essay about robot teacher

Robot teachers use, types, advantages and disadvantages

by Heba Soffar · Published June 20, 2016 · Updated April 12, 2024

Robot teachers are programmed for their jobs, They will always obey, They are the solution to education, They can teach you technological skills, They can teach poor kids that have no chance to come in contact with technology and they do not have to get paid.

Robot teachers

Robot teachers can be used in the development of the design and structure of learning programs, It may be challenging to use such technologies as a substitute for human education all throughout the world, if the entire teaching curriculum is based on computer programs, human teaching may appear to be redundant, This is due to the associated technology limitations, such as inaccuracy in voice or emotion recognition.

The first robot teacher was invented in Japan in 1973. It was called WABOT-1 and was a humanoid robot that could teach English to children. It was a simple robot that could teach children basic math and language skills. Robot teachers can be programmed to adapt their teaching style to each student.

Robot teachers advantages

Robot teachers are better than humans , They are new and they will have new methods, The teachers have the old methods while the robot teachers have up-to-date methods, If the robots become teachers, They will only be in elementary schools and pre-schools.

Robot teachers can be used to teach students in remote locations. This is beneficial for students in developing countries or who live in rural areas. Robot teachers can be used to teach students with disabilities, Robot teachers can be used to teach students with autism spectrum disorder or other communication disorders.

Robot teachers are mainly used as classroom assistants in elementary schools, Some robots can transmit video from far away places, so, the teacher does not have to be in the classroom if they do not live in the country, The kids not only love the robots but also the robots benefit the kids in the classroom.

Scientists think that social interaction with the live human being is crucial for learning to take place in children under 1 year, In the future, more and more of us will learn from social robots , especially the kids learning preschool skills and students of all ages studying a new language.

Social robots are being used on an experimental basis to teach various skills to preschool children, including color names, new vocabulary words, and songs and they can save money for the schools by not having to pay the teachers. Some robot teachers can tell jokes and sing songs. Some robot teachers can play games with students. Some robot teachers can give students hugs.

In the future, robots will only be used to teach certain skills such as acquiring a foreign or new language, possibly in playgroups with children or to individual adults, But robot teachers can be cost-effective compared to the expense of paying the human teacher.

Relying on technology for classroom instruction creates an even playing field where all the students are learning everything that needs to be covered according to the curriculum standards and they should have a well-educated, high-quality teacher in the classroom.

The students are all also receiving the same high-quality information, using the robot teacher for student instruction can greatly cut down on the teacher’s salary costs, By placing the burden of teaching the lessons on programmed instruction.

SMART Boards are interactive whiteboards that can project computer displays and allow the students to interact with them through touch, SMART pens help the students to write on the screen and the board can translate the student’s handwriting into the computer text and then save it as a document file on the connected computer.

While technology can be a great tool for promoting interactive learning and providing information beyond the scope of the teacher’s knowledge base, It can not replace the intrinsic value of having the human devoted to the child’s educational development present in the classroom.

Today, robot teachers are much more sophisticated. They can teach a wide range of subjects, including science, history, and social studies. Robot teachers can also be used to provide individualized instruction to students. They can assess each student’s progress and tailor the lessons accordingly.

Robot teachers are used as teaching assistants, rather than as full-fledged teachers. They can help human teachers with tasks such as grading homework, leading small groups, and providing extra help to struggling students. Robot teachers can be used to provide students with personalized feedback and extra help when needed.

Robot teachers can be used to create immersive learning experiences for students. a robot teacher could be used to create a simulated historical event or a virtual field trip to a foreign country. Robot teachers can be used to teach students about robotics and artificial intelligence . This can help students develop important skills for the future workforce.

Robot teachers have the potential to revolutionize education. They can help to provide students with more personalized and engaging instruction, and they can make education more accessible to students all over the world.

Some robot teachers can be programmed to speak multiple languages, making them whizz at teaching foreign languages or helping students from different backgrounds. Robot teachers could be used to provide education in remote locations where there might not be enough human teachers. This can make learning more engaging and fun for students.

Unlike traditional teachers, robot teachers can be programmed to adjust their teaching style to fit each student’s needs, giving everyone a more personalized learning experience. This means they can give extra help to those who struggle and keep things moving for those who grasp concepts quickly.

Robot teachers can zip through grading multiple-choice tests and other assessments, freeing up human teachers for more interactive tasks. While emotions might not be their strong suit yet, some robot teachers can be programmed to tell jokes, sing songs, or dance to keep students engaged and having fun while they learn in the classroom.

Robot teachers can be tireless assistants in the classroom, helping with tasks like grading assignments and taking attendance, freeing up human teachers for more one-on-one interaction. They don’t get tired! Robot teachers can tirelessly explain concepts, answer questions, and practice with students all day long.

Disadvantages of robot teachers

Many schools d on’t have a lot of money, They don’t pay their teachers, So, they cannot afford the robot teacher even a t the cheapest price, The robots need electricity , and electricity costs a lot.

Robot teachers d o not have feelings, They are not able to help you to get over things and help you feel better but the human teachers can and the robot wouldn’t know what to do. If we converted to robots , teachers and staff worldwide would lose their jobs, The robots are not able to develop personal distinctions between the students.

Implementing this technology in the classroom r equires the existing infrastructure for electricity and Internet , an instructor device (desktop/laptop/iPad) is needed to connect to and the software to enable the use of all aspects of the hardware.

Robot teachers are higher-cost technologies in the developing world, The software is employed on low-cost laptops, desktops, or tablets to simulate teacher instruction. In these classrooms, The entire curriculum can be imparted to the students through the computer program, making a quality human teacher unnecessary.

There are no inspiring robot teachers , They are all programmed to spit the knowledge out at the students and expect the students to spit it back at them. Robot teachers can not develop creative or innovative ideas for teaching the material in a new way, It can not comment on the papers to provide the students with valuable positive feedback or critiques.

Robot teachers can not pull the struggling student aside and determine if there are personal issues related to his/her performance, It can not encourage students with particular strengths and interests in the subject to consider certain career paths. In developing regions, Employing technology as an alternative to human instruction makes it difficult to gauge the design specifications for effective instructional software.

Types of Robots in the Classroom

A small robot named KeeKo is being used to help kindergarten teachers when needed In China, the KeeKo robot tells stories to the children, KeeKo robot gives the students logic problems to answer, and shows certain facial expressions when the student gets the problem correct or wrong, KeeKo offers the human teacher a break for a few minutes to take a breather. KeeKo can assist the teacher in the classroom, and the students can participate and enjoy the activity.

Tega is an AI-powered, teddy bear-sized and -looking robot, that was tested in Boston-area schools with substantial English-language learner populations in randomized control trials, The robots ‘ can help 5- and 6-year-olds develop their language and literacy skills, the usage of human teachers and artificially intelligent robots in schools develop education in terms of vocabulary and oral language development in children.

Boe-bot robots are simple robots with a microprocessor mounted on wheels as their main component, they can identify the distance from an item, maneuver, and steer by sensing light, thanks to the program built into their system, they come with light and sound mechanisms to indicate the status of contact sensors and the room’s escape edges.

Humanoid robots are used in the classroom, they are a step up from telepresence , so, teachers can use the robot to stay linked to students remotely, The instructor can virtually engage in a learning session through a display device, The robots type that can be employed in a classroom is determined by the students’ age, group and the course of study. In the classroom, many kinds of robots can be deployed as teachers.

In China, a robot teacher named Xiao Hui is being used to teach English to elementary school students. In Japan, a robot teacher named Robovie is being used to teach social studies to middle school students. a robot teacher named Elias is being used to teach math to kindergarten students.

In Japan, there is a robot teacher named Pepper who is used to teach English to elementary school students. Pepper can interact with students in a variety of ways, including through conversation, gestures, and facial expressions. Another robot teacher , named Elias, is being used in elementary schools to help students with their speaking and listening skills.

Benefits of a human teacher

Human teachers can read social cues, they can inspire children, they have strong sensory feelings and emotions, they can be creative, they are social, and they do not have technical disruptions, Young people still need human teachers to help them remain in the reality in front of them.

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29 Responses

Comments 29
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very well said

Thank you very much

What are the advantage of human teachers

teachers explain more and if you have questions, they can understand the questions , They can answer them and show them to you step by step , then again teachers love the students , They help them , The teacher is the best friend to the student .

Heba Soffar you explain very well about important key words and there is no sentences that are not important

Thank you very much for your comment

You’ve clearly thought about this in a lot of detail. This is a great piece of writing.

please write about the future robtic teachers

Thank you very much for your comment You can read these articles Pros and cons of technology in education & Can technology replace teachers? Telepresence robots uses, advantages & disadvantages The importance and uses of the educational robotics for the students

thank you for the information it is very informative and it has helped a lot with my research.

You are welcome

the girl next to me is very annoying and robots could take care of that

THIS IS ONLY FOR PEOPLE WHO BETRAYED US HIGHSCHOOLERS

very cool and well said

good morning 😃

what points can u state about robots knowing more languages than humans

You can read this article about Robots for Learning Language, Children can learn English or any language from a humanoid robot Educational robotics, Robot teachers, Social robots review, features advantages & drawbacks

Very well written

Thank you for your comment

superb writing

Robot teachers

Editor’s note: This essay is an entry in Fordham’s 2023 Wonkathon , which asked contributors to answer this question: “How can we harness the power but mitigate the risks of artificial intelligence in our schools?” Learn more .

We live in a world where physical textbooks are dead like the paper they were printed on. Despite my affinity for hardbound books with signatures from older brothers and sisters written in the front cover along with a list of twenty-five other students, this type of instruction is fading fast, with its own timely end, expedited by the recent pandemic.

We’ve been integrating AI into classrooms since the first adaptive assessments became part of end-of-course exams. Today it’s even commonplace to have adaptive homework, tutoring, and in-class assessments on a “one to one” device basis. This type of AI in education relies solely on an input method focusing on the student .

Plenty of educational vendors promise results to narrow the achievement gap, which existed long before Covid. Many AI platforms have been in existence in classrooms for decades at the best schools, with the well-funded budgets, who offered “one to one” well before the feds required it for standardized testing. But our students’ achievement hasn’t kept pace with the promise of these technologies.

The answer to our AI innovation in education isn’t solely a student-centered approach with inputs only and teachers as device monitors. In fact, AI is safest and most effective when it is focused on the adult in the room, instead of minor children. As existing achievement gaps persist for the student, we should be focusing on an input model for the teacher . It has been widely written that the impact on students of having a high-quality teacher in the classroom cannot be ignored no matter what content you have on a device.

Enter robot teachers, the next generation of education, requiring no sleep, no sick days, and no student loan debt to pay off. They can harness the power of the infinite knowledge available through an internet connection and customize to every single student’s needs. Common to other types of educational software on the market, robot teachers would have real-time feedback from student assessment, content to accelerate or catch up students who are not ready for what’s next, and a dashboard for the teachers to see how students are doing.

Yet robot teachers, let’s call them AI coaches, go beyond what is part of the classroom today by helping teachers become high-quality teachers in real time, without going back to school, with the students they have in class today. Using the best pedagogy methods, human psychology, and research-based methods of instruction in real time, the teacher becomes a pilot navigating their classrooms with the benefits of AI.

Leveraging the endless information already available, AI coaches will curate content to assist the teacher in inspiring students to fully dive into what they are learning and develop a deeper level of inquisition for the student sans Google search bar. Curriculum linkages both horizontally and vertically to other subjects throughout the school, AI curricular mapping, and real time progress that provides feedback to teachers will help automate the high-quality teaching throughout the school year, reducing boring hours in irrelevant teacher professional development and associated costs.

Using Ralph Tyler’s four-phase curriculum cycle of analysis, design, implementation, and evaluation ( Tyler, 1949 ) as a basis for the AI coach process design, a camera follows the teacher while she is instructing students doing an analysis based on speech, body language, and delivered content. Students perform AI created tasks on a device, which then provides instant feedback to the teacher, which many are accustomed to today, and informs the AI coach’s design process to prompt the teacher immediately with review, teaching strategies, or new content.

During the “analysis phase,” as AI coach records the teacher instructing, students would respond to quick assessments throughout the class. Instantaneously, given the nature of AI, the teacher would receive AI coaching. This coaching would provide a high-quality example for the teacher to work through with the students, along with a new short assessment for the students to see who now understands the material.

With the precision of a surgeon, the teacher could focus on students who didn’t understand the concept using another example tailored to their current understanding of the subject, while other students were guided to explore the topic further to read or write more on the subject and/or do additional problems, with no lost time for students who already are proficient on the topic.

Using the data from the analysis phase, the AI coach will design and recommend the next steps for the teacher in real time. Options include the teacher moving on to new material or additional content based on its horizontal and vertical integration of what is happening in other classes, subjects, or grades through a high-quality example. It can also recommend students take a break with content for the break, or provide a high-quality example for the teacher to work through with individual students while splitting the remaining students into countless groups or individual assignments tailored to each student’s progress and interests.

During the “implementation stage,” the teacher is working through a high-quality example with students who need it, while, unlike today, the rest of the class isn’t left idle with lost learning time, but instead, using this horizontal and vertical framework across grades and classrooms, the AI coach would provide additional content. For example, for a student in sixth grade math who is doing well on this topic, the AI coach would present basic Euclidean theory, a short biography of Euclid as a preview for upcoming geometry class, or a battlefield from WWII that used this math to determine where to drop resources linking it to a topic studied in social studies. For students who need additional help, the AI coach would provide high-quality coaching, including other methods of teaching or other high-quality examples with linkages to other subjects that increase comprehension and move towards proficiency.

Another benefit to teachers during this phase is AI device control that keeps students from navigating away from the content. If a student tries to navigate away, the student can be reminded of why it’s important to stay on topic, and could even suggest a break for that individual student, including standing up and stretching or a “brain break” activity. In addition, it could ask the student to self-reflect on their work in the class, other classes, or another topic entirely.

