, Human learning for brain-computer interfaces, Brain-Computer Interfaces, vol.1, pp.233-250, 2016.

J. Camille, N. Bernard, S. Sriram, H. Martin, and L. Fabien, Predicting mental imagery-based BCI performance from personality, cognitive profile and neurophysiological patterns, PloS one, vol.10, issue.12, p.143962, 2015.

J. Camille, V. Chi, S. Daniel, N. Bernard, and L. Fabien, Subramanian Sriram. Continuous tactile feedback for motor-imagery based brain-computer interaction in a multitasking context, pp.488-505, 2015.

D. W. Johnson and R. T. Johnson, An educational psychology success story: Social interdependence theory and cooperative learning. Educational researcher, vol.38, pp.365-379, 2009.

E. Jovanov, A. Milenkovic, C. Otto, and P. De-groen, A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation, Journal of NeuroEngineering and rehabilitation, vol.2, issue.1, p.1, 2005.

K. Mostafa, G. Ali, and A. , Sentence subjectivity analysis in social domains, Proceedings of the 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies, vol.01, pp.268-275, 2013.

J. Kennedy, P. Baxter, and T. Belpaeme, The robot who tried too hard: Social behaviour of a robot tutor can negatively affect child learning, Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction, pp.67-74, 2015.

Y. Kim, A. L. Baylor, and P. Group, Pedagogical agents as learning companions: The role of agent competency and type of interaction, Technology Research and Development, vol.54, issue.3, pp.223-243, 2006.

K. Sonja, C. , and K. Andrea, Psychological factors influencing brain-computer interface (BCI) performance, 2015 IEEE International Conference on, pp.3192-3196, 2015.

C. Kothe, Lab streaming layer (LSL)

A. Kübler, B. Kotchoubey, J. Kaiser, J. R. Wolpaw, and N. Birbaumer, Brain-computer communication: unlocking the locked in, Psychology Bulletin, vol.127, issue.3, pp.358-375, 2001.

R. Leeb, F. Lee, C. Keinrath, R. Scherer, H. Bischof et al., Brain-Computer Communication: Motivation, aim and impact of exploring a virtual apartment, Transactions on Neural Systems & Rehabilitation Engineering, vol.15, pp.473-482, 2007.

J. C. Lester, S. A. Converse, S. E. Kahler, S. T. Barlow, B. A. Stone et al., The persona effect: affective impact of animated pedagogical agents, Proceedings of the ACM SIGCHI Conference on Human factors in computing systems, pp.359-366, 1997.

F. Lotte and C. T. Guan, Learning from other Subjects Helps Reducing Brain-Computer Interface Calibration Time, International Conference on Audio, Speech and Signal Processing (ICASSP'2010), pp.614-617, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00441670

F. Lotte, F. Larrue, and C. Mühl, Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design, Frontiers in Human Neuroscience, vol.7, issue.568, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00862716

K. Mathiak, Social reward improves the voluntary control over localized brain activity in fMRI-based neurofeedback training, Frontiers in behavioral neuroscience, vol.9, p.136, 2015.

M. Dennis, J. , W. Jon, and R. , Braincomputer interface use is a skill that user and system acquire together, PLoS biology, vol.16, issue.7, p.2006719, 2018.

M. Scott, W. , L. James, and C. , Modeling and evaluating empathy in embodied companion agents, International Journal of Human-Computer Studies, vol.65, issue.4, pp.348-360, 2007.

E. Mencarini, A. De-angeli, and M. Zancanaro, Emotions in climbing: a design opportunity for haptic communication, Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct. ACM, pp.867-871, 2016.

D. K. Meyer and J. Turner, Discovering emotion in classroom motivation research. Educational psychologist, vol.37, pp.107-114, 2002.

