Affective Computing refers to the idea that humans can program machines to recognize, interpret, process, and simulate the range
of human emotions. This concept revolves around the development of computers attaining humanlike understanding through activities
such as implementing a video camera to capture facial cues and gestures that work in conjunction with an algorithm that detects and interprets these interactions. The ultimate goal of affective computing is to improve and apply these technologies to create context-aware, emotionally responsive machines that cater to even the most subtly communicated needs. This will be a particularly exciting development for virtual assistants such as Amazon’s Alexa and Apple’s Siri, which already understand and respond to voice commands;
the addition of emotion recognition would take the category to a new level.
Within learning, where students’ knowledge is increasingly being assessed through analytics, affective computing has the potential to fill in an elusive part of the picture by understanding and catering to learner attitudes and emotions.