Not only will AI coaches help students in real time, during the “evaluation phase,” the teacher will reflect using collected data, experiences in the classroom, and be able to review videos created by the AI coach with suggestions on how the lesson could have been implemented better or additional strategies that the teacher could use in the future. These videos would be of the teacher, but created by the AI coach so they can see themselves giving the lesson. The teacher could use this tool for reflection whenever they wanted, daily or weekly. The teacher could include notes on which subjects need to be reviewed again based on the data and get insights on which kind of teaching methods work for each of their students. The AI coach could even design assessments based on the data and align them to standards negating the need for the use of a curve. The data has endless possibilities for the teacher and school leadership.

Principals would review a dashboard of data daily and/or weekly looking at real-time student progress and recognize teachers who are excelling more frequently. A principal could also use these data for curricular implementation, points of content intersection across the school, and to design new innovative programing for the students. Teacher evaluation would become more useful and simpler, and training a substitute teacher corps on the AI coach means that teachers can actually take days off without student learning loss .

While technology will continue to fill in the gaps through tutoring and curriculum integration, it won’t replace having a high-quality teacher at the front of the classroom, which our country desperately needs. Covid dollars will run out, and trained high-quality teachers will still be needed. To get the training teachers need, no other medium will deliver what AI can bring to the teaching profession. Teachers will learn skills to teach in a much more meaningful and fulfilling way each day, and manage their classrooms more effectively assisted by AI coaches. AI is best used and safest when it’s focused on the teacher. This advancement could lead to every child having a high-quality teacher, with a world of knowledge on teaching at their fingertips, no matter where they live.

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Teachers, the Robots Are Coming. But That’s Not a Bad Thing

Bring up the idea of even the possibility of artificially intelligent robots replacing some of what teachers do, and you are likely to spark a tornado of anger among many educators. Intelligent machines could never match human interactions, they argue. Such moves would be a giant step toward a digital dystopia in education.

That kind of reaction to the role of AI robots in education clearly played out in our recent Big Ideas survey of K-12 teachers, which featured questions about robotics. The vast majority of teachers, 84 percent, disagreed with the suggestion that student learning would likely improve if more K-12 teachers had AI-powered robots working with them as classroom assistants. More than 90 percent did not think that student learning would improve in classrooms where chronically low-performing human teachers were replaced by artificially intelligent robots.

It makes sense that teachers might think that machines would be even worse than bad human educators. And just the idea of a human teacher being replaced by a robot is likely too much for many of us, and especially educators, to believe at this point.

But consider the case of a computer science professor at Georgia Tech . According to the Global Education & Skills Forum , this professor had a mix of online teaching assistants, and all of them were human except for one. The teaching assistants were available via email to answer questions. Only one student in the class thought one of the teaching assistants was not a human being, because that assistant tended to answer questions much faster than the others. That student was right.

The forum—part of the London-based Varkey Foundation, which brings together leaders from public, private, and social sectors from around the world to show how improving education can help solve global problems—posed a provocative question on its site that caught my attention: “Robots replacing teachers is a good thing—yes or no?”

The better question might have been: Can robots help teachers improve classroom learning?

In China, they are testing that question. Hundreds of kindergarten classes in the country are now using a small robot named KeeKo, which tells stories, poses logic problems, and reacts with facial expressions when students master content. The robots are part of a big push in the country to be the world leader in the use of AI-powered technologies.

“Technology is a wonderful tool, and it can help with many individual tasks,” said Darrell Billington, a 25-year veteran social studies teacher at Fairview High School in Boulder, Colo., who responded to our national survey of teachers. “But in education, there needs to be some sort of relationship. I don’t think artificial intelligence is there yet.”

But researchers are trying to get there.

Consider the work of Cynthia Breazeal, an associate professor of Media Arts and Sciences at the MIT Media Lab, who leads the Personal Robots group.

The group is conducting randomized control trials of the use of an AI-powered, teddy bear-sized and -looking robot named Tega in Boston-area schools that have large English-language-learner populations. The goal of the robots is to improve the language and literacy skills of 5- and 6-year-olds. Researchers are tracking gains in the youngsters’ vocabulary and oral language development to determine how the use of human teachers and artificially intelligent robots together in classrooms compares with instruction without robots.

“We’re starting to see some exciting and significant learning gains,” Breazeal said. “I am very encouraged.” But she conceded that a longer, bigger study is the next step.

What is particularly interesting is the research Breazeal and her colleagues are doing around social robots . In their study “Growing Growth Mindset With a Social Robot Peer,” young children played a puzzle-solving game with a peer-like robot. The social robots were fully autonomous and programmed to either exhibit a “growth mindset” (modeled after the work of Carol Dweck and Angela Duckworth) or a “neutral” mindset. Breazeal found that children who played with the growth-mindset robot were more persistent when trying to solve the puzzles compared with the kids working with the neutral robot.

And Breazeal points out that it is not just young children who respond positively to social robots. The team has used social robots with MIT undergraduates and older adults. “We see a social-emotional benefit across age groups,” she said.

30% of teachers cited “grading” as a task that robots could do to help improve their teaching.

That social connection also seems to be much stronger with physical robots rather than intelligent tutors or agents students view on computer screens. Jamy Li, an assistant professor in the Human Media Interaction group at the University of Twente in the Netherlands, conducted a review of 33 studies that examined how adults and children interact with physical versus virtual robots. The analysis, published in 2015 in the International Journal of Human-Computer Studies, found that adults and children tend to have more positive interactions with physical robots and find them more believable than virtual robots.

Now, of course, there are all kinds of red flags that go up when you start talking about artificially intelligent robots playing a bigger role in teaching. Data privacy is a big one, with huge fears that kids would share personal information with an artificially intelligent robot they trust, and that information could get in the hands of people who should not see it. Plus, if the information that is input into the robots to allow them to learn is biased or skewed, that would make the judgments of the robot flawed.

And there is the value of human connections. If students started feeling much more comfortable interacting with robots rather than human beings, and preferred the machines, they might jeopardize their willingness and ability to have meaningful conversations or relationships with other people. In some ways, you already see those troubling signs in how many young people (and even some older folks!) prefer to text back and forth to each other rather than have a face-to-face conversation.

Breazeal recognizes those downsides. For starters, the AI field right now is not diverse or inclusive and that could affect the kinds of technologies being developed and fuel potential biases in the software. And, “we need to be thinking more deeply around ethics,” she said, “particularly with AI with children.”

But that’s exactly why educators should not be putting their heads in the sand and hoping they never get replaced by an AI-powered robot. They need to play a big role in the development of these technologies so that whatever is produced is ethical and unbiased, improves student learning, and helps teachers spend more time inspiring students, building strong relationships with them, and focusing on the priorities that matter most. If designed with educator input, these technologies could free up teachers to do what they do best: inspire students to learn and coach them along the way.

And what the developers of these technologies might need to consider is what matters most is often in the eye of the beholder.

In our survey of teachers, we also asked them to rank duties they think AI robots could replace to help them do a better job teaching. The top-ranked response (44 percent of teachers) said “taking attendance, making copies, and other administrative tasks,” 30 percent said “grading,” and 30 percent said “translating/communicating with emerging bilinguals.”

But Billington, the Colorado teacher, takes exception to turning attendance over to robots. That is often the one time in which he has a face-to-face interaction with some students. “Do they look happy? Are they sad? What is their mood? I would be sad if I had to give that one up.”

On the other hand, when we spoke, Billington began to calculate aloud the time it takes to grade essays: “If I take three minutes per student, and there are 120 students, that’s six hours of work. And most assignments take longer than that to grade.”

He paused, adding: “If AI could help us figure out a way to help us grade faster, that would be amazing.”

As it is, Billington remains heavily skeptical of AI-powered robots becoming a regular feature in U.S. classrooms in the foreseeable future. But he also cautions educators to never say never. It would be “stupid,” he said, “to think it can’t happen.”

A version of this article appeared in the January 08, 2020 edition of Education Week as How Come Robots Can’t Be Teachers?

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Science News

Robots are becoming classroom tutors. but will they make the grade.

Mechanical mentors try to find their place as teacher’s helper

CAST OF CHARACTERS Researchers are testing a motley crew of robots to serve as tutors and learning companions for children in classrooms or at home.

Here to help

Before grading robots on their teaching abilities, consider why automated educators might work better as physical rather than virtual entities. It turns out that a robot’s body may be just as important as its brain. A review of 33 studies that examined how adults and children respond to physically present robots, videos of the robots and animated versions of those same robots revealed that people generally view physical robots more positively and find them more persuasive than videotaped and animated robots. Jamy Li of the University of Twente in the Netherlands reported these results in 2015 in the International Journal of Human-Computer Studies .

“There’s something about robots that sets them apart from a computer,” Belpaeme says. “The exact same content delivered by a robot somehow makes our brains sit up and pay attention…. We don’t yet know why that is.” Still, roboticists have exploited that attention-grabbing edge to build machines that relay information on everything from math to nutrition and sign language.

Of course, a well-rounded education is about far more than learning facts. It’s also about developing good study habits and attitudes toward education that will make students lifelong learners. In this area, robots have proved useful.

On a very basic level, robots can make schoolwork more fun, proponents assert. “If kids enjoy learning, they’re going to learn more,” Belpaeme says. “It’s really as simple as that.” Researchers at the University of Wisconsin–Madison witnessed robots’ power to make schoolwork fun when they designed a bot named Minnie to support children’s reading at home. Minnie, described last August in Science Robotics , comments on a book as the child reads aloud, shows emotional responses to stories and summarizes plot points to support reading comprehension.

Roboticist Bilge Mutlu and learning researcher Joseph Michaelis randomly assigned 24 students ages 10 to 12 to either two weeks of reading aloud alone or with Minnie. Afterward, the solo readers gave the activity more mixed reviews, reporting, for example, “I didn’t not like it, but I didn’t, like, really enjoy it.” Only four said the activity motivated them to read more. Kids in the robot group said reading to Minnie was “fun” and “a cool experience.” Seven students said they felt more motivated to read.

Robots can also encourage specific reasoning strategies, such as thinking aloud, which is supposed to help students craft more deliberate, organized plans for multistep problem-solving. Computer scientist Chien-Ming Huang of Johns Hopkins University and colleagues programmed a Nao robot to nod along with a child’s speech and remind students who lapse into silence to keep going.

More students who read aloud with a robot companion said that the activity motivated them to read and increased their reading comprehension than students who read aloud alone.

A robot helped with reading

Source: J. Michaelis and B. Mutlu/ Science Robotics 2018

To test whether this supportive robot helped students learn, researchers randomly assigned 26 kids who were about 11 years old to solve math word problems while thinking aloud with or without the robot’s encouragement. From a pretest to a posttest taken about one week later, the robot-trained children increased their own scores an average of 52 percent ; solo students self-improved by an average of 39 percent, the researchers reported last March in Chicago at the International Conference on Human-Robot Interaction, or HRI 2018.

For a more deep-rooted effect on students’ educational experiences, robots can model certain beliefs about learning, like a growth mind-set: the idea that success comes from effort and perseverance, rather than inherent ability.

In one experiment, 33 children ages 5 to 9 solved geometric puzzles called tangrams with a Tega. Half the kids partnered with a robot that made growth mind-set comments, such as, “You are not afraid of a challenge. I like that!” Other students worked with a bot that stated facts only: “You solved the puzzle.”

Before and after working with the robot, each child completed an assessment that rated growth mind-set from 0 to 10. The growth mind-set cohort’s scores, on average, increased a small amount , 7.63 to 8.06, but the neutral bot group’s scores dropped from 6.94 to 6.59, Breazeal and colleagues reported in Vienna at HRI 2017.

Personalization problems

Although robots show the potential to positively influence students, tailoring a bot’s behavior to an individual is still a major challenge. Roboticists have created machines that can make some simple decisions, like choosing when to encourage a student to take a break . In a study presented at HRI 2017, Scassellati’s team found that when robots offered breaks as a reward for good work, or an opportunity to refocus if a student was struggling, children learned more than if the robot called time-outs at regular intervals.

Designing robots that track student performance to adjust pacing and choose what to teach next is trickier. Some robots have been programmed to adjust activity difficulty based on student proficiency, but researchers have had trouble showing that these bots help students learn more than generic robots do.

What if robots could go beyond responding to performance by keeping tabs on how a student is feeling? Gordon and colleagues at MIT explored this idea by creating a Tega robot that analyzed facial expressions for levels of engagement and valence, which is basically “the goodness of the emotion,” Gordon says. For instance, happiness has positive valence and anger has negative. While working with students on a Spanish-language learning game that involved packing for a trip to Spain, the robot offered various types of feedback, from an excited “Woo-hoo, you’re trying so hard!” to game-related comments like, “The suitcase looks heavy.”

Read the room

One Tega robot watched students’ facial expressions after giving feedback on an educational activity and learned to offer comments that made kids happier.



Child’s facial expression for engagement and emotion	Child’s performance in game

“The robot slowly learns which … behaviors result in high valence and high engagement,” and becomes more likely to use those behaviors at the right time, Gordon says. In three to seven sessions over two months, two groups of nine preschoolers worked with either this adaptable Tega or a nonadaptive Tega. From the first to final session, kids in the personalized group generally became more positive about the interaction , with their valence increasing an average of seven points on a scale of −100 to 100. In the impersonal group, valence dropped an average of 18 points, researchers reported in Phoenix in 2016 at an Association for the Advancement of Artificial Intelligence conference.

Robots attuned to students’ thoughts and feelings may make better tutors and learning companions if they can offer the right level of personalization without becoming predictable. But some educators are concerned about the amount of data machines would have to collect and store to do that job right. Human teachers may be able to get a general read on a student’s state of mind. But a robot designed to exhaustively analyze every facial expression or game move a child makes may be able to gather such detailed information on kids that it would constitute an invasion of privacy.

This concern was raised in a series of focus groups with certified and student teachers discussing educational robots. Some participants worried that companies might try to buy that student data from schools, Sofia Serholt, a child-robot interaction researcher at Chalmers University of Technology in Sweden, and colleagues reported in November 2017 in AI & Society .

