What is Affective Computing?

Affective computing is the idea that humans can program machines to recognize, interpret, process and simulate the range of human emotions. This concept centers on the development of programs and hardware that create the faculties for a computer to do this, such as implementing a video camera to capture facial cues and gestures that works in conjunction with an algorithm that can detect and interpret these human affects. Not to be confused with facial recognition technologies associated with security, like those that facilitate secure payment transactions, affective computers recognize emotional and behavioral cues that trigger a reactionary process in the computer. A potential application of affective computing is in online learning situations wherein a computerized tutor reacts to facial cues of boredom in a student in an effort to motivate or boost their confidence. With researchers already working on educational applications, and start-up companies exploring other novel uses, growth in the field of affective computing has deep implications for the future of human and computer interactions.

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1) How might this technology be relevant to the educational sector you know best?

  • Successful instructors have the ability to intuitively manage students' emotions (such as passion, boredome, happiness, dislike, fear, frustration, satisfaction, etc.) to promote learning. However, there are missing e-learning environments that affectively react to students' emotions. It has been shown that Emotional Feedback has a direct effect on Behavioral Intention to Use a Computer-based Assessment. Avatars or Embodied Conversational Agents (ECAs) have been used to provide emotional feedback. ECAs' emotional facial and tone of voice expressions combined with empathetic verbal behavior have been displayed as feedback to students’ fear, sad, and happy emotions in the context of a self-assessment tests and assessment. Results indicate that an ECA performing parallel empathy displaying emotional expressions relevant to the emotional state of the student may cause this emotion to persist. Moreover, the ECA performing parallel and then reactive empathy appeared to be effective in altering an emotional state of fear to a neutral one http://conta.uom.gr/conta/filter_pub.php?filter=33&lang=en - Anastasios.A.ECONOMIDES Anastasios.A.ECONOMIDES Oct 22, 2015

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(2) What themes are missing from the above description that you think are important?

  • A lot of work has been done on recognizing emotions. However, it is important to also react to students' emotions or even try to modify them for the students' improvement, education and well-being. - Anastasios.A.ECONOMIDES Anastasios.A.ECONOMIDES Oct 22, 2015

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(3) What do you see as the potential impact of this technology on higher education?

  • Major! Affective computing will become necessary for any e-learning environment. Students with great talent in science or other disciplines could fail to perceive their potential and follow a career that does not reflect their real inclination because of emotional exhaustion, lack of self-competence, or other psychological inefficiencies. Consequently, an educational system not integrating helpful affective learning techniques could result in unsatisfied individuals and in loss of valuable social capital. http://conta.uom.gr/conta/filter_pub.php?filter=33&lang=en - Anastasios.A.ECONOMIDES Anastasios.A.ECONOMIDES Oct 22, 2015
  • Affective computing can also be particularly important for students with non-neurotypical patterns of learning. - escience escience Oct 25, 2015
  • Affective computing has the potential for us to reach out the learners in more meaningful ways than previously possible. The reality is that one faculty member cannot meet every student’s single need while under their care. With virtual agents programmed to recognize the attitudes, likes, dislikes, and disposition so as to guide the learning experience is quite promising. It could also address unique learning scenarios such as those of the autistic learners who struggle with recognizing the emotions of other people. The MIT Media Lab emotional-social intelligence toolkit is a great example of this scenario (see link below)
    - francisca francisca Oct 25, 2015

(4) Do you have or know of a project working in this area?

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