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Advances in Robotics & Mechanical Engineering
Article . 2019 . Peer-reviewed
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Article . 2019
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Robotics in Education and Training

Authors: Mitra, Manu;

Robotics in Education and Training

Abstract

{"references": ["NY Post (2018) Finland schools are testing out robot teachers.", "US Army Research Laboratory (2018) Teaching robots to be more reliable teammates for soldiers. ScienceDaily.", "Tony Belpaeme, James Kennedy, Aditi Ramachandran, Brian Scassellati, Fumihide Tanaka (2018) Social robots for education: A review Science Robotics 2018.", "University of Plymouth (2018) Robots will never replace teachers but can boost children's education. ScienceDaily.", "Cornell University (2014) Robot can be programmed by casually talking to it. Science Daily.", "Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne (2015) Kids and robots learn to write together. ScienceDaily.", "University of Manchester (2015) Training teachers for deaf children gets a robotic helping hand. ScienceDaily."]}

In Finland, a new teacher called Elias at primary school who has endless patience for repetition and never creates a pupil feel humiliated for asking same question again and again and can even do “Gangnam Style” dance. Elias is also robot. The Artificial Intelligence language machine includes a humanoid robot at primary schools in southern city of Tampere. This robot can able to understand and speak 23 different languages and it also allows to understand student’s requirements and helps to inspire learning. It recognizes student’s skill levels and adjusts its questions accordingly and gives feedback to teachers about pupil’s possible problems. Below are some of few from many applications of robots that can be used in education, teaching and training.

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Keywords

Training, Education

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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