Robotics ethicist Amanda Sharkey also notes that kids might feel compelled to share private information with a robot peer that acts like a friend. One remedy might include requiring robots to continually divulge what information is being collected and who the robots share it with, says Sharkey, of the University of Sheffield in England.

Social savvy

If privacy concerns about oversharing with robots could be addressed, kids’ comfort with robotic companions could be a strong force for good in the classroom. Scassellati recalls one first-grade boy who worked on English language skills with a robot. “He was so afraid to talk in class, he was so worried about making mistakes,” Scassellati says. But when the student worked one-on-one with a nonjudgmental, patient robot peer, “the first time he made a mistake … and the robot corrected him, he paused for a second, and then he went on, and it was OK.”

Gordon similarly recalls an especially shy student, who “only whispered in your ear; he didn’t talk at all,” he says. But “after the fourth or fifth interaction [with a robot], he started hugging the robot. Every three or four minutes, just stopped and started hugging the robot.”

Capitalizing on this potential for child-robot kinship could help keep students invested even after the novelty effect wears off, so that educational robots don’t end up collecting dust in a corner, Michaelis says. To that end, researchers have begun investigating how robots programmed to be more convivial can better hold students’ attention and improve learning.

Social robotics researcher Ginevra Castellano of Uppsala University in Sweden and colleagues programmed iCat, a yellow robot with a feline face, to express empathy to test if that would help keep kids engaged with the robot for the long term. Over five weeks, iCat played weekly chess exercises with 16 children in Portugal, ages 8 and 9. The robot, described in 2014 in the International Journal of Social Robotics , monitored the game status and students’ facial expressions and offered advice or emotional support when students looked unhappy . After the first and final interactions, kids filled out questionnaires that rated their feelings of social presence with the robot — that is, how much working with iCat felt like interacting with an intelligent, emotional being — from 1 to 5.

In an earlier study with a similar setup but a nonempathetic iCat robot, kids generally rated their sense of social presence between 2 and 4, and these scores declined between the first and fifth interactions. The empathetic iCat kept the kids at a high level of social presence — between 4 and 5 — from the first through the final session.

But robots’ sociability can be a double-edged, distracting sword, as Belpaeme’s team discovered when using a sociable Nao robot to teach 7- and 8-year-olds in the United Kingdom a strategy for identifying prime numbers. Twelve kids worked with this robot, which used social behaviors, calling the child by name and making eye contact. Another 11 students worked with an asocial bot. From a pretest to a posttest, kids who worked with the asocial bot improved their scores on a 12-point test an average of 2.18 points; the social robot group improved an average of 1.34 points, researchers reported in Portland, Ore., at HRI 2015.

The socially adept bot may have diverted attention away from the lesson ; children spent about 45 percent more time looking at the social robot than the asocial one.

Machine learning

People tend to think that educational robots are ready to replace teachers, says learning researcher Joseph Michaelis. Not close. Even if robots are good at helping kids learn specific skills through highly structured exercises, the machines still need more work to handle many activities.

Robots are good at:

Playing structured games like chess or snakes and ladders
Teaching basic math skills or foreign language vocabulary
Offering scripted responses to books read aloud
Telling prerecorded stories

Robots struggle with:

Open-ended conversations
Dexterity for physical activities such as science lab experiments
Being engaging without distracting from the lesson
Keeping students’ attention over the long term

There are other reasons not to make the robots too engaging. Huang likens the dilemma to concerns about excessive screen time, which may put young children at risk for speech delay ( SN Online: 5/12/17 ). “Obviously we have good intentions for these educational robots,” he says, “but the long-term side effects … are unclear.” Some teachers in Serholt’s focus groups expressed similar concerns that kids who spend too much time chatting with robots may lose some ability to decode human facial expressions or the youngsters may adopt more robotic mannerisms.

For Sharkey, “the main concern would be that [kids] come to prefer interacting with the robot.” A robot that’s always encouraging and never disagrees would probably be easier company than other kids. A child who spends more time hanging around agreeable machines than with peers may not develop the social skills necessary to navigate interpersonal conflict, Sharkey says.

Bridges left to cross

So far, investigations of student-robot interactions have typically lasted a couple of weeks or months at most. “What we would want to get up to is a full academic year,” Breazeal says. Roboticists also need to test their technology with children from more diverse backgrounds. Belpaeme and colleagues recently ran an experiment with tutoring robots that helped about 200 children learn a second language. Compared with most educational robot studies, 200 students is a staggering number, says Huang, but “in the real world, this is like nothing.”

Amid questions about how they should or shouldn’t behave, today’s robots are still pretty limited in what they can do. Educational robots are typically designed to work on very specific tasks. The robots still have trouble understanding the high-pitched and grammatically spotty speech of little kids and don’t have the dexterity to participate in many physical learning activities such as science lab experiments.

“We are still a long way” from educational robots that can interact with students like real people, says Ana Paiva, an artificial intelligence researcher at the University of Lisbon in Portugal. Still, it’s difficult to watch a kid doting on a fluffy Tega or making small talk with a seemingly interested Nao and not imagine a future where robots might join teachers and students in class photos.

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Humanoid robots as teachers and a proposed code of practice.

$\nDouglas P. Newton$

School of Education, Durham University, Durham, United Kingdom

This article will discriminate between kinds of robot, point to its burgeoning development and application in the home and workplace, and describe its growing use in the classroom as a teacher. It will describe its potential to support, for instance, language development, social, and emotional training [e.g., for children with an autistic spectrum disorder (ASD)], and teaching and assessment, and will review researchers', teachers', students', and parents' responses to this use. Some of these responses recognize the potential usefulness of humanoid robots, but also show an awareness that digital “thought” (AI) is not the same as human thought (HI), and show some caution about using robots as teachers. This disparity generates problems and dilemmas. These stem from, for example, a lack of discretion in decision-making, a lack of emotion (other than by simulation), a limited creative ability (in the foreseeable future), the nature of AI/HI relationships, ethical/legal matters, and culturally unsuitable programming. These matters point to the need for forethought about robot roles and for a code of practice for teachers who work with them. Derived from the discussion, such a code is proposed. The introduction of robot teachers will have significant implications for teachers' roles and their professional identity as human teachers move from being often solitary sources of learning to becoming teaching and learning managers who need to provide learning opportunities creatively. The change in teacher identity and the teacher's roles is described.

Introduction

Automation, the replacement of people in the workplace by machines is not something new, but digital technology has increased the capabilities of these machines enormously (see e.g., Fletcher and Webb, 2017 ). For instance, machines in factories manufacture cars tirelessly, precisely, and quickly, and these cars are increasingly able to drive themselves, and, at the same time, present urgent ethical challenges ( Gogoll and Müller, 2017 ). Artificial intelligence (AI) 1 gives these machines their ability to carry out complex tasks with little or no supervision. A robot is one such machine that senses, thinks, and acts and, when this is without external control, it is described as autonomous ( Lin et al., 2014 ). Sometimes, the appearance of these machines is governed entirely by function, but when this function is to interact with people, they may be given anthropomorphic form. Humanoid robots are intended to look and behave somewhat like people and they usually have some means of communicating with them.

Androids are humanoid robots which mimic human form and behavior ( Kanda et al., 2009 ). The pace of development of robotics is rapid, often encouraged by governments for its perceived economic advantages. For instance, the workforce in Japan is declining at a rate which seriously threatens its economy and the expectations of its people. Robots are seen as a part of the solution. As well as using them to manufacture goods, the aim is to put them to use as cleaners, sales assistants, museum guides, carers for the young and old, TV programme presenters, and of particular relevance here, as teachers ( Robertson, 2007 ). This is not a pipedream of robot engineers; Japan and South Korea, for instance, intend to make significant use of humanoid robots within the next decade, while interest in robot as teachers, as it is reflected in the number of publications about them, is increasing around the world ( Robertson, 2007 ; Steinert, 2014 ).

Robots in the classroom can have diverse uses. Some are objects of study for students to practice programming, others are tools which assist a teacher, some can be learning companions, and others might be autonomous teachers which provide some unit of instruction more or less in its entirely (e.g., Major et al., 2012 ; Mubin et al., 2013 ). The purpose of this article is to consider what humanoid robots that teach can do for and to learners in the classroom, and hence, propose a code of practice for working with robot teachers. Like most innovations, there may be a good side and a bad side, and care is needed to foster the former and counter the latter. The roles of the human teacher change over time with needs, new tools and teaching aids, but the capabilities and nature of AI promote teaching robots to new levels of relationship with the teacher and the learner. Instead of an unreflective application of such devices, we feel that there needs to be forethought about how they could and should be used. We begin by describing what humanoid robots in the classroom can and cannot do (currently), and describe what people have said about their use. We then raise some issues which have never arisen with other surrogate teachers, and discuss teachers' roles and identities which would be germane in a world where AI is likely to expand in application and ability.

Humanoid Robots Teaching

Clearly, as objects of study, and for students to learn about robotics, and to practice programming and control, the presence of a robot can have significant advantages for learning ( Keane et al., 2016 ). It is not as objects of study, but the uses they are put to that is the focus of interest here. Engineers have made robots which can move around classrooms, often but not exclusively those of younger children, asking questions, providing information, noting and commenting on answers, and responding to requests. They are able to recognize individual students and maintain a record of those interactions. Frequently working as classroom assistants, they may make useful contributions to learning.

Some robots have been programmed to teach a second language, and have the capacity to do more than a human teacher is generally willing or able to do (e.g., Meghdari et al., 2013 ). As well as playing games and engaging students in conversation, they can respond to students' commands in the second language ( Toh et al., 2016 ). There can be more value in this than might at first appear. In student-teacher interaction, the human teacher generally controls the conversation, and the student responds. With a robot, the student can have a more balanced dialogue and be the instigator of actions, as would be the case in everyday conversation. Some students also suffer from a more or less crippling performance emotion, like anxiety and embarrassment, which sets up an affective barrier to the development of proficiency in speaking a second language ( Newton, 2014 ). Instead of anxiously interacting with a human teacher, or another student, talking with a robot can be less emotive, and so it provides a potentially useful bridge to conversational proficiency, less anxiety and more positive attitudes to learning ( Chen and Chang, 2008 ; Alemi et al., 2014 ). In the same way, a robot programmed to be minimally expressive, and to interact indirectly can be a learning companion for a child with an autistic spectrum disorder (ASD). Over time, such children's oversensitivity to human interaction may be reduced by slowly adjusting the robot's behavior. The robot's expression and interaction are increased to accustom these children to some human-like behavior, and help them develop socially ( Robins et al., 2009 ; Esteban et al., 2017 ). Many people feel inhibited when they have to work with others. Some are too timid to express themselves openly. Lubart (2017) has demonstrated that avatars can enable anonymous participants to take risks with their thinking, to generate ideas, and solve problems. By interacting through avatars—digital substitutes for themselves—diffidence is significantly reduced. Clearly, where direct human interaction presents problems, and where teachers feel it threatens their authority or dignity, robots can be useful ( Mubin et al., 2013 ). A different way of using a robot in the classroom is to have it take the role of student, and the student's role is to teach the robot. In Japan, Tanaka and Matsuzoe (2012) found this “learning by teaching” approach to have potential when they tested it on young children learning English. Of course, the novelty of learning with something new can be engaging, although this is likely to be temporary unless what is learned is, itself, engaging (e.g., Hung et al., 2012 ). In the context of health education in the Netherlands, children (8–12 years old) have been successfully taught about chronic conditions, like Type 1 Diabetes, using a “personal” robot (one which “develops a user model and adapts the child-robot interaction accordingly”) using games and quizzes engaged in by robot and child ( Henkemans et al., 2013 , p. 175).

In the same way, there is evidence that robots can support language development, writing skills, teach sign language, enhance reasoning, and some kinds of problem solving, support self-regulated learning (SLR), and foster SLR skills using prompts, help with small group work by answering questions while, at the same time, free the teacher to give more time to other groups and to individuals ( Pandey and Gelin, 2017 ). Of course, some learning and motivational effects may be due to the current novelty of the robot in the classroom, and it is not entirely certain whether, with familiarity, such benefits will persist ( Baxter et al., 2015 ). There are indications that they can decline over time, and that, in some cases (as in vocabulary development), similar learning may be achieved using other devices, like tablet computers ( Vogt et al., 2019 ). Even the social behavior of some classroom robots may, at times, be a distraction which reduces learning ( van den Berghe, 2019 ). Nevertheless, robot teachers have at least some potential to teach successfully.

Attendant Concerns

Putting aside some current technological limitations in artificial intelligence's ability to recognize speech, and its ability to answer follow-up questions, limitations which are likely to become less in the future ( Crompton et al., 2018 ), the problem is that artificial intelligence is not the same as human intelligence, in other words, robots do not think like people. They may do so in ways which achieve the same ends, but this difference creates what Serholt et al. (2017) call “ethical tensions”.

The first one is a matter of privacy. The robot may assess a student's responses, provide feedback, and maintain records, potentially useful for a teacher. It can also use this information to build and store personal profiles which shape its future interactions. This might make its teaching more effective, but when the data is stored without the student's consent, often a minor, it may breach data protection laws, and has the risk that it will be accessed and misused. In such an event, who is responsible for the breach (or, more to the point, for preventing it)? More broadly, who is to blame for any detrimental consequences of a robot's actions ( Lin et al., 2014 )? A UK government report was of the view that: “It is possible to foresee a scenario where AI systems may malfunction, underperform or otherwise make erroneous decisions which cause harm. In particular, this might happen when an algorithm learns and evolves of its own accord” ( SCAI, 2018 , p. 135). If the robot will not have to defend its actions, will the teacher, the school, or the manufacturer be legally liable ( Asaro, 2007 )? Again as a matter of privacy, students can be monitored continuously by a robot, a process which has been used to erode prisoners' resistance, and has come to be known as psychological imprisonment ( Serholt et al., 2017 ) 2 , but seen as an extra benefit by Johal et al. (2018) .