C. Neuper and G. Pfurtscheller, Neurofeedback training for BCI control, Brain-computer interfaces, pp.65-78, 2009.

R. Nkambou, J. Bourdeau, and R. Mizoguchi, Advances in intelligent tutoring systems, vol.308, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00699845

D. A. Norman, How might people interact with agents, Communications of the ACM, vol.37, issue.7, pp.68-71, 1994.

P. Reinhard, The impact of emotions on learning and achievement: Towards a theory of cognitive/motivational mediators, Applied Psychology, vol.41, issue.4, pp.359-376, 1992.

G. Pfurtscheller and C. Neuper, Motor Imagery and Direct Brain-Computer Communication. proceedings of the IEEE, vol.89, pp.1123-1134, 2001.

W. Picard-rosalind, Affective computing: challenges, International Journal of Human-Computer Studies, vol.59, issue.1-2, pp.55-64, 2003.

L. Pillette, C. Jeunet, R. N'kambou, B. N'kaoua, and F. Lotte, Towards Artificial Learning Companions for Mental Imagery-based Brain-Computer Interfaces, Workshop sur les "Affects, Compagnons Artificiels et Interactions"(ACAI), 2018.
URL : https://hal.archives-ouvertes.fr/hal-01762612

P. Robert, The nature of emotions: Human emotions have deep evolutionary roots, a fact that may explain their complexity and provide tools for clinical practice, American scientist, vol.89, issue.4, pp.344-350, 2001.

H. Ramoser, J. Muller-gerking, and G. Pfurtscheller, Optimal spatial filtering of single trial EEG during imagined hand movement, IEEE Transactions on Rehabilitation Engineering, vol.8, issue.4, pp.441-446, 2000.

B. Reeves and C. Nass, How people treat computers, television, and new media like real people and places, 1996.

Y. Renard, OpenViBE: An Open-Source Software Platform to Design, Test and Use Brain-Computer Interfaces in Real and Virtual Environments. Presence: teleoperators and virtual environments, vol.19, pp.35-53, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00477153

J. Robison, S. Mcquiggan, and J. Lester, Evaluating the consequences of affective feedback in intelligent tutoring systems, 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, pp.1-6, 2009.

S. Michael, Tangible interaction with anthropomorphic smart objects in instrumented environments, 2010.

E. Short, How to train your dragonbot: Socially assistive robots for teaching children about nutrition through play, The 23rd IEEE International Symposium on Robot and Human Interactive Communication, pp.924-929, 2014.

V. J. Shute, Focus on Formative Feedback. Review of Educational Research, vol.78, pp.153-189, 2008.

S. Barry and G. , Modeling emotion and behavior in animated personas to facilitate human behavior change: the case of the HEART-SENSE game. Health care management science, vol.4, pp.213-228, 2001.

E. Um, J. L. Plass, E. O. Hayward, and B. Homer,

D. , Emotional design in multimedia learning, Journal of Educational Psychology, vol.104, issue.2, p.485, 2012.

W. Ning, W. Johnson, M. Lewis, E. Richard, R. Paola et al., The politeness effect: Pedagogical agents and learning outcomes, International journal of human-computer studies, vol.66, issue.2, pp.98-112, 2008.

W. John, M. Roderick, B. Benjamin, K. Matthias, and K. Müller, Designing for uncertain, asymmetric control: Interaction design for brain-computer interfaces, International Journal of Human-Computer Studies, vol.67, issue.10, pp.827-841, 2009.

J. Wolpaw and E. W. Wolpaw, Brain-computer interfaces: principles and practice, 2012.

B. P. Woolf, I. Arroyo, D. Cooper, W. Burleson, and K. Muldner, Affective tutors: Automatic detection of and response to student emotion, Advances in Intelligent Tutoring Systems, pp.207-227, 2010.

T. O. Zander and S. Jatzev, Detecting affective covert user states with passive brain-computer interfaces, Affective Computing and Intelligent Interaction and Workshops, 2009. ACII 2009. 3rd International Conference on, pp.1-9, 2009.