Educating Humans Using Robots
As in so many fields concerning humans, robots should perform the job and humans should be
involved in supervision and robot repair.
The use of social robots to teach human children is growing. In the near future, children learning pre-
school skills and students of all ages studying a new language seems very feasible.
Some literature is referring to a "new science of learning," which brings together recent findings from
the fields of psychology, neuroscience, machine learning and education.
New insights into how humans learn now and could learn in the future, based on various studies
including some that document the amazing amount of brain development that happens in infants and
later on in childhood.
Humans are born immature and naturally curious, and become creatures capable of highly complex
cultural achievements. Examples include the ability to build schools and school systems that can teach
humans how to create computers that mimic human brains.
With a stronger understanding of how human learning happens, scientists are coming up with new
principles for human learning, new educational theories and designs for learning environments that
better match how humans learn best. Social robots will have a growing role in these future learning
environments. The mechanisms behind these sophisticated social robots complement some of the
mechanisms behind human learning.
One such robot, which looks like the head of Albert Einstein, shows facial expressions and reacts to
real human expressions. Humans who built the body-less robot plan to test it in schools.
Machine learning
In the first 5 years of life, human learning is exuberant and effortless. Humans are born learning and
adults are driven to teach infants and children. During those years and up to puberty, human brains
exhibit neural plasticity and it easier to learn languages.
Human early learning is computational. Children under three and even infants have been found to use
statistical thinking, such as frequency distributions and probabilities and covariation, to learn the
phonetics of their native tongue and to infer cause-effect relationships in the physical world.
Some of these findings have helped human engineers build machines that can learn and develop social
skills, such as BabyBot, a baby doll trained to detect human faces.
Meanwhile, human learning is also highly social, so social, in fact, that newborns as young as 42
minutes old have been found to match gestures shown to them, such as someone sticking out her
tongue or opening his mouth.
Imitation is a key component to human learning — it's a faster and safer way to learn than just trying
to figure something out on one's own.
Even human adults use imitation when they go to a new setting such as a dinner party or a foreign
country, to try and fit in. Of course, for kids, the learning packed into every day can amount to
traveling to a foreign country. In this case, human children are "visiting" human adult culture and
learning how to act like the people in their culture, becoming more like other local humans.
If you roll all these human learning features into the field of robotics, there is a somewhat natural
overlap — robots are well-suited to imitate humans, learn from humans, socialize with humans and
eventually teach humans.
Robot teachers
Social robots are being used on an experimental basis already to teach various skills to preschool
children, including the names of colors, new vocabulary words and simple songs.
Robot teachers can be cost-effective compared to the expense of paying a human teacher.
By capturing the techniques of social interaction and pedagogy the plan is to embody those tricks in
machines, including computer agents, automatic tutors, and robots.
Currently children learn best from other people and playgroups of peers but we can foresee a time
where children are taught entirely by robots.
Terrance Sejnowski is working on using technology to merge the social with the instructional, and
bringing it to bear on classrooms to create personalized, individualized teaching tailored to students
and tracking their progress.
"By developing a very sophisticated computational model of a child's mind, we can help improve that
child's performance," Sejnowski said.
Prosthetic Hand:
http://www.youtube.com/watch?v=AZM40MVJVFY
Humbot
Next
As in so many fields concerning humans, robots should perform the job and humans should be
involved in supervision and robot repair.
The use of social robots to teach human children is growing. In the near future, children learning pre-
school skills and students of all ages studying a new language seems very feasible.
Some literature is referring to a "new science of learning," which brings together recent findings from
the fields of psychology, neuroscience, machine learning and education.
New insights into how humans learn now and could learn in the future, based on various studies
including some that document the amazing amount of brain development that happens in infants and
later on in childhood.
Humans are born immature and naturally curious, and become creatures capable of highly complex
cultural achievements. Examples include the ability to build schools and school systems that can teach
humans how to create computers that mimic human brains.
With a stronger understanding of how human learning happens, scientists are coming up with new
principles for human learning, new educational theories and designs for learning environments that
better match how humans learn best. Social robots will have a growing role in these future learning
environments. The mechanisms behind these sophisticated social robots complement some of the
mechanisms behind human learning.
One such robot, which looks like the head of Albert Einstein, shows facial expressions and reacts to
real human expressions. Humans who built the body-less robot plan to test it in schools.
Machine learning
In the first 5 years of life, human learning is exuberant and effortless. Humans are born learning and
adults are driven to teach infants and children. During those years and up to puberty, human brains
exhibit neural plasticity and it easier to learn languages.
Human early learning is computational. Children under three and even infants have been found to use
statistical thinking, such as frequency distributions and probabilities and covariation, to learn the
phonetics of their native tongue and to infer cause-effect relationships in the physical world.
Some of these findings have helped human engineers build machines that can learn and develop social
skills, such as BabyBot, a baby doll trained to detect human faces.
Meanwhile, human learning is also highly social, so social, in fact, that newborns as young as 42
minutes old have been found to match gestures shown to them, such as someone sticking out her
tongue or opening his mouth.
Imitation is a key component to human learning — it's a faster and safer way to learn than just trying
to figure something out on one's own.
Even human adults use imitation when they go to a new setting such as a dinner party or a foreign
country, to try and fit in. Of course, for kids, the learning packed into every day can amount to
traveling to a foreign country. In this case, human children are "visiting" human adult culture and
learning how to act like the people in their culture, becoming more like other local humans.
If you roll all these human learning features into the field of robotics, there is a somewhat natural
overlap — robots are well-suited to imitate humans, learn from humans, socialize with humans and
eventually teach humans.
Robot teachers
Social robots are being used on an experimental basis already to teach various skills to preschool
children, including the names of colors, new vocabulary words and simple songs.
Robot teachers can be cost-effective compared to the expense of paying a human teacher.
By capturing the techniques of social interaction and pedagogy the plan is to embody those tricks in
machines, including computer agents, automatic tutors, and robots.
Currently children learn best from other people and playgroups of peers but we can foresee a time
where children are taught entirely by robots.
Terrance Sejnowski is working on using technology to merge the social with the instructional, and
bringing it to bear on classrooms to create personalized, individualized teaching tailored to students
and tracking their progress.
"By developing a very sophisticated computational model of a child's mind, we can help improve that
child's performance," Sejnowski said.
Prosthetic Hand:
http://www.youtube.com/watch?v=AZM40MVJVFY
Humbot
Next
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Human Education