A second concern is about the norms and values which shape a robot's program, giving it social and cultural biases. Programmers are immersed in particular cultures, and unconsciously or otherwise, their cultural norms and values are likely to be reflected in what they have their robot do ( Robertson, 2007 ; Nørskov and Yamazaki, 2018 ). For instance, in China, it is acceptable for a child to hug a teacher as a mark of gratitude, but this would be frowned on where such physical contact is proscribed ( Kanda et al., 2004 ; Mavridis et al., 2012 ). Programming might offer a choice of cultures (which, nevertheless, some might see as “ideal” behaviors, or impositions of others' values ( Sloman, 2006 ), but this would be much more difficult when some fundamental ideology shapes the very nature of how the robot will teach.

Another concern is that students may spend a lot of time interacting with robot teachers. Children in particular learn much by imitation ( Bandura, 1962 ; as do some robots, e.g., Schaal, 1999 ), but if they do not have adult humans to imitate, will their interpersonal behavior be adversely affected? For instance, in Australia, it was found that “the children mimicked the robot's interaction styles, suggesting social modeling was occurring” ( Broadbent, 2017 , p. 633). This was also noted in the diabetes teaching study mentioned above, where the children encouraged and complimented the robot, mimicked how it spoke, and used its vocabulary. Such children can believe the robot has mental states and feelings, offer it comfort, and tell it secrets ( Kahn et al., 2012 ). This generates unease about the development of an ability to relate to one another with empathy, sympathy, consideration, discretion, tolerance, and some understanding of the human condition. Of course, children often play at being something else, so perhaps the robot could teach them how to interact with people. Social robots are designed to be “user friendly” in that they are intended to interact with people, identify emotions, simulate emotions, and provide appropriate although unfelt (some would say deceitful) responses (c.f. chatbots). These robots are given appearances that people see as friendly, and human-robot emotional attachments can form, albeit one-way ( Beran and Ramirez-Serrano, 2011 ; Toh et al., 2016 ). A concern is that some children will begin to adapt to and prefer the more amenable and predictable human-robot relationships, lacking in the “reciprocacy of human-human relationships” ( Serholt et al., 2017 , p. 616). Enfants sauvages , children who grow outside human contact, are known to be deficient in social abilities, and remediation can be difficult, at best ( Classen, 1990 ). We do not suggest that this extreme will be the outcome of being taught by current classroom robots. Indeed, it may be possible to use robots to support social and emotional skills. For example, Leite et al. (2015) , in the USA, use small robots to act out a story with moral lessons for young children (6–8 years old), and Wolfe et al. (2018) shared teaching about emotions with a social robot. Serholt and Barendregt (2016) point out that while children do engage socially with robots, interaction may reduce over time, and the child-robot relationship may not be the same as a child-adult or child-child relationship. Very young children, however, have been found to treat a humanoid robot more as a peer than a toy, but the nature of the relationship is likely to change as the child develops ( Tanaka et al., 2007 ). Nevertheless, reduced interaction with people could begin to degrade human-human behavior, simply because there is less opportunity for learning its complexity and subtleties, and how to respond when human-human interaction fails. The risk would be greater if education was automated, particularly for the young, but schooling is unlikely to be entirely automated in the near future, given AI's current limitations. Nevertheless, boundaries of automated teaching will be explored as new applications are envisaged, as when television robots are used to teach children unable to attend school due to illness or remoteness (e.g., Newhart et al., 2016 ).

Yet another concern stems from the kinds of thinking and habits of mind that robots may promote. Bakshi et al. (2015) have described how the digital revolution will affect the workplace. They see AI as doing those tasks which can be rendered into routines, putting some 47% of jobs in the USA and 35% of jobs in the UK at risk. People will be left largely with work that is currently beyond the capability of AI. Bakshi et al. see this as centered on creative activity and problem solving [which can, of course, involve AI (e.g., Savransky, 2000 ; Rea, 2001 )]. Education needs to respond to this future by preparing its students for it (e.g., DCCE, 2017-19 ). Can a robot usefully support the range of purposeful thought expected of students in the classroom? As far as memorization and recall of facts, figures, and procedures are concerned, it seems likely. Robots are increasingly able to ask questions, recognize correct answers, exercise students' recall, give immediate feedback, and record students' progress in this kind of purposeful thought. A robot may also expound a topic, present information, direct attention to what matters, and then check for understanding with tasks requiring specific predictions and applications. But how well a contemporary robot can cope with responses that cannot be pre-determined is unclear, as in creative thinking where its products are potentially infinite. Similarly, it is questionable whether the robot could adequately assess thinking which involves personal values, beliefs, and goals, as in decision-making ( Newton, 2016 ). The danger is that what robots can do becomes only what is done, and that is seen as a complete education. Of course, it could be worse if students learned to leave their thinking entirely to AI.

Finally, there is the matter of how the robot teaches. Teaching has been called “emotional labor.” This is not simulated emotion, but felt and acted on emotion. It is what makes teachers devoted to their subject and to teaching, and to teach with passion, not false passion ( Newton, 2016 ). Can a robot, without deceit, feel or even communicate that devotion? Can it, with honesty and belief, bring students to love learning or a subject and give their lives to it? And will it be remembered in years to come as the teacher who made a fundamental difference ( Howard, 1998 )?

Human Reflections

What do people think about robots as teachers? Care is needed here as experience of classroom robots is, as yet, relatively limited, and non-existent in some parts of the world. Some studies have collected views from those without direct experience. Any expressed willingness to interact with robotic teachers may be due to their novelty, and may decline with familiarity (e.g., Robins et al., 2009 ; Broadbent, 2017 ). At the same time, what classroom robots do also varies. For instance, Fridin and Belokopytov's socially assistive robot in Israel could play educational games with pre-school and elementary school students, and teachers were favorable toward using it (although, in this case, they were probably pre-disposed by prior interest; Fridin and Belokopytov, 2014 ). But cultures and educational systems vary around the world so views in one context may not generalize entirely (or at all) to another. With that in mind, we begin with some views of the general public.

Two pan-European surveys found the general public to be broadly positive about robot applications in general, but with some variation, largely from northern to southern countries, with the former tending to be more favorable than the latter. While four out of ten people were comfortable with using robots in education, more than three out of ten had reservations, and few saw it as a priority. Younger people, men, and those with more years in full-time education tended to be more favorable ( TNS Opinion and Social, 2012 , 2015 ). A thought-provoking study by Mavridis et al. (2012) in the Middle East usefully addresses the gap between Western and Far Eastern studies. Interaction with their android robot (Ibn Sina, simulating an Islamic philosopher of that name of a thousand years ago) provided the opportunity to collect responses from conference delegates from around the world. As far as children's education is concerned, this opens a window into what parents' responses might be. Those from South-East Asia were more positive about the prospect of robots teaching their children than those from other parts of the world. The Far East is where there is a lot of research on such applications. Nevertheless, there can still be some hesitation about using robots as teachers ( Lee et al., 2008 ). Those from Europe and the USA recognized that children might like it but had reservations about their use. This indicates the current climate surrounding the potential adoption of robot teachers.

Conde et al. (2016) report their exploratory study in Spain of a robot, Baxter, teaching students from roughly Kindergarten to 18 years of age. Baxter could be described as being toward the less humanoid end of the spectrum in appearance. Most of the students said that they felt comfortable interacting with robots, and the younger ones in particular thought they could be friends with them. The effect of direct experience with the robot did tend to lessen concerns about interacting with them, and, as might be expected, the younger children tended to be less critical. Broadbent et al. (2018) , p. 295 suggest that “children accept robots easily because they have a natural ability to empathize with objects and interactive devices,” as is the case with some of their toys. Their study, in New Zealand, was of a similar age range to that of Conde et al. but their robots were designed to be more toy-like in appearance (one, Paro, was like a young seal). Again, most children were comfortable with the robots, and talked with them; the highest level of engagement, however, was by the primary/intermediate school children. It has to be remembered, however, that these robots were intended largely for use as companions in isolated rural schools with small student numbers, with some application in, for example, practicing mathematics or a language. When they are used mainly as teaching assistants, such students say they are willing to talk to them, and be their friends, although few wanted robots to grade their work, monitor their behavior, or replace human teachers ( Fridin and Belokopytov, 2014 ). Earlier studies in Japan by Kanda et al. (2004 , 2009) and in South Korea ( Shin and Kim, 2007) also found that children established what might be called friendly relationships with a robot, even when it was not particularly humanoid in appearance.

Serholt et al. (2017) , p. 295 held focus groups of practicing and pre-service teachers studying for a Master's degree in Education in Sweden, Portugal, and the UK. The groups were generally positive about digital technology although none had direct experience of robot teachers. Regarding matters of privacy, the teachers pointed out that data about students were already stored electronically, but there was some concern about the nature of what would be stored, the risk of unauthorized use or use by state agencies, surveillance, and the lack of control of that data by the students or their parents. Nevertheless, there was some feeling that this should be set against a background of society's decline in concern for privacy in the digital age. It was felt that robots could be useful in routine teaching (referred to as “training”), but that they lacked the perception and insight needed to help students overcome their difficulties, and should not take decisions affecting students that teachers are uniquely able to fulfill [like grading students' work; noted in an earlier study by Serholt et al. (2014) ]. Their concern was that this would not be recognized, and autonomous robots would eventually replace teachers. As a consequence there would be a dehumanization of children, and they would become over-reliant on robots for their thinking. Some also felt that working with robot assistants would make teachers passive and over-reliant on AI for what happened in the classroom. For these teachers, an acceptable role for the classroom robot was seen as a controlled, instrumental one. In the UK, Kennedy et al. (2016) similarly found what they call “cautious but potentially accepting” attitudes amongst some primary teachers in the UK, with an additional concern that some children might be isolated by interacting mainly with the classroom robot. They point out that teachers' beliefs and attitudes are important as they at least partly determine if and how technology is used. At the same time, we must bear in mind the children's increasing exposure to digital devices in their homes.

Given these views, Johal et al. (2018) claim that there is resistance to the acceptance of robots is a little overstated. On balance, these studies indicate that, at this stage, there is a cautious interest in their use as teaching assistants. There could, however, be another side to this in the future: there is also the robot's point of view. Baxter et al. (2015) noticed that teachers seem inclined to treat robots as having particular roles, like that of “informant.” Steinert (2014) has grouped robots in general into those which are obedient instruments, and those which autonomously take decisions and act on them. The first cannot be held responsible for their actions while the second may, in due course, become so. If they do, how will being an informer affect their role? Steinert adds that humans may behave toward robots in various ways, and mentions that children tend to treat robots as they do animals. Children have also been observed to abuse robots when adults are absent (see, e.g., Broadbent, 2017 ). Few would doubt that human teachers have a right to safety and freedom from bullying in the workplace, but at what point will the robot be allowed such rights? This may be a matter for the future, but if some future autonomous robot is to be nothing more than a slave like slaves of the Ancient World (and “robot,” coined by Karel Capek in the 1920s, refers to the coerced laborer of central Europe's feudal system; Robertson, 2007 ), it is a question which may need to be answered. This, however, may be a concern for a later generation, but some speculation already touches on it ( McCauley, 2007 ; Gunkel, 2018 ), and a definition of “cyberlife” has been contemplated ( Korzeniewski, 2001 ).

Education, Robots, and Teacher

Aids to teaching and learning are not, of course, new. Textbooks, for instance, are long-standing surrogate teachers which have found wide application around the world, but no-one has concerns that children will behave like a book. Humanoid robots, however, are more active, even pro-active. Unlike the passive textbook, they can respond and adapt to each student, tailoring teaching to particular needs. There is clear evidence that they have the potential to support learning, as in teaching children about their medical conditions, developing and rehearsing learning, and testing it. They can also take on teaching roles which human teachers may find time-consuming, uncomfortable, inhibiting, or unfeasible. For example, they can patiently help a student practice a skill or procedure, practice conversation in a foreign language, or act dumb and be “taught” by the student. They can even do what a teacher would find difficult by his or her presence, as in teaching an ASD student while slowly accustoming that student to social interaction. Belpaeme et al. (2018) , p. 7 provide a positive and well-evidenced evaluation of the potential of robots to enhance learning through their physical presence in the classroom. They concluded that, “Robots can free up precious time for human teachers, allowing the teacher to focus on what people still do best: providing comprehensive, empathetic, and rewarding educational experience.” But, beyond a mere division of labor, there is likely to be an increasing potential for a productive collaboration between HI and AI ( Ball, 2019 ).

To set against this are concerns about privacy, malfunction, and perpetual surveillance. Matters of privacy and legal responsibility may be eased through legislation, although probably not eliminated. EPSRC (2011) principles for the design and manufacture of robots makes humans responsible for all that a robot does, but wants robots to be designed “as far as practicable to comply with laws, rights, and freedoms, including privacy,” a leeway criticized by Müller (2017) , but one reflecting the practical limits of what is currently implementable ( McCauley, 2007 ) 3 . A fail-safe approach to robot manufacture and some form of override control may minimize malfunction effects, and time-out for the robot would give students a break from its all-seeing vigilance. There may also be concerns about robots which make decisions about what is educationally appropriate for a particular student. AI decisions may not be the same as those of a human teacher who understands a student's motives, values, and goals, and the emotions which drive the student's behaviors, and so can exercise discretion, or tune a decision to allow for these. There are also concerns about effects on habits of mind a robot may encourage. Entirely dispassionate thought is not possible for people, and, at times, it may be inappropriate for a fulfilling, rewarding life ( Newton, 2018 ). It may result in a neglect of certain kinds of purposeful thinking (although there is the risk of that with a human teacher; Newton and Newton, 2000 ). There are, however, concerns about its effect on human-human interaction and relationships. Children have been observed to mimic the robot and treat it as though it is like themselves, but children in their pretend play may give certain toys human attributes, and become emotionally attached to them. Nevertheless, children generally know that their toys are not alive. Robots, however, are becoming increasingly anthropomorphic and it remains an open question how well children will discriminate between robots, animals and humans in the future. Clearly, robots can shape social behavior, as their effect on ASD students has shown, so this seems to have some foundation. In addition, technology can change and even encourage new behaviors, as with the Smart phone and immersion in some virtual worlds (e.g., Persky and Blascovich, 2006 ). Robots may shape the kinds of thinking that are practiced and tested, and even an inclination to think in certain ways. Belpaeme et al. (2018) , p. 7 ask how far we want to delegate education to machines with the risk that “what is technologically possible is prioritized over what is actually needed by the learner.” At times, the notion of technological determinism has been a contentious one (for a discussion, see e.g., Paragas and Lin, 2016 ; Hauer, 2017 ). In this context, however, there is a danger that the capabilities of the technology could directly determine what is learned. There is also the matter of equity of access. Students in different parts of the world, and even in one region, are likely to vary in the amount and kind of access they have to digital technology, including robot teachers (see, e.g., Dimaggio et al., 2004 ; Pöntinen et al., 2017 , or perhaps more pertinent here, to human teachers).

