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Robot Helps Children With Learning Disabilities Stay Focused



A team of engineering researchers at the University of Waterloo has successfully developed and used a robot to help keep children with learning disabilities focused on their work.

This was part of a larger study that also found both the children and their instructors valued the positive classroom contributions that the robot made.

The research paper titled “User Evaluation of Social Robots as a Tool in One-to-one Instructional Settings for Students with Learning Disabilities” was presented at the International Conference on Social Robotics in Florence, Italy.

Potential of Robots in Public Education System

Dr. Kerstin Dautenhahn is a professor of electrical and computer engineering.

“There is definitely a great potential for using robots in the public education system,” said Dautenhahn. “Overall, the findings imply that the robot has a positive effect on students.”

Dautenhahn has dedicated several years to researching robotics in the disability context and strives to incorporate principles of equity, inclusion, and diversity in her research projects.

Individualized learning support, such as one-on-one instruction and the use of smartphones and tablets, may prove advantageous to students with learning disabilities.

Recently, educators have been exploring the use of social robots to aid in students' learning, primarily focusing on children with Autism Spectrum Disorder. Unfortunately, little attention has been paid to the use of socially assistive robots for students with learning disabilities.

Conducting Experiments With QT Humanoid Robot

In collaboration with two other Waterloo engineering researchers and three experts from the Learning Disabilities Society in Vancouver, Dautenhahn set out to address this gap. They conducted a series of experiments utilizing a small humanoid robot called QT.

As the Canada 150 Research Chair in Intelligent Robotics, Dautenhahn believes that QT's head and hand gestures, speech, and facial expressions make it particularly well-suited for use with children with learning disabilities.

Expanding on earlier successful research, the team divided 16 students with learning disabilities into two groups. The first group received one-on-one instruction, while the second group received one-on-one instruction and interacted with the QT robot. The instructor directed the robot via tablet, and it then independently performed various activities using its speech and gestures.

During the sessions, the instructor maintained control, with the robot taking over periodically, prompted by the instructor, to lead the student. The robot initiated the session, set objectives, and provided self-regulating strategies as required. If the learning process was interrupted, the robot implemented strategies such as games, riddles, jokes, breathing exercises, and physical movements to redirect the student back to the task.

According to Dautenhahn, students who worked with the robot were generally more engaged with their tasks and could complete their tasks at a higher rate compared to students who weren’t assisted by a robot.

Alex McFarland is a tech writer who covers the latest developments in artificial intelligence. He has worked with AI startups and publications across the globe.