Carnegie Mellon's RoboTutor advances to Global Learning XPRIZE semifinals

  
Carnegie Mellon's RoboTutor advances to Global Learning XPRIZE semifinals
RoboTutor, educational technology developed at Carnegie Mellon University that teaches children basic math and reading skills, has been named a semifinalist in the $15 million Global Learning XPRIZE competition. "RoboTutor is a brilliant piece of educational technology that has already proven to effectively teach English and Swahili-speaking children basic skills. It also perfectly exemplifies our evidence-based approach to carefully integrating technology and using data to continuously refine and improve instruction, leading to better student learning while supporting new discoveries in the learning sciences," said Richard Scheines, dean of the Dietrich College of Humanities and Social Sciences and faculty lead for CMU's Simon Initiative. Credit: Carnegie Mellon University

RoboTutor, educational technology developed at Carnegie Mellon University that teaches children basic math and reading skills, has been named a semifinalist in the $15 million Global Learning XPRIZE competition.

An estimated 250 million children around the world cannot read, write or do fundamental arithmetic, and many of these children are in developing countries without regular access to schools or teachers. XPRIZE is attempting to address the acute shortage of teachers in developing countries by funding an international competition to create open-source Android tablet apps that enable children ages 7-10 to learn basic reading, writing and math skills without requiring adult assistance. Apps were created in both English and Swahili.

Nearly 200 teams from 40 different countries entered the competition. Following an evaluation and pilot test, RoboTutor, led by CMU's Jack Mostow, is one of 11 remaining teams competing for five $1 million finalist prizes.

"RoboTutor is a brilliant piece of educational technology that has already proven to effectively teach English and Swahili-speaking children basic skills. It also perfectly exemplifies our evidence-based approach to carefully integrating technology and using data to continuously refine and improve instruction, leading to better student learning while supporting new discoveries in the learning sciences," said Richard Scheines, dean of the Dietrich College of Humanities and Social Sciences and faculty lead for CMU's Simon Initiative.

RoboTutor's design is based on scientific learning principles in order to engage students so that they learn the material and can then use it in other contexts. It is powered by advanced technologies, including speech and handwriting recognition, facial analysis and machine learning. It collects data from its interactions with children both to enable cognitive tutors to adapt to individual students and to enable innovative data mining tools to continuously evaluate and refine its design and functionality.

Mostow, emeritus research professor of robotics, machine learning, language technologies and human-computer interaction, has spent the past three decades applying advanced language technologies to literacy.

"I have been able to help a few thousand children over my career, but the Global Learning XPRIZE is the opportunity of a lifetime for me to help millions or even billions of children get a basic education," Mostow said.

RoboTutor leverages many assets, including its precursor, Project LISTEN, which used speech technology to enable natural spoken dialogue with an automated Reading Tutor that listened to children read aloud and helped them learn to read.

RoboTutor's hundreds of activities address four content areas—reading and writing, numbers and math, comprehension and shapes.

Another distinguishing feature is how RoboTutor's data-driven design process integrates with local cultures.

"While we focus on improving RoboTutor with large-scale data, we never forget that it really represents kids who are living and learning in a context that we must understand, in order to properly interpret that data," said Amy Ogan, assistant professor of human-computer interaction, who field-tested RoboTutor in several settings in Tanzania.

In addition to Mostow and Ogan, the RoboTutor team consists of over one hundred CMU students and faculty as well as other experts and students from around the globe.

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