This should be seen in a setting of moderately positive attitudes toward robot teaching assistants, although parents and teachers are more cautious than students. This caution generally does not reflect an anti-robot attitude, and may be useful in prompting constructive thought about robot-student interaction. We should expect robots to continue to develop in capability, and adults' concerns may be greater if the robot was the sole teacher. However, as robots become more common in the home, at work, in hospitals, and in the high street, so, too, are they likely to be accepted in the classroom. This, in itself, is not a bad thing. We must prepare children for the world in which they will live, and enable them to develop “digital literacy.” As a UK Select Committee ( SCAI, 2018 , p. 77) suggest: “All citizens have the right to be educated to enable them to flourish mentally, emotionally and economically alongside artificial intelligence.” Nevertheless, we should consciously decide when we will draw on a classroom robot's potential, rather than drift haphazardly into its use.

If the benefits of AI in the classroom maximized, and potential harm minimized, teachers' roles will need to change. It has always been easier to give more time to memorization than to understanding, and to creative, evaluative and wise thinking, but the problem today is more one of dispelling the data smog and using information wisely, than committing data to memory (e.g., Newton, 2012 ). In the future, competence in creative and evaluative thinking is likely to confer greater advantages than today. The balance of a teacher's role will need to move much further in this direction (and examinations will need to do the same if they are not to undermine the move). Teachers will need to see their primary goal as developing their students' competence in these kinds of productive thought. This, of course, requires knowledge of strategies and activities which support it, and this may involve professional development and training. But these teachers will be supported by robot assistants whose current strengths may not lie in this direction. Teachers will need to learn to use them in ways which support this move in thinking, as when they help a student acquire pre-requisite skills and understanding, assist students with a ready supply of information so they can practice creative and critical thinking, and show them unlimited patience in developing ideas, and putting them into effect through scaffolding activities. But, during this, the teacher must watch for any tendency of students to economize mental effort and leave thinking to the robot. In the process, however, we must take care that students, particularly the more vulnerable and younger students, are not adversely affected by digital technology. With such children, the teacher will have to be equally watchful for any tendencies to adopt dehumanizing robot behaviors, other than playfully. The development of an understanding and appreciation of human behavior, particularly the emotions and how they shape it remain a priority. Nevertheless, children may need to learn to interact with robots appropriately, bearing in mind that in their lifetimes, humanoid robots will become more sophisticated. Teachers plan what they will teach, but in the future, this planning will need to include the robot assistant, be more reflective about what is being learned both formally and informally, and, importantly, what is being overlooked. This oversight role of teaching may be supported by the robot's ability to collect and maintain information about each child, and even to recommend what may be needed next, but the teacher will need to defend that data from illegitimate access. Given the speed at which AI is developing and is realized in robot form, it is surprising how little attention is being given to it by those who concern themselves with “the future of education” (e.g., BERA, 2016 ; DeArmond et al., 2018 ). The teacher's role is, of course, culture dependent, and what is appropriate in one milieu may not be in another. This means that variations on the theme are to be expected, and some may be radical, but the presence of a robot teacher will bear upon what a teacher does and can do, wherever it is. With this caveat, we venture to offer a code of practice for teaching with robots.

Before enlisting the help of a robot teacher, a school should develop a policy on its use which should be reconsidered from time to time, and especially when that robot is supplemented or replaced by a more capable robot. This should include a code of practice. Suggested by the above account and relating to current classroom robots, we offer the following:

A Code of Practice 4

1. There should be a collective judgement of the suitability of the assumptions, values and beliefs reflected in the robot's teaching, and also about matters that should be reserved for the human teacher.

2. A human teacher should be responsible for arranging and managing the learning environment, and for the kinds and quality of teaching and learning which takes place.

3. A human teacher should be present when a robot teacher is in use 5 .

4. Care should be taken to ensure that data collected by the robot or human teacher is secure, and is maintained only for the minimum length of time it is needed, after which it is destroyed 6 .

5. Decisions taken by a robot about teaching and learning should be monitored and, if judged inappropriate, changed at the teacher's discretion.

6. Younger children should not interact only or predominantly with a robot teacher; an upper limit of time in robot-human interaction should be imposed 7 .

7. The teacher should ensure that young children see, experience and reflect on human-human interaction in ways which illustrate its nature, and exercise the skills of interpersonal behavior.

8. The teacher should ensure that children interact with robot teachers appropriately.

9. Care should be taken to discourage a habit of shallow thinking arising from robot use, or of leaving thinking and decisions to the robot teacher.

10. Care should be taken to ensure that children exercise a wide range of thought in the classroom, giving due weight to higher levels of purposeful thinking and to thinking dispositions, and for which the human teacher should be largely responsible 8 .

Teacher identity, or what it means to be a teacher, is an evolving complex collection of personal roles, behavioral norms, and social and cultural expectations ( Akkerman and Meijer, 2011 ). The Code of Practice, as a collection of expected roles and norms of behavior, would influence a teacher's professional sub-identity relating to working with robots. Roles centered upon the student-teacher relationship are a main feature of teacher identity ( Zembylas, 2003 ). Of particular relevance are behavioral norms associated with the expression of emotions ( van der Want et al., 2018 ). For instance, in some educational systems a steering, friendly, and understanding teacher is generally seen as more appropriate than an uncertain, reprimanding, dissatisfied teacher. The Code of Practice recommends that the nature of human-human and robot-human interaction becomes a conscious concern. At the same time, some human teachers may need to concern themselves less with their students' acquisition of information, routines and procedures and more with developing their competence in open-ended kinds of thinking. And examinations need to reflect this if they are not to impede such a change. But overarching this is the need for teachers to be managers of teaching and learning, creative providers of learning experience, and imaginative users of available resources (including themselves) to meet the needs of their students in a digital age. Of course, where the emphases lie may vary with student age. Whatever the phase of education, the robot may present dilemmas, but it also has the potential to free teachers so they can think more about the kinds of learning (formal and informal), the direction they should take, and the particular needs of individuals. This probably represents the main change in teacher identity that soon may be needed.

GRIN technologies (genomics, robotics, information, and nanotechnologies) are changing the way we learn, play, work, and interact ( O'Hara, 2007 ). Robot teachers offer opportunities but also challenges for teachers, unlike the classroom aids of the past. On the one hand, they make new ways of teaching and learning possible, and their presence helps to prepare children for a world of AI-enabled products with which they will have to interact daily. On the other hand, robots may degrade human interaction, encourage laziness in thinking, and narrow what is exercised to what robots can do. Their novelty is attractive, but there are understandable reservations about their use in the classroom. There is a danger that we will drift into the future without forethought about how to use and not use robot teachers ( SCAI, 2018 ). With robots present, human teachers' roles will need to change in order to maximize the benefits while minimizing the detriments. At times, this should go beyond a simple division of labor between teacher and robot (HI and AI), to include collaborative teaching between HI and AI when, together, they produce a more effective learning experience for the students, and illustrate HI/AI collaboration, modeled by the teacher. Working with highly sophisticated robots is likely to bring about a change in teacher identity, moving it from a largely solitary responsibility for students' learning toward a more or less joint enterprise, but one in which the human teacher has oversight of and manages the teaching. In the foreseeable future, robot teachers are likely to have a significant impact on teaching.

As we move into this new world, human teachers will probably need training to work with robot teachers and in AI/HI collaboration in the classroom, and they and their trainers should reflect on its pros and cons. This should be informed by research. For instance, teachers need to know how children's relationships with robot teachers change over time and with use. Some tools which may lend themselves to such research are emerging (e.g., Spirina et al., 2015 ), but teachers would also find clues to evolving relationships and the development of children's personal identities useful in the classroom. We often see research about how to support learners' engagement with new technologies. This is not a bad thing as it prepares children for the world in which they will live. But we also need research on when not to use a particular kind of digital technology, and on how to teach children (and adults) to use such technologies with discernment and discretion. The growing capabilities of AI also bring with them matters of ethics that need to be addressed and monitored. There needs to be collaboration between, for instance, robot engineers, programmers, teachers, sociologists, and ethicists to ensure that rights are observed, and cultural and ideological matters considered effectively.

Humanoid robot teachers have the potential to make a useful contribution in the classroom, and they will become more autonomous and more capable over time, but they do not think and feel like people. Those who work with them will need to think in different ways about what they do. But one thing they should bear in mind is the need for children to learn to be human ( Macmurray, 2012 ).

The Code of Practice and reflection on teachers' roles and identities offered here is intended to support that forethought and preparation.

Author Contributions

DN researched and wrote the first draft of the article. LN invited, collated, and integrated colleagues' and practicing teachers' comments on it, particularly in relation to iterations of the Code of Practice. Both also collaborated to finalize the article.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

1. ^ The definition of AI adopted by the UK's Select Committee on Artificial Intelligence ( SCAI, 2018 , p. 13) is: “Technologies with the ability to perform tasks that would otherwise require human intelligence, such as visual perception, speech recognition, and language translation.”

2. ^ This concern extends to other forms of surveillance technology (see e.g., van den Hoven and Vermaas, 2007 ; Soroko, 2016 ; Perry-Hazan and Birnhack, 2018 ).

3. ^ In this context, some refer to Asimov's Laws of Robotics (in brief, directing that robots must serve and never harm humans), but the laws have proved to be too ambiguous to implement in current robots, and if future robots can “understand” them, they would have reached a stage where it would be unethical to apply the laws to them, as the laws would enslave such robots (see, e.g., Clarke, 2011 ).

4. ^ We thank those colleagues and practicing teachers who kindly commented on summaries of the article and drafts of this Code of Practice.

5. ^ At some point, this may need modification should autonomous robots become more competent and fail-safe. Here, it is a precautionary suggestion which assumes that the human teacher has the off-switch.

6. ^ Laws regarding data management vary from place to place.

7. ^ The upper limit may depend on child age and robot function: if used to overcome a disability or disadvantage, for instance, a different limit may be appropriate.

8. ^ There may, of course, be ways in which a robot can support a teacher in this work.

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Shin, N., and Kim, S. (2007). “Learning about, from, and with Robots: Students' Perspectives,” in RO-MAN 2007-The 16th IEEE International Symposium on Robot and Human Interactive Communication (IEEE) 1040–1045. Available online at: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4415235 (accessed March 15, 2019).

Sloman, A. (2006). Why Asimov's Three Laws of Robotics Are Unethical . Available online at: http://www.cs.bham.ac.uk/research/projects/cogaff/misc/asimov-three-laws.html (accessed March 12, 2019).

Soroko, A. (2016). No child left alone: the classdojo app. Our Schools Our Selves , 25, 63–74. Available online at: https://www.researchgate.net/profile/Agata_Soroko/publication/304627527_No_child_left_alone_The_ClassDojo_app/links/5775607508ae1b18a7dfdeed.pdf (accessed October 17, 2019).

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Keywords: robot teachers, teachers' code of practice, teachers' roles/identity, digital versus human thought, fostering constructive thinking

Citation: Newton DP and Newton LD (2019) Humanoid Robots as Teachers and a Proposed Code of Practice. Front. Educ. 4:125. doi: 10.3389/feduc.2019.00125

Received: 05 June 2019; Accepted: 14 October 2019; Published: 05 November 2019.

Reviewed by:

Copyright © 2019 Newton and Newton. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Douglas P. Newton, d.p.newton@durham.ac.uk

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

AI for Good blog

The future of educational robotics: enhancing education, bridging the digital divide, and supporting diverse learners.

Robotics for Good
31 March 2023

By Alexandra Bustos Iliescu

Educational robotics is poised to revolutionize the learning landscape by equipping children with essential skills and preparing them for a future where AI and robotics are integral to their lives. However, there are challenges that must be addressed to make educational robotics accessible, affordable, and effective in classrooms. In a recent panel discussion, experts in the field explored the current state of educational robotics, its challenges, the future research directions, and the benefits for diverse learners.

“Robots increase the possibility of doing work at a distance” said Tony Prescott , Professor from University of Sheffield .

Credits: Sneh Vaswani from Miko

Role of Robots in Education

Educational robots can serve various purposes in enhancing learning experiences. They can promote active engagement, problem-solving, and collaboration among students as active learning tools. By introducing robotics in the classroom, children can develop their critical thinking and creativity skills. Robots can also serve as a scaffold for developing social skills, especially for shy children or those with special needs. Interacting with robots can be less intimidating and more predictable than interacting with peers, fostering confidence in social situations. Additionally, robots can act as co-learners or tutors, encouraging children to explain concepts or teach the robot, thereby reinforcing their own understanding.

Credits: University of Sheffield – the animal-like robot Miro-e designed for applications in research, education and healthcare

Challenges in Implementing Robots in Classrooms

Two primary barriers hinder the widespread adoption of robots in classrooms: cost and teacher training. Schools often have limited budgets, making it difficult to invest in expensive robotic equipment. The high cost of advanced robotic systems may exacerbate the digital divide between schools with access to resources and those without. Furthermore, teachers may lack the necessary time and training to effectively integrate robotics into their curriculums. With an already packed schedule and curriculum demands, incorporating robotics can be a daunting task for educators.

Addressing these challenges requires the development of better teacher training programs and government support for prioritizing robotics and AI in education. By recognizing the importance of these technologies for the future workforce, governments can promote the adoption of educational robotics.

