Now, a computer which responds to students' emotions!
Now, a computer which responds to students' emotions!
Scientists in the US say they have developed a computer which can respond to students' emotions and boredom.

Washington: Scientists in the US say they have developed a computer which can respond to students' emotions and boredom.

A team from University of Notre Dame, the University of Memphis and Massachusetts Institute of Technology has in fact come up with what they claim is the "emotion-sensing" computer software that models and responds to students' cognitive and emotional states, including frustration and boredom.

The new technology, that matches the interaction of human tutors, not only offers tremendous learning possibilities for students, but also redefines human-computer interaction, the scientists say in a release.

Known as "AutoTutor" and "Affective AutoTutor", the programme can gauge the student's level of knowledge by asking probing questions; analysing the student's responses to those questions; proactively correcting misconceptions; responding to the student's own questions.

The programme can even sense a student's frustration or boredom via facial expression and body posture and dynamically changing its strategies to help the student conquer those negative emotions, say the scientists.

"Most of the 20th century systems required humans to communicate with computers through windows, icons, menus and pointing devices. But humans have always communicated with each other through speech and a host of nonverbal cues such as facial expressions, eye contact, posture and gesture.

"In addition to enhancing the content of the message, the new technology provides information regarding the cognitive states, motivation levels and social dynamics of the students," team leader Sidney D'Mello said.

D'Mello added: "Much like a gifted human tutor, AutoTutor and Affective AutoTutor attempt to keep the student balanced between the extremes of boredom and bewilderment by subtly modulating the pace, direction and complexity of the learning task."

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