Evaluating Engagement Physiologically and Knowledge Retention Subjectively through Two Different Learning Techniques

Andujar, Marvin; Ekandem, Joshua I.; Gilbert, Juan E.; Morreale, Patricia

doi:10.1007/978-3-642-39262-7_38

Cited by 5 publications

(2 citation statements)

References 7 publications

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“…[32,33] Other studies have focused on the comparison of learning techniques while wearing a BCI (Figure 8). [34] The adaptation of artistic BCI in education can be useful from an expression and stimulus perspective to assist teachers to identify in real time, or after the given task, the student's learning experience: for instance, a scenario where learners in a classroom are wearing a BCI and the teacher is able to monitor on his or her computer or mobile device when the students are engaged. The visualization type and the use of colors are the key to the data comprehension for both the teacher and students.…”

Section: Educationmentioning

confidence: 99%

Artistic brain-computer interfaces: the expression and stimulation of the user’s affective state

Andujar

Crawford

Nijholt

et al. 2015

Brain-Computer Interfaces

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Science, technology, engineering, and mathematics (STEM) is rapidly transitioning to STEAM, which is the integration of the arts and design into the sciences. This transition is due to the need of adapting creativity in the sciences and engineering fields. This demonstrates the growing importance of the arts contribution towards the sciences in various ways. An area where art shows promise is in brain-computer interfaces. In this paper, we propose a definition for artistic brain-computer interfaces (artistic BCI) from a passive BCI perspective. We defined its composition in four fields: human-computer interaction, neurophysiology, art, and computing. This definition is based on the user's state stimulation and expression and how art could help us and the end user understand the user's affective state. We also discuss its applicability towards different areas and how these areas can benefit from artistic BCI.

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Section: Educationmentioning

confidence: 99%

Artistic brain-computer interfaces: the expression and stimulation of the user’s affective state

Andujar

Crawford

Nijholt

et al. 2015

Brain-Computer Interfaces

Self Cite

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“…Within the HRI community, there is a small, but growing body of research employing brain-computer interfaces as a modality for both understanding and augmenting a person's experience (Canning and Scheutz, 2013;Zander, 2009;Zander and Kothe, 2011). Brainbased adaptivity of robotic agents based on students' level of attention has been repeatedly shown to produce learning enhancements (Andujar et al, 2013;Szafir and Mutlu, 2012;Szafir and Mutlu, 2013). BCIs have also been used to further understand the user's perceptions of a robot, e.g., (Broadbent et al, 2013;Kawaguchi et al, 2012;Rosenthal von der Putten et al, 2013a).…”

Section: Related Workmentioning

confidence: 99%

Using Near Infrared Spectroscopy to Index Temporal Changes in Affect in Realistic Human-robot Interactions

Strait¹,

Scheutz²

2014

Proceedings of the International Conference on Physiological Computing Systems

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Recent work in HRI found that prefrontal hemodynamic activity correlated with participants' aversions to certain robots. Using a combination of brain-based objective measures and survey-based subjective measures, it was shown that increasing the presence (co-located vs. remote interaction) and human-likeness of the robot engaged greater neural activity in the prefrontal cortex and severely decreased preferences for future interactions. The results of this study suggest that brain-based measures may be able to capture participants' affective responses (aversion vs. affinity), and in a variety of interaction settings. However, the brain-based evidence of this work is limited to temporally-brief (6-second) post-interaction samples. Hence, it remains unknown whether such measures can capture affective responses over the course of the interactions (rather than post-hoc). Here we extend the previous analysis to look at changes in brain activity over the time course of more realistic human-robot interactions. In particular, we replicate the previous findings, and moreover find qualitative evidence suggesting the measurability of fluctuations in affect over the course of the full interactions.

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Evaluation of User’s Affective Engagement While Interacting with Educational Technologies: A Pilot Study

Andujar

Morreale

Jimenez

et al. 2016

Advances in Neuroergonomics and Cognitive Engineering

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Evaluating Engagement Physiologically and Knowledge Retention Subjectively through Two Different Learning Techniques

Cited by 5 publications

References 7 publications

Artistic brain-computer interfaces: the expression and stimulation of the user’s affective state

Artistic brain-computer interfaces: the expression and stimulation of the user’s affective state

Using Near Infrared Spectroscopy to Index Temporal Changes in Affect in Realistic Human-robot Interactions

Evaluation of User’s Affective Engagement While Interacting with Educational Technologies: A Pilot Study

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