Credits: ROBOCAT – young participants working on their robots

Accessibility and Affordability

“There has been a massive change in the past decade where kids have been empowered with new mediums of technology and parents have started getting busier in their day-to-day lives” said Sneh Vaswani , Co-Founder and CEO from Miko .

Parents are dissatisfied by screen addiction in their young kids

Parents will not prevent their kids from technology as every other child has access to it

To bridge the digital divide and ensure equal access to educational robotics, it is essential to make the technology accessible and affordable. Shared resources, such as community centers or mobile labs, can provide access to robotics equipment for multiple schools. Repurposing disused robots from universities and industries for educational purposes can reduce costs and promote sustainability. A subscription model for educational robotics can make it more affordable for consumers, allowing users to purchase a basic robot at a lower price point and subscribe to additional services and content as needed.

Hot Research Topics and the Role of Large Language Models

Current research in educational robotics focuses on swarm robotics, which explores the use of multiple robots working together to lead to more effective learning experiences. Soft robotics investigates the use of soft materials and components in robot design, opening up new possibilities for educational applications. Research in active learning and collaboration seeks to enhance active learning experiences and collaborative problem-solving capabilities.

Large language models like GPT-4 are expected to play a crucial role in enhancing conversational experiences with robots. These models, combined with improvements in emotional intelligence and collaborative problem-solving capabilities, can create more engaging and effective educational robots.

Credit: IReCHeCk EPFL

Educational robotics holds great promise for transforming learning experiences, equipping children with valuable skills for their future careers, and supporting diverse learners. By addressing the challenges of cost and teacher training, exploring innovative research areas, and focusing on accessibility, educational robotics can become an inclusive and effective tool for classrooms worldwide.

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Empowering African innovators: Bridging AI and robotics with real-world solutions

Exploring the role of socially-assistive robots in education, companionship, and care

Machine Learning

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Your pitch deck (file size max. 15MB)*

Solution/Product description (one-liner)*

What is your solution and what is the value proposition (uniqueness) of the solution/product?*

Describe clearly the use/role of Artificial Intelligence in your idea?*

Which UN Sustainable Development Goal(s) does your idea aim to achieve?*

Select the UN Sustainable Development Goal(s) relevant to your project/speaking proposal* GOAL 1: No Poverty GOAL 2: Zero Hunger GOAL 3: Good Health and Well-being GOAL 4: Quality Education GOAL 5: Gender Equality GOAL 6: Clean Water and Sanitation GOAL 7: Affordable and Clean Energy GOAL 8: Decent Work and Economic Growth GOAL 9: Industry, Innovation and Infrastructure GOAL 10: Reduced Inequality GOAL 11: Sustainable Cities and Communities GOAL 12: Responsible Consumption and Production GOAL 13: Climate Action GOAL 14: Life Below Water GOAL 15: Life on Land GOAL 16: Peace and Justice Strong Institutions GOAL 17: Partnerships to achieve the Goal

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Organization country* --- Afghanistan Albania Algeria Andorra Angola Antigua and Barbuda Argentina Armenia Australia Austria Azerbaijan Bahamas Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bhutan Bolivia Bosnia and Herzegovina Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cambodia Cameroon Cabo Verde Canada Central African Republic Chad Chile China Colombia Comoros Congo Costa Rica Cote d'Ivoire Croatia Cuba Cyprus Czech Republic Denmark Djibouti Dominica Dominican Republic Ecuador Egypt El Salvador Equatorial Guinea Eritrea Estonia Eswatini Ethiopia Falkland Islands (Malvinas) Faroe Islands Fiji Finland France Gabon Gambia Georgia Germany Ghana Greece Grenada Guatemala Guinea Guinea-Bissau Guyana Haiti Honduras Hungary Iceland India Indonesia Iran Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Kiribati Korea Kuwait Kyrgyzstan Lao People's Democratic Republic Latvia Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Mauritania Mauritius Micronesia Moldova Monaco Mongolia Montenegro Morocco Mozambique Myanmar Namibia Nauru Nepal Netherlands New Zealand Nicaragua Niger Nigeria North Macedonia Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Qatar Romania Russian Federation Rwanda Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Slovakia Slovenia Solomon Islands Somalia South Africa South Sudan Spain Sri Lanka Sudan Suriname Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Tonga Trinidad and Tobago Tunisia Turkey Turkmenistan Tuvalu Uganda Ukraine United Arab Emirates United Kindom United States Uruguay Uzbekistan Vanuatu Venezuela Viet Nam Yemen Zambia Zimbabwe

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Comoros	KM	COM	Developing
Djibouti	DJ	DJI	Developing
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Ethiopia	ET	ETH	Developing
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Mayotte	YT	MYT	Developing
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Congo	CG	COG	Developing
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Eswatini	SZ	SWZ	Developing
Lesotho	LS	LSO	Developing
Namibia	NA	NAM	Developing
South Africa	ZA	ZAF	Developing
Benin	BJ	BEN	Developing
Burkina Faso	BF	BFA	Developing
Cabo Verde	CV	CPV	Developing
Côte d’Ivoire	CI	CIV	Developing
Gambia	GM	GMB	Developing
Ghana	GH	GHA	Developing
Guinea	GN	GIN	Developing
Guinea-Bissau	GW	GNB	Developing
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Barbados	BB	BRB	Developing
Bonaire, Sint Eustatius and Saba	BQ	BES	Developing
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Cayman Islands	KY	CYM	Developing
Cuba	CU	CUB	Developing
Curaçao	CW	CUW	Developing
Dominica	DM	DMA	Developing
Dominican Republic	DO	DOM	Developing
Grenada	GD	GRD	Developing
Guadeloupe	GP	GLP	Developing
Haiti	HT	HTI	Developing
Jamaica	JM	JAM	Developing
Martinique	MQ	MTQ	Developing
Montserrat	MS	MSR	Developing
Puerto Rico	PR	PRI	Developing
Saint Barthélemy	BL	BLM	Developing
Saint Kitts and Nevis	KN	KNA	Developing
Saint Lucia	LC	LCA	Developing
Saint Martin (French Part)	MF	MAF	Developing
Saint Vincent and the Grenadines	VC	VCT	Developing
Sint Maarten (Dutch part)	SX	SXM	Developing
Trinidad and Tobago	TT	TTO	Developing
Turks and Caicos Islands	TC	TCA	Developing
United States Virgin Islands	VI	VIR	Developing
Belize	BZ	BLZ	Developing
Costa Rica	CR	CRI	Developing
El Salvador	SV	SLV	Developing
Guatemala	GT	GTM	Developing
Honduras	HN	HND	Developing
Mexico	MX	MEX	Developing
Nicaragua	NI	NIC	Developing
Panama	PA	PAN	Developing
Argentina	AR	ARG	Developing
Bolivia (Plurinational State of)	BO	BOL	Developing
Bouvet Island	BV	BVT	Developing
Brazil	BR	BRA	Developing
Chile	CL	CHL	Developing
Colombia	CO	COL	Developing
Ecuador	EC	ECU	Developing
Falkland Islands (Malvinas)	FK	FLK	Developing
French Guiana	GF	GUF	Developing
Guyana	GY	GUY	Developing
Paraguay	PY	PRY	Developing
Peru	PE	PER	Developing
South Georgia and the South Sandwich Islands	GS	SGS	Developing
Suriname	SR	SUR	Developing
Uruguay	UY	URY	Developing
Venezuela (Bolivarian Republic of)	VE	VEN	Developing
Kazakhstan	KZ	KAZ	Developing
Kyrgyzstan	KG	KGZ	Developing
Tajikistan	TJ	TJK	Developing
Turkmenistan	TM	TKM	Developing
Uzbekistan	UZ	UZB	Developing
China	CN	CHN	Developing
China, Hong Kong Special Administrative Region	HK	HKG	Developing
China, Macao Special Administrative Region	MO	MAC	Developing
Democratic People’s Republic of Korea	KP	PRK	Developing
Mongolia	MN	MNG	Developing
Brunei Darussalam	BN	BRN	Developing
Cambodia	KH	KHM	Developing
Indonesia	ID	IDN	Developing
Lao People’s Democratic Republic	LA	LAO	Developing
Malaysia	MY	MYS	Developing
Myanmar	MM	MMR	Developing
Philippines	PH	PHL	Developing
Singapore	SG	SGP	Developing
Thailand	TH	THA	Developing
Timor-Leste	TL	TLS	Developing
Viet Nam	VN	VNM	Developing
Afghanistan	AF	AFG	Developing
Bangladesh	BD	BGD	Developing
Bhutan	BT	BTN	Developing
India	IN	IND	Developing
Iran (Islamic Republic of)	IR	IRN	Developing
Maldives	MV	MDV	Developing
Nepal	NP	NPL	Developing
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Sri Lanka	LK	LKA	Developing
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Iraq	IQ	IRQ	Developing
Jordan	JO	JOR	Developing
Kuwait	KW	KWT	Developing
Lebanon	LB	LBN	Developing
Oman	OM	OMN	Developing
Qatar	QA	QAT	Developing
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Syrian Arab Republic	SY	SYR	Developing
Turkey	TR	TUR	Developing
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Yemen	YE	YEM	Developing
Fiji	FJ	FJI	Developing
New Caledonia	NC	NCL	Developing
Papua New Guinea	PG	PNG	Developing
Solomon Islands	SB	SLB	Developing
Vanuatu	VU	VUT	Developing
Guam	GU	GUM	Developing
Kiribati	KI	KIR	Developing
Marshall Islands	MH	MHL	Developing
Micronesia (Federated States of)	FM	FSM	Developing
Nauru	NR	NRU	Developing
Northern Mariana Islands	MP	MNP	Developing
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American Samoa	AS	ASM	Developing
Cook Islands	CK	COK	Developing
French Polynesia	PF	PYF	Developing
Niue	NU	NIU	Developing
Pitcairn	PN	PCN	Developing
Samoa	WS	WSM	Developing
Tokelau	TK	TKL	Developing
Tonga	TO	TON	Developing
Tuvalu	TV	TUV	Developing
Wallis and Futuna Islands	WF	WLF	Developing

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Robot TeachersTransform Education

Topics & Resources
Robot Teachers Transform Education

Date Published:

Nov 1, 2017

Tim Sprinkle

There was always something a little off about Jill Watson.

In early 2016 Watson had been assigned as the teaching assistant for Dr. Ashok Goel’s graduate course in artificial intelligence (AI). Offered online through Georgia Institute of Technology, the course taught hundreds of students from all over the world. The workload, Goel remembers, quickly became overwhelming for him. There were far more students than in a typical class. They lived across a dozen different time zones and they all had questions for their professor at all hours of the day and night.

“It was a large class and the questions were constant,” Goel says. “It takes a lot of time to pursue all of those messages and answer the questions. So we started off looking for a way to make the work easier on ourselves.”

So he called Jill, an artificial intelligence-backed “robot TA” that was developed at Georgia Tech and based on IBM’s Watson system.

The students, at least in the beginning, didn’t even notice they were dealing with a robot TA.

Jill was an incredibly effective TA. She answered student questions within minutes, no matter when they contacted her. She offered in-depth answers to a wide range of complex queries. She was generally more accessible, more personal, and more upbeat than any human could ever be. The class rolled through half a semester beforeGoel gave up Jill’s real identity. Since then, he’s used the AI system in a few other classes and has noticed that, beyond helping with his workload, Jill also improves the overall student experience, making for better, more effective, and more engaged learning.

“What we realized is that, when a student asks a question, a human TA may not get to that question for six hours, 12 hours, 24 hours,” Goel says. “But Jill answers your question within a few minutes. That does tend to be really important because, if you're a student say, somewhere in Japan , and you ask a question and you don't even get a response for 24 hours, by the time the response comes you have moved on. You're doing something else. But when Jill responds within five minutes then you're still on the topic and can stay focused.”

Getting Personal

AI is another step on the path to personalized learning, Goel says. Teachers play many roles in the classroom. They are coaches and mentors. They provide assessments and offer cognitive challenges. The long-term goal for systems like Jill, is to combine all of those functions into one solution that can do it all. Eventually, the hope is that students will be able to ask an AI system a question and, based on data about a student’s learning trajectory or demographic or cognitive profile, the answers and guidance that come back will be tailored specifically to them.

“My understanding is that 400 years back, 500 years back, much of education was personalized, except it was accessible only to the elite.” Goel says, “Then mass education started and all of us started getting learning, but it became impersonal. And now I think we are swinging back toward personalized learning, where we will have systems that will build very excellent models of students, and then use those student models to personalize all the tutoring and teaching.”

To get there, technology needs to become more human . These systems need to understand human beings. They need to understand what we want and how we think, and then use that information to interact with us. In many cases, AI needs to emerge from a technological vacuum and function effectively in the real, human world.

“Being able to have AI that understands the learner is incredibly important because it gets a deeper focus on that learner and understands what they're doing,” says futurist Brian David Johnson, a professor of practice at Arizona State University’s School for the Future of Innovation in Society. “But, for me, we need to certainly get the core skills and we need to teach, but we also have to remember that we're going to have this AI and this technology doing more and more of our work for us.”

It’s the things that machines can’t do in the classroom—empathize, read emotions, adjust guidance—Johnson says that will really matter as AI systems become more common.

“We can’t lose sight of the fact that education is not just about skills,” he says. “It's also about developing human beings and developing whole learners.”

Growth and Scale

The potential applications for robot teachers—and AI-based learning systems in general— are broad and ambitious. One limitation for educators today is reach. A teacher standing in front of a classroom can teach up to about 50 students at a time. A college lecturer can reach maybe 200 or so. Digitally, though, the scope is almost limitless. Digital assistance allows educators to scale their services and reach communities and individuals who didn’t have access to different types of education.

“If you look at the global picture, we're short somewhere around 18 million teachers in the world today,” says Thomas Frey, author and futurist with the DaVinci Institute. “Teachers don’t want to go to Africa, they don’t want to go to Siberia, they don’t want to go to Afghanistan. There are lots of places in the world teachers don’t want to go to, and that’s what’s created this shortage of teachers.”

As a result, he says, nearly 25 percent of children worldwide are growing up today without any schooling whatsoever. This hinders their potential and consigns them to unskilled labor and subsistence jobs. Digital forms of education can help reverse that and actually raise the IQ of the entire planet.

