| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | September 11, 2013 |
| Latest Amendment Date: | April 21, 2015 |
| Award Number: | 1321042 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Amy Baylor
abaylor@nsf.gov (703)292-5126 IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 15, 2013 |
| End Date: | August 31, 2017 (Estimated) |
| Total Intended Award Amount: | $275,001.00 |
| Total Awarded Amount to Date: | $283,001.00 |
| Funds Obligated to Date: |
FY 2015 = $8,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
1608 4TH ST STE 201 BERKELEY CA US 94710-1749 (510)643-3891 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
CA US 94720-1670 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
REAL, Cyberlearn & Future Learn Tech |
| Primary Program Source: |
01001516DB NSF RESEARCH & RELATED ACTIVIT 04001314DB NSF Education & Human Resource |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
In this Cyberlearning: Transforming Education EXP project, PIs from computer science and mathematics education are collaborating to investigate the use of gestures by teachers (both human and virtual) and learners in support of mathematics learning. They are investigating the ways teachers' gestures influence learning of mathematics concepts and how to design gestural supports for learning that a computer avatar might use in communicating with a learner. Their conceptual foundations come from embodied cognition, and they are aiming towards understanding the integration of two types of gestures: those that are used to promote understanding of content and those used for social purposes. The project focuses on learning of proportion, and the technological innovation in this project is creation of a gesturing pedagogical agent/avatar that has a rich repertoire of both types of gestures that it uses while interacting with a learner and helping the learner to deepen his or her understanding of the mathematics of proportion. In a series of design studies, the PIs are designing software and extracting principles for augmenting pedagogical agents with new gesture-enriched capabilities and gleaning insights into the nature, types, and roles of gesture in educational interaction.
Despite consistent reform efforts, U.S. students still lag behind their global peers in mathematics understanding and capabilities. Intelligent tutoring systems can be used to provide one-on-one help to students who are struggling as they learn mathematics, but such interactions lack the social cues that help learners maintain their attention and know they are being understood and lack, as well, full means of expressing concepts in ways that learners might need for understanding. Good teachers use gestures for these purposes, and this project focuses on design of pedagogical agents (avatars) that will also be able to use such gestures. Infusing interactive tutoring systems with the ability to gesture in naturalistic and domain-appropriate ways may provide a missing link in making tutorial interactions effective for more learners. At the same time, insights gleaned about the pedagogical roles of gesturing can be leveraged in educating teachers of the future.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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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.
A substantial and growing literature demonstrates that successful teaching of mathematics relies on complex coordinations of demonstrative, reactive, and discursive actions in both verbal and nonverbal modalities. While embodied, multimodal communication is a ubiquitous dimension of mathematics pedagogical practice, it remains untapped in digital media applications. Gesture, in particular, provides critical spatial-dynamical complements to verbal and symbolic utterance. Digital media offer the potential for widespread distribution of effective instructional interventions at moderate cost, but is hampered by the lack of embodied communication that is so effective in the teaching of mathematics. This work developed animated pedagogical agents to realize the potential of digital media by enhancing them with fluid verbal and nonverbal behavior to provide mathematics training for children.
In particular, this work developed a pedagogical agent designed to support students in an embodied, discovery-based learning environment. Discovery-based learning guides students through a set of activities designed to foster particular insights. In this case, the animated agent explains how to use the Mathematical Imagery Trainer for Proportionality, a system for teaching the mathematical concept of proportion, provides performance feedback, leads students to have different physical and symbolic experiences related to proportion, and provides remedial instruction when required. Building a system to automatically determine agent behavior is a challenging task for agent technology, as the amount of concrete feedback from the learner is very limited, here restricted to the location of two markers on the screen. A Dynamic Decision Network was designed to automatically determine agent behavior, based on a deep understanding of the tutorial protocol. A pilot evaluation showed that all participants developed goal movement schemes supporting proto-proportional reasoning. They were able to provide verbal proto-proportional expressions for one of the taught strategies. The project yielded and publicized an innovative and carefully documented Dynamic Decision Network methodology that is broadly generalizable across other efforts to build interactive animated pedagogical avatars, along with a software architecture that can be used to develop such applications. The work further demonstrated the effectiveness of embodied pedagogical agents for this type of learning task, providing a basis for further development of this technology. In addition, new collaboration strategies were published that will allow learning scientists and computer scientists to work more effectively on developing future embodied technologies.
The project contributed substantially to student education and training of a technically qualified workforce. Four graduate students in computer science and six undergraduates in computer science received training during this project. An additional four graduate students in learning science and five undergraduates in learning science received training, contributing to the development of a highly qualified workforce.
Last Modified: 12/08/2017
Modified by: Dor Abrahamson
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