Award Abstract # 1321056
EXP: Transforming World Language Education using Social Robotics

NSF Org: IIS
Division of Information & Intelligent Systems
Recipient: ALELO TLT LIMITED LIABILITY COMPANY
Initial Amendment Date: August 20, 2013
Latest Amendment Date: September 9, 2013
Award Number: 1321056
Award Instrument: Standard Grant
Program Manager: Christopher Hoadley
IIS
 Division of Information & Intelligent Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: September 1, 2013
End Date: August 31, 2015 (Estimated)
Total Intended Award Amount: $549,957.00
Total Awarded Amount to Date: $549,957.00
Funds Obligated to Date: FY 2013 = $549,957.00
History of Investigator:
  • William Johnson (Principal Investigator)
    ljohnson@alelo.com
  • Kino Coursey (Co-Principal Investigator)
Recipient Sponsored Research Office: Alelo TLT LLC
3937 MARCASEL AVE
LOS ANGELES
CA  US  90066-4615
(310)574-7500
Sponsor Congressional District: 36
Primary Place of Performance: Alelo TLT LLC
12910 Culver Bl., Suite J
Los Angeles
CA  US  90066-6709
Primary Place of Performance
Congressional District:
36
Unique Entity Identifier (UEI): Y1H7DDL3SR95
Parent UEI:
NSF Program(s): Cyberlearn & Future Learn Tech
Primary Program Source: 01001314DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 8045, 8841
Program Element Code(s): 802000
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

This Cyberlearning Exploration Project explores the potential for social robotics to transform foreign-language learning. The social robot being developed in this project is designed to act as a language partner for students learning a foreign language, in this case those learning Chinese. It augments classroom instruction, providing for the learner a robot companion to converse with. The hypothesis is that social robots can make interactions with language speakers more exciting and more accessible, especially for less commonly taught languages. The embodied robot is designed not only to converse with learners but also to point and nod and gesture at particular people and objects, helping to direct the attention of learners and interact socially with learners in ways that a non-embodied simulation cannot. The PIs take a task-based approach to language learning, helping students learn the language that goes with a variety of real-world situations. The technological innovation is a synthesis of social robots and social simulation; classroom language instruction is augmented by robot interaction. In this Exploration project, robots are being used in classrooms; as the price of such robots decrease, such robots could become available for after-school, library, cafeteria, or even home or public use.

This project brings together a leading developer of simulation-based learning solutions for intercultural communication (Alelo, Inc.) with a leading developer of lifelike intelligent robots (Hanson Robokind) to create a prototype social robot for language learners (in this case those learning Chinese) and to investigate the roles such robots might play in language learning and the most effective ways of interacting with learners so as to sustain their engagement in foreign-language conversation. The project meets a critical need in this country for a workforce that can engage well in the international marketplace. The particular focus in this project is on Mandarin Chinese language and culture, but what is learned will be applicable to other foreign languages as well.

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Social robots—robots that interact with and communicate with humans in a lifelike manner—have the potential to transform world language education. Low-cost robots that understand and respond to spoken language could give learners now opportunities to practice their conversational skills, in a fun, non-threatening environment. They could be particularly helpful in underserved schools where shortages of qualified language teachers limit access to high-quality foreign-language education.

Alelo tested the potential of social robotics for language education, through the use of low-cost robots designed to engage learners in complex conversational interactions in Mandarin Chinese. The prototype robot-assisted language learning system, named RALL-E (Robot-Assisted Language Learning in Education) was configured to engage in a variety of conversations that support language learning.

        Our work with RALL-E addresses the practical and complex problem of helping learners achieve conversational proficiency in a foreign language, which promotes a globally competent workforce. We created RALL-E to motivate language learners to practice critical speaking skills and support higher levels of proficiency. RALL-E is designed to operate in realistic classroom environments, which can be noisy and chaotic at times.

        RALL-E is capable of having conversations in Mandarin Chinese that are punctuated by realistic facial expressions and movement. Developed by Robokind, our robot had sophisticated facial reaction and expressions while talking to the students. With help from The Virginia Department of Education, we tested the robot in several Chinese classrooms at the Thomas Jefferson High School for Science and Technology in Alexandria, VA. The students were immediately drawn to the robot. They found it to be a novel and entertaining language-learning tool. They noted that the robot didn’t judge their attempts with the language, which put them at ease. Our study also indicated that facial expressions positively impacted language learning by providing positive feedback and encouragement.

        We went through several, focus group tested, iterations of the RALL-E robot until we arrived at our final design. Our partnership with Curious Labs allowed us to synthesize and analyze all student inputs and interactions over the course of several focus groups with many high school Mandarin classes. Student input was pivotal in how we designed the flow of conversations, the topics of discussion, and the use of the robot’s display screen. Our final product reflected what the students found to be most helpful in acquiring a new language and allowed for rewarding communicative practice that motivated students to practice the target language with the robot.

        Social robots are the next big thing in language learning. They are easily configurable and entertaining to use. Social robots motivate students to perform the daunting task of speaking a new language because they can do so in a personalized setting without judgment. This tool can potentially increase the fluency of foreign languages in the United States and create a more globally minded workforce. Our robot has the potential to address American monolingualism by providing convenient and sustainable immersion foreign language practice. Further research is needed to see t...

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