“We have the Googles and the Facebooks of the world trying to bring Wi-Fi to the other three billion people on the planet, so educating those people just changes the equation almost instantly,” Frey says “Even small things, like teaching people how to take care of themselves or how to use a water filtration system, minor improvements in understanding of how the world works would be a huge change.”

Tim Sprinkle is an independent writer.

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The next fifty years of education will feature a greater role for technology. Chris Whiteoak / The National

Future of schools: robot teachers, AI in the classrooms but with a ‘human heart’

Uae’s zayed university gathered hundreds of global experts in k-12 education to map out how the next fifty years might look.

November 29, 2020

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></center></p><h2>The Top 20 Advantages of Having A Robot Teacher: A Realistic View</h2><ul><li>October 11, 2023</li></ul><h2>Table of Contents</h2><p>Introduction.</p><p>Once upon a time, classrooms were filled with only students and teachers. But in today’s world, a new type of teacher has emerged: robot teachers! These aren’t just ordinary robots; they’re here to help us learn in exciting new ways. For the students of Saudi Arabia, it’s time to explore the advantages of having a robot teacher. Join us as we journey through this magical blend of technology and education.</p><p>Imagine sitting in a classroom where your teacher knows exactly how you learn best. That’s what robot teachers do through adaptive learning. They understand each student’s unique learning style and use that information to create customized lessons. But that’s not all! Imagine getting instant feedback on your work, like having a helpful friend by your side.</p><h2>Why We Need to Talk about This?</h2><p>In a world where technology is changing everything, classrooms are also getting a high-tech makeover. But what about robot teachers? Aren’t they just for science fiction movies? Not anymore! They’re real, and they’re transforming education. The big question is, what are the advantages of having a robot teacher? Let’s unravel how these tech-savvy educators are shaping the future of learning.</p><p>Remember those traditional chalkboards? They’re being replaced with impressive screens that show all sorts of information. And guess what? Robot teachers are joining the educational scene! These special robots bring a new dimension to classrooms. They blend technology with the art of teaching. But how do they truly enhance learning? Let’s take a closer look!</p><h2>Top Advantages of Having a Robot Teacher</h2><p>1. making learning personal, how robot teachers adapt to you.</p><p>Imagine having a teacher who understands how you learn best. That’s exactly what robot teachers do! They use something called adaptive learning to figure out what works best for each student. It’s like having your own personalized learning recipe. If you learn quickly, they’ll challenge you more. If you need more time, they’ll slow down and help you catch up. It’s all about making sure each student learns at their own pace.</p><h2>Getting Feedback, Faster</h2><p>In a regular class, you might have to wait until the next day to know if you got something right. But with robot teachers, you get feedback right away. Imagine solving a tough math problem, and your robot teacher instantly tells you if you’re on the right track. This quick feedback helps you learn better and fix any mistakes faster.</p><h2>2. Lessons that Never Sleep</h2><p>Why consistency matters.</p><p>Have you ever noticed that teachers need breaks too? But robot teachers don’t get tired. They can teach non-stop, which means every lesson is just as good as the last one. This consistency is important because it ensures that every student receives the same quality of education, no matter when they’re learning. </p><h2>Always There to Teach</h2><p>Imagine needing help with a lesson at midnight. That’s when robot teachers truly shine! They’re available 24/7, ready to help you understand anything you’re struggling with. Whether it’s early in the morning or late at night, robot teachers are always there to guide you.</p><h2>3. Education Beyond Borders</h2><p>No school no problem.</p><p>In some rural places , schools might be far away or even unavailable. But robot teachers don’t mind traveling! They can reach places where education might be hard to find. This means more kids can learn, no matter where they live. It’s like having a classroom that comes to you!</p><h2>Talking the Same Language</h2><p>Learning in a different language can be tough. But robot teachers can speak many languages, so they’re like language superheroes! They break down language barriers, making sure everyone understands the lesson. Now, learning a new language or understanding a tricky subject becomes much easier.</p><h2>4. Tech-Powered Teaching</h2><p>Fresh lessons every day.</p><p>Robot teachers don’t just stick to old textbooks. They have access to a whole world of knowledge online. This means they can give you the latest information on any subject. Learning with robot teachers is like going on a journey of discovery, where every lesson feels new and exciting.</p><h2>Learning in Color and Sound</h2><p>Traditional learning can sometimes be a bit boring, especially if it’s all about reading and writing. But robot teachers make learning colorful and fun! They use videos, pictures, and interactive activities to help you understand better. This multi-sensory learning is like having an adventure while you’re learning.</p><h2>5. Smart Data, Smart Moves</h2><p>Teachers who understand you.</p><p>Robot teachers are not just educators; they’re also smart data collectors. They keep track of how you’re doing in class and what you need help with. This way, they can give you exactly what you need to learn better. It’s like having a teacher who really gets you.</p><h2>Saving Money, Making Sense</h2><p>Some people might think that robot teachers are expensive. But in the long run, they actually save money. Robot teachers work tirelessly without needing breaks, which means schools can spend less on teacher salaries. This cost-effective education ensures that learning remains affordable for everyone.</p><p><center><a href=

Special Attention for Special Students

Students with special needs deserve extra care and attention. Robot teachers are amazing at giving them just that. With their patient and understanding nature, they provide the focused attention special students require. Learning becomes a safe and supportive journey, boosting confidence and knowledge.

No More Feeling Scared

Learning can sometimes be scary, especially if you’re worried about making mistakes. But with robot teachers, there’s no need to fear. They create a non-judgmental environment where mistakes are seen as opportunities to learn and grow. This supportive atmosphere encourages students to explore without hesitation.

6. Learning Safe and Sound

No germs, just learning.

Staying healthy is important, especially in classrooms where germs can spread easily. Robot teachers offer a solution: they provide contact-free learning. This means you can learn without touching anything, keeping yourself and others safe from illness.

Keeping Us Safe

Safety matters in school. Robot teachers help keep classrooms safe by eliminating potential hazards. With contact-free teaching, there’s no need to worry about accidents. This safe environment lets you focus on learning without any worries.

7. Saving the Planet, One Lesson at a Time

Less paper, more green.

We all know how important it is to take care of our planet. Robot teachers contribute by reducing the need for paper and printed materials. By embracing digital resources, they play their part in creating an eco-friendlier learning environment. This shift towards sustainability helps protect our Earth for future generations.

8. Collaboration and Teamwork: Fostering Social Skills

One of the standout advantages of robot teachers is their ability to facilitate collaborative activities among students, promoting teamwork and the development of interpersonal skills. By coordinating group tasks and encouraging interaction, these robots create a dynamic learning environment that mirrors the real world, where collaboration is key to success.

9. Easy Scalability: Meeting Growing Educational Needs

As educational institutions grapple with rising student populations, the scalability of robot teachers becomes invaluable. These mechanical educators can be easily replicated and deployed in multiple classrooms, ensuring that quality education remains accessible even in the face of growing demand.

10. Preparation for the Future: Adapting to a Tech-Driven World

Interacting with robot teachers prepares students for a future where human-robot interactions are increasingly common. Equipped with the skills to adapt and thrive in a technology-driven world, students gain a competitive edge by learning in an environment that mirrors the workplace of tomorrow.

11. Consistent and Standardized Teaching: Ensuring Quality Education

Robot teachers offer consistent and standardized teaching methods, ensuring that all students receive the same quality of education. This levels the playing field, providing equal opportunities for all learners to excel.

12. Reduced Teacher Workload: Empowering Educators

Robot teachers can assist human teachers by handling administrative tasks, grading assignments, and managing classroom logistics. This reduction in the teacher’s workload allows them to focus on what matters most: teaching and guiding their students.

13. Instant Feedback: Real-Time Improvement

Imagine receiving feedback on your work immediately. Robot teachers provide just that. They help students identify mistakes and areas for improvement in real-time, fostering a culture of continuous learning.

14. Reduced Classroom Disruptions: A Conducive Learning Environment

Maintaining discipline and order in the classroom can be challenging. Robot teachers excel in this regard, minimizing disruptions and creating a conducive learning environment where students can thrive.

15. Consistent Assessment Standards: Fairness in Grading

Objective assessment is vital. Robot teachers ensure consistent and fair grading standards, eliminating potential biases and promoting fairness in evaluating students’ work.

16. Increased Efficiency: Maximizing Instructional Time

Robots deliver lessons efficiently, covering a wide range of topics and maximizing instructional time. This efficiency is crucial for comprehensive learning.

17. Specialized Expertise: Expanding Educational Horizons

Robot teachers offer specialized knowledge in specific subjects or areas where human teachers may have limited expertise. This broadens the scope of available educational resources, ensuring students receive a well-rounded education.

18. Reduced Teacher-Student Ratio: Individualized Attention

With robot teachers assisting human teachers, the teacher-student ratio improves, allowing for more individualized attention and support for students. Personalized learning becomes a reality.

19. Overcoming Teacher Shortages: Ensuring Access to Education

In regions facing teacher shortages, robot teachers step in to fill the gap, ensuring that students still have access to quality education. They become the beacon of hope in underserved areas.

20. Consistent Classroom Management: Fair and Orderly Environment

Robot teachers enforce consistent rules and regulations, ensuring a fair and orderly classroom environment for all students. This consistency sets clear expectations and fosters a positive learning atmosphere.

Embracing Robot Teachers for a Brighter Future in Education

In our exploration of the advantages of having robot teachers, we’ve uncovered a transformative force in education. These tech-savvy educators offer personalized learning, instant feedback, and 24/7 availability, revolutionizing the way we learn.

Robot teachers create a safer, eco-friendly learning environment, while also empowering human teachers to focus on nurturing students. They bridge the gap in underserved areas, promote collaboration, and ensure fair and consistent education for all.

As we embrace the future of education, it’s clear that robot teachers are here to stay. They guide us towards a more innovative, efficient, and accessible learning experience, paving the way for a brighter future in education. Let’s embark on this exciting journey together!

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Robot Teachers vs Human Teachers:

Simona Johnes, editor-in-chief of Science and Literacy , an educational blog for teachers and parents, did some research into a topic that is of growing concern to my fellow teachers: Robots in the classrom. Here’s an interesting article comparing the pros and cons of robots vs. humans:

I recently came across an article published by Ohio State University that mentioned how several industries are using robots to get their jobs done, and the use of robotics is only expected to grow. This led me to thinking about the industry that I am currently employed in, education, and how this may affect my fellow teachers around the world. I began researching the topic and found a few articles about robots and artificial intelligence replacing teachers soon.

It was no surprise to see that educators are furious at this idea , and while I agree that human connection is important, I do think that there are several pros to having help from a robot in this tough industry from time to time. For example , robots can create a learning experience based on the personality of every single student, and this does not take much time or effort. I will explain more about what robots can help with throughout the article as well as explain why human teachers are still a necessity

After reading this article, you will officially know:

6 advantages of a human teacher
5 pros of a robot teacher
Who is better Human of Robot teachers?

6 Main Advantages of a Human Teacher

Here are a few of the pros of a human teacher:

Human teachers have the ability to read social cues
Human teachers can inspire children
Human teachers have strong sensory feelings and emotions
Human teachers can be creative
Human teachers are social
Human teachers do not have technical disruptions

Even though the use of technology continues to be on the rise, young people still need human teachers to help them remain in the reality in front of them. Young people are being pulled into a virtual world , but human teachers are able to show them how to socialize, be creative, have feelings and emotions, and more.

It is important to also mention that robot teachers are less likely to be able to maintain discipline and order in schools. Children may not take robots seriously and create total chaos if no human is in sight. Human teachers understand how to establish authority and remain strict with their students to ensure that their classroom remains in order. If you do not do so, your students will walk over you. To get some help with learning how to be strict with your students, check out my other article by clicking here .

5 Pros of a Robot Teacher

So many teachers are experiencing burnout, and they are leaving their positions to find better paying jobs that are not mentally exhausting. This has left school systems scrambling to fill those positions to educate students around the globe. Therefore, it is not shocking to learn that people are searching for ways to alleviate the pressure from teachers, which is where robotics has come into the conversation.

In China, a small robot named KeeKo is being used to help kindergarten teachers when needed. This little robot tells stories to the children, gives the students logic problems to answer, and shows certain facial expressions if the student gets the problem correct or wrong. KeeKo gives the human teacher a break for a few minutes to take a breather, focus on grading papers, or determine what the students will do next.

I recommend watching the video below to see KeeKo in action in a classroom. It looks like KeeKo is able to assist the teacher in the classroom, and the students seem to be participating and enjoying the activity (access allowed only through YouTube).

https://www.youtube.com/watch?v=ULB7I2LpiuM

After watching that video and seeing the teacher benefit from the robot’s assistance, it is important for you to know that some teachers are not totally against the idea of robots giving them a hand in their day-to-day tasks, such as grading, tutoring, taking attendance, making copies of worksheets, and translating languages . If a robot took over some of these tasks, the human teacher could focus on other important components of the day, which could benefit both the students and the teacher. Below, I will tell you about the pros of a robot teacher.

The following are the pros of a robot teacher :

Robot teachers can be faster and can help speed up the teaching and lesson plan
Little to no errors will be made as everything is programmed into the robot teacher
Robot teachers can integrate students with different learning styles, disabilities, or who speak different languages into the classroom better
Robots can grade assignments, take attendance, and make important copies very quickly
Robot teachers do not require a salary to teach or assist human teachers

If you would like a glimpse of what a student’s day may look like if robots replaced teachers, watch BBC’s YouTube video below. It is an interesting video that you may find enjoyable to watch.

https://www.youtube.com/watch?v=rjCkiNRM-FI

Next, let’s go over the comparison of a human teacher and robot teacher.

Comparison of a Human Teacher and a Robot Teacher

When you look at the comparison of using robot teachers vs human teachers, there are things that the human teacher can do better than a robot teacher, and there are things that a robot teacher can do better than a human teacher. A robot teacher can do certain tasks fast and efficient that could take a human teacher a longer time to complete and could have errors. However, a human teacher brings real connection, socialization, and creativity to the classroom.

