Coming soon to a preschool classroom near you: Robot teachers?

Robots all over the world

In Seoul, South Korea, robots are establishing a presence in education and soon will move beyond basic testing to full classroom implementation.

Engkey (a contraction of “English Jockey,” as in disc jockey), a robot created by the Center for Intelligent Robotics (CIR) at the Korea Institute of Science and Technology (KIST), is a short, penguin-like robot designed to help South Korean students learn English.

Engkey in a school in Seoul. Copyright: Choe Sang-Hun, NYT.
Engkey in a school in Seoul. Copyright: Choe Sang-Hun, New York Times.

CIR’s focus on the development of robot technologies for daily human assistance is what inspired the team to create Engkey. CIR’s technologies are managed by a government-funded program, 21C Frontier, which is hosted by the Korea Ministry of Knowledge and Economy (MKE). The program is a 10-year initiative that began in 2003, and its total budget is about 130 million U.S. dollars.

MKE, and the city of Masan in Korea, provided an additional half a million U.S. dollars specifically for the development of Engkey.

According to KIST’s Intelligent Robotics team leader, Dr. Mun-taek Choi, the development of Engkey started in early 2009, and the first version took slightly less than a year to create by applying some of the original technologies from CIR. Choi and his team expect the second version of Engkey, with better software, to be ready by the end of this year.

In a pilot project to test the applicability of the robot as a teaching tool, the first version of Engkey was installed in classrooms for two months, from late Dec. 2009 to early Feb. 2010. Engkey helped teach students in two Masan schools.

Engkey has the option of using either a synthesized female or male voice and can follow students around the room, asking them basic programmed questions in English, such as “How can I help you today?”

The robot also is programmed to give a series of set responses, such as “Wow, very good!” or “Not good this time. You need to focus more on your accent.”

However, Engkey is programmed to hear a set list of responses, and if a student deviates from the responses, Engkey cannot compute those responses.

“To make a robot have ‘good’ interaction skills, first we need to develop good recognition technologies to understand humans, environments, and situations,” said Choi. “Those are very limited with current sensor technologies.”

After more tests in schools this year, Choi hopes to commercialize Engkey and to reduce the price from the current $24,000 to $8,000.

South Korea, a leader in robotics, soon will deploy hundreds of robotic teaching aides as part of a plan to have the country’s 8,400 kindergartens work with robots by 2013, thanks to the efforts of the Education Ministry.

“In Korea, English education is very important to students and their parents, and in many cases it takes substantial costs to have native speakers teaching,” explained Choi. “Although robots cannot supplant human teachers, we believe that we can at least provide a cost-effective way of teaching; and robots are quite effective in teaching as long as they are carefully designed with predefined teaching materials using current technologies.”

Engkey might (or might not) be one of these teaching aides, owing to the robot’s inability to handle off-program responses and what some critics have called a lack of functional human abilities, such as recognizing emotions or responding organically.

“In reality, many unexpected incidents happen all the time [in the classroom], and humans have a good capability to adapting to these incidents and even learning from them. Although robotists are doing hard work, they might not have that capability in the short term,” Choi said.

Because robots can’t yet recognize individual students and respond promptly and properly, he said, they cannot be used to replace teachers.

Social robots

However, one robot currently being developed in the United States might be the most promising development in robotic teaching assistants.

Simon, the creation of Dr. Andrea Thomaz, assistant professor in the School of Interactive Computing at the Georgia Institute of Technology’s Socially Intelligent Machines (SIM) Lab, can learn simply by socializing.

According to the SIM Lab’s web site, Simon was partly developed due to the realization that if robots are to be effective in the classroom, developers will not be able preprogram the robots with every skill needed–the robots will need to interact and learn new things “on the job” from ordinary people.

Simon, an upper-torso robot with a “socially expressive head” and the body proportions of a 5-foot, 7-inch woman, learns from social attention and interactive task learning. For example, say Simon is handed an object. If Simon recognizes the object, it will drop that object into the appropriate color-coded bucket. If Simon has not learned where to put the object, it is told, and then will remember that object and its designation in the future.

Simon is also a proactive learner. If Simon is asked whether it has any questions, it will scan the environment to identify any objects it might not know.

Simon performing simple tasks

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Simon is also programmed to recognize the most important aspects of its environment through visual and auditory stimuli, and then assigns value to these stimuli.

Meris Stansbury

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