Overall, the education system can benefit from having robot teachers assisting human teachers because they can reduce the time and research a human teacher may have to spend doing simple tasks when they could be using that time to teach children, and they do not have to hand out hefty salaries to intrigue people to assist their teachers. However, robots may need to develop a lot more to be able to fully assist human teachers in ways that they really need them, which could take many years or decades.

For the students who need to stay after school or just want other ways to ignite their passions, you should check out my article on afterschool clubs to excite and interest students. In this article , I write about photography club, art club, singing club, dance club, gardening club, cooking club, and many other clubs which involve having a human teacher help students reach their full potential when it comes to their interests. If it is something you are interested in starting at your school, head over to that article right away!

I hope this article helped you understand the difference of robot teachers vs human teachers. Instead of human teachers seeing robots as a total threat, we should start seeing them as a solution to our burnout and exhaustion. The robots’ advancement in technology allows them to assist human educators, which will lead to children receiving the best education that they deserve with better resources and more refreshed teachers. Robots cannot replace human teachers as no machine can substitute human communication, connection, emotions, creativity, inspiration, and so much more. So, instead of worrying about robots taking over our jobs, we should accept that technology could help human teachers give your children the best learning experience possible.

Simona’s Bio

Simona Johnes is the visionary being the creation of “Science and Literacy” project. Johnes spent much of her career in the classroom working with students. And, after many years in the classroom, Johnes became a principal.

While Johnes enjoyed her new role, she never lost her passion for working with students and helping them succeed.

After a lot of thought, she decided to pursue creating a next generation curriculum to prepare high school students for future success. She left her position as a principal and developed her teaching portal.

5 thoughts on “ Robot Teachers vs Human Teachers: ”

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That was a fun video. The Japanese are really into Robotics. I’ve worked in robotics as well as artificial intelligence. I’ve done research robotics and practical robotics to create the software for spray painting, spot welding, arc welding, palletizing, and mail sorting robots. I agree with you that robots can really save time on tedious tasks, improve quality for such tasks, and it can also be fun. Teachers don’t need to worry about robots taking their jobs. Truly human like intelligence and human like interaction is far away in the future. It’s been 30 years in the future ever since AI research started in the 1950’s. Like with fusion. 1950’s: We’ll have it 30 years. The 2020’s: We’ll have it in 30 years.

Thanks for the comment, Thomas. This is truly a brave new world. An accurate allusion, but no offense against those areas that have banned that book.

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Will robots replace teachers in the future?

Dive brief:.

In a world where news anchors are being replaced by robots, teachers can feel that their jobs are safe because students will need teachers to foster needed higher-order thinking skills, which only human teachers can provide, Andre Perry, a Brookings Institution fellow, asserts in a column for the Hechinger Report.
However, public education is adapting to a changing world and technology is already affecting education in the form of MOOCs and computer programs that allow education to be personalized for students in ways not possible with a single teacher in a crowded classroom. But failed experiments, such as the Electronic Classroom of Tomorrow in Ohio , illustrate the dangers of relying too heavily on electronic education.
For teachers to stay relevant in a changing society, they must be able to prepare students for a world that does employ robots by giving them skills such as critical thinking , communication, collaboration, problem-solving and entrepreneurialism. In a world where information is available at our fingertips, Perry said, “Learning in practice is no longer about extracting knowledge; it is about constructing it — and that’s what separates humans from machines.”

Dive Insight:

As the age of AI approaches, the question of whether robots can replace teachers looms larger. Anthony Seldon, vice chancellor of the University of Buckingham , predicts that robots will replace teachers by 2027 , less than a decade away. Some say that robots can never replace teachers because teachers inspire us. But, in another article, Seldon, says “inspirational robots” are possible and can be adapted to each student’s individual learning style.

The idea of robot teachers may sound appealing on some levels because teachers are expensive and in increasingly short supply. Robots do not require pay, health care or pensions, are fairly reliable and do not have preconceived notions about race or gender that can impact the delivery of knowledge and expectations.

However, education is not just about the acquisition of knowledge, it is about relationships and the shaping young minds. A true teacher does not just impart facts; he or she creates a thirst for knowledge and teaches students how to quench that thirst. Teachers also inspire students to think for themselves and to innovate new solutions, something that AI cannot do.

The experiment with the Electronic Classroom of Tomorrow illustrates some of these challenges. The school failed because many of the “students” weren’t actually participating in the process of education. Students are human beings who need to be motivated and guided. They have questions that need to be answered by humans. They also need warmth, encouragement and personal attention. They need to learn social skills only humans can teach.

Robots may be able to play a role in the future of education as aides in the classroom , despite the reluctance of many teachers to use them . They may be able to help personalized curriculum and deal with some of the more mundane tasks of monitoring progress or drilling students on facts. Teachers may need to adapt to dealing with AI in the future, but they will likely never be replaced by them.

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The case of classroom robots: teachers’ deliberations on the ethical tensions

Published: 15 June 2016
Volume 32 , pages 613–631, ( 2017 )

Cite this article

Sofia Serholt 1 ,
Wolmet Barendregt 1 , 2 ,
Asimina Vasalou 3 ,
Patrícia Alves-Oliveira 4 , 6 ,
Aidan Jones 5 ,
Sofia Petisca 4 &
Ana Paiva 4

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Robots are increasingly being studied for use in education. It is expected that robots will have the potential to facilitate children’s learning and function autonomously within real classrooms in the near future. Previous research has raised the importance of designing acceptable robots for different practices. In parallel, scholars have raised ethical concerns surrounding children interacting with robots. Drawing on a Responsible Research and Innovation perspective, our goal is to move away from research concerned with designing features that will render robots more socially acceptable by end users toward a reflective dialogue whose goal is to consider the key ethical issues and long-term consequences of implementing classroom robots for teachers and children in primary education. This paper presents the results from several focus groups conducted with teachers in three European countries. Through a thematic analysis, we provide a theoretical account of teachers’ perspectives on classroom robots pertaining to privacy, robot role, effects on children and responsibility. Implications for the field of educational robotics are discussed.

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Robot Tutors: Welcome or Ethically Questionable?

Should we welcome robot teachers?

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www.etica-project.eu .

These discussions were held in English as not all participants were Swedish speakers.

Note that the pre-service teacher focus groups in Sweden were held in English as there were some non-Swedish speakers present. As they were not fluent English speakers, this sometimes resulted in errors. To preserve a verbatim account, however, grammatical and linguistic errors produced in quotes were not corrected.

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Acknowledgments

We would first of all like to thank all the teachers and students who took part in the studies. We would also like to extend our gratitude to teacher education students Rebecka Olofsson and Trixie Assarsson for their excellent video editing. We thank Tiago Ribeiro, Eugenio Di Tullio, Etienne Roesch and Daniel Gooch for facilitating some of the focus groups. We would also like to thank master student Thomas Rider for his initial transcription services and ideas. We also thank the MUL group at the University of Gothenburg for their valuable feedback on an earlier version of this paper. This work was partially supported by the European Commission (EC) and was funded by the EU FP7 ICT-317,923 project EMOTE ( www.emote-project.eu ). P. Alves-Oliveira acknowledges a FCT Grant Ref. SFRH/BD/110223/2015. The authors are solely responsible for the content of this publication. It does not represent the opinion of the EC, and the EC is not responsible for any use that might be made of data appearing therein.

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Sofia Serholt & Wolmet Barendregt

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Asimina Vasalou

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Patrícia Alves-Oliveira, Sofia Petisca & Ana Paiva

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Serholt, S., Barendregt, W., Vasalou, A. et al. The case of classroom robots: teachers’ deliberations on the ethical tensions. AI & Soc 32 , 613–631 (2017). https://doi.org/10.1007/s00146-016-0667-2

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Received : 24 March 2016

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Published : 15 June 2016

Issue Date : November 2017

DOI : https://doi.org/10.1007/s00146-016-0667-2

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A teacher caught students using ChatGPT on their first assignment to introduce themselves. Her post about it started a debate.

A teacher's students ChatGPT for a simple introductory assignment in an ethics and technology class.
Professor Megan Fritts shared her concerns on X, sparking debate on AI's role in education.
Educators are divided on AI's impact, with some feeling it undermines critical thinking skills.

Professor Megan Fritts' first assignment to her students was what she considered an easy A: "Briefly introduce yourself and say what you're hoping to get out of this class."

Yet many of the students enrolled in her Ethics and Technology course decided to introduce themselves with ChatGPT .

"They all owned up to it, to their credit," Fritts told Business Insider. "But it was just really surprising to me that — what was supposed to be a kind of freebie in terms of assignments — even that they felt compelled to generate with an LLM."

When Fritts, an assistant professor of philosophy at the University of Arkansas at Little Rock, took her concern to X, formerly Twitter, in a tweet that has now garnered 3.5 million views, some replies argued that students would obviously combat " busywork " assignments with similarly low-effort AI-generated answers.

Second week of the semester and I've already had students use (and own up to using) ChatGPT to write their first assignment: "briefly introduce yourself and say what you're hoping to get out of this class". They are also using it to word the *questions they ask in class*. — Megan Fritts (@freganmitts) August 28, 2024

However, Fritts said that the assignment was not only to help students get acquainted with using the online Blackboard discussion board feature, but she was also "genuinely curious" about the introductory question.

"A lot of students who take philosophy classes, especially if they're not majors, don't really know what philosophy is," she said. "So I like to get an idea of what their expectations are so I can know how to respond to them."

The AI-written responses, however, did not reflect what the students, as individuals, were expecting from the course but rather a regurgitated description of what a technology ethics class is, which clued Fritts in that they were generated by ChatGPT or a similar chatbot.

"When you're a professor, and you've read dozens and dozens of AI essays, you can just tell," she said.

The calculator argument — why ChatGPT is not just another problem-solving tool

While a common defense permeating Fritts' replies likened ChatGPT for writing to a calculator for math problems, she said that viewing LLMs as just another problem-solving tool is a "mistaken" comparison, especially in the context of humanities.

Lasting impacts on students

Beyond cheating on papers, Fritts said that students have, in general, become compromised in their thinking ability — and they've noticed.

"They're like, 'When I was young, I used to love to read, and now I can't. I can't even get through the chapter of a book,'" she said. "'My attention span is so bad, and I know it's from looking at my phone, always having YouTube or TikTok on.' And they're sad about it."

Fritts said that technology addiction has affected students' general agency when interacting with information. She cited a 2015 paper by Professor Charles Harvey, chair of the Department of Philosophy and Religion at the University of Central Arkansas, which examines the effects that interactions with technology could have had on human agency and concentration.

Harvey wrote that two different eye-tracking experiments indicated that the vast majority of people skim online text quickly, "skipping down the page" rather than reading line by line. Deep reading of paper texts is being snipped into "even smaller, disconnected" thoughts.

"The new generations will not be experiencing this technology for the first time. They'll have grown up with it," Fritts said. "I think we can expect a lot of changes in the really foundational aspects of human agency, and I'm not convinced those changes are going to be good."

Teachers are getting tired

Fritts acknowledges that educators have some obligation to teach students how to use AI in a productive and edifying way. However, she said that placing the burden of fixing the cheating trend on scholars teaching AI literacy to students is "naive to the point of unbelievability."

"Let's not deceive ourselves that students are using AI because they're just so siked about the new tech, and they're not sure of what the right way to use it in the classroom," Fritts said.

"And I'm not trying to slam them," she added. "All of us are inclined to take measures to make things easier for us."

But Fritts also feels just as "pessimistic" about the alternative solution — educators and institutions forming a "united front" in keeping AI out of the classroom.

"Which isn't going to happen because so many educators are now fueled by sentiments from university administration," Fritts said. "They're being encouraged to incorporate this into the curriculum."

At least 22 state departments of education have released official guidelines for AI use in schools, The Information recently reported . A 2024 survey by EdWeek Research Center found that 56% of over 900 educators anticipated AI use to rise. And some are excited for it.

Curby Alexander, an associate education professor at Texas Christian University, previously told BI that he uses AI to help brainstorm ideas and develop case studies "without taking up a lot of class time."

ASU's Anna Cunningham, a Dean's Fellow, and Joel Nishimura, an associate professor in the Mathematical and Natural Sciences department, wrote an op-ed encouraging having students teach ChatGPT agents with programmed misunderstandings.

"With this, we are on the cusp of being able to give all students as many opportunities as they want to learn by teaching," they wrote.

OpenAI even partnered with Arizona State University to offer students and faculty full access to ChatGPT Enterprise for tutoring, coursework, research, and more.

However, many educators remain skeptical. Some professors have even reverted back to pen and paper to combat ChatGPT usage, but Fritts said many are tired of trying to fight the seemingly inevitable. And students are left in the middle of education and AI's love-hate relationship.

"I think it, understandably, creates a lot of confusion and makes them feel like the professors who are saying 'Absolutely not' are maybe philistines or behind the times or unnecessarily strict," Fritts said.

Fritts is not the only professor voicing concerns about AI use among students. In a Reddit thread titled " ChatGPT: It's getting worse ," several users who identified as professors lamented increased AI usage in classrooms, especially in online courses. One commented, "This is one reason I'm genuinely considering leaving academia."

A professor in another post that received over 600 upvotes said that ChatGPT was "ruining" their love of teaching. "The students are no longer interpreting a text, they're just giving me this automated verbiage," they wrote. "Grading it as if they wrote it makes me feel complicit. I'm honestly despairing."

Watch: What is ChatGPT, and should we be afraid of AI chatbots?

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9. Easy Scalability: Meeting Growing Educational Needs

10. Preparation for the Future: Adapting to a Tech-Driven World

11. Consistent and Standardized Teaching: Ensuring Quality Education

12. Reduced Teacher Workload: Empowering Educators

13. Instant Feedback: Real-Time Improvement

14. Reduced Classroom Disruptions: A Conducive Learning Environment

15. Consistent Assessment Standards: Fairness in Grading

16. Increased Efficiency: Maximizing Instructional Time

17. Specialized Expertise: Expanding Educational Horizons