Silk, Eli Michael (2011) *RESOURCES FOR LEARNING ROBOTS: ENVIRONMENTS AND FRAMINGS CONNECTING MATH IN ROBOTICS.* Doctoral Dissertation, University of Pittsburgh.

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## Abstract

How do learning environments influence the ways that middle school students use math to engage with and learn about robotics? Data from two observational studies suggest that existing formal (scripted inquiry) and informal (competitions) learning environments in this domain are limited in their support for connecting math with robotics. In light of the evaluation of these existing learning environments, two additional studies were conducted documenting the design, implementation, and redesign of a new learning environment intended to more effectively align learning and engagement with the connection between math and robots. Pre-post assessments and analyses of student work support the hypothesis that a model eliciting learning environment can facilitate learning while maintaining interest in both disciplines, and facilitate the development of a greater sense of the value of math in robotics. Two additional studies expanded on the previous work. The first study identified two contrasting approaches for connecting math with robots in the context of the model-eliciting learning environment from the previous studies. One approach used mathematics as a calculational resource for transforming input values into desired output values. The second approach used mathematics as a mechanistic resource for describing intuitive ideas about the physical quantities and their relationships. The second study manipulated instructional conditions across two groups of students that encouraged the students to take on one of these approaches or the other. Both groups engaged in high levels of productive mathematical engagement: designing, justifying, and evaluating valid strategies for controlling robot movements with connections to mathematics. But only the mechanistic group made significant learning gains and they were more likely to use their invented robot math strategies on a transfer competition task. All six studies taken together provide a rich description of the range of possibilities for connecting math with robots. Further, the results suggest that in addition to carefully crafting environments and associated tasks to align math and robots, that instructional designers ought to pay particular attention to helping students frame their approaches to using math productively as a tool for thinking about situations.

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## Details | ||||||||||||||||

Item Type: | University of Pittsburgh ETD | |||||||||||||||
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Title: | RESOURCES FOR LEARNING ROBOTS: ENVIRONMENTS AND FRAMINGS CONNECTING MATH IN ROBOTICS | |||||||||||||||

Status: | Unpublished | |||||||||||||||

Abstract: | How do learning environments influence the ways that middle school students use math to engage with and learn about robotics? Data from two observational studies suggest that existing formal (scripted inquiry) and informal (competitions) learning environments in this domain are limited in their support for connecting math with robotics. In light of the evaluation of these existing learning environments, two additional studies were conducted documenting the design, implementation, and redesign of a new learning environment intended to more effectively align learning and engagement with the connection between math and robots. Pre-post assessments and analyses of student work support the hypothesis that a model eliciting learning environment can facilitate learning while maintaining interest in both disciplines, and facilitate the development of a greater sense of the value of math in robotics. Two additional studies expanded on the previous work. The first study identified two contrasting approaches for connecting math with robots in the context of the model-eliciting learning environment from the previous studies. One approach used mathematics as a calculational resource for transforming input values into desired output values. The second approach used mathematics as a mechanistic resource for describing intuitive ideas about the physical quantities and their relationships. The second study manipulated instructional conditions across two groups of students that encouraged the students to take on one of these approaches or the other. Both groups engaged in high levels of productive mathematical engagement: designing, justifying, and evaluating valid strategies for controlling robot movements with connections to mathematics. But only the mechanistic group made significant learning gains and they were more likely to use their invented robot math strategies on a transfer competition task. All six studies taken together provide a rich description of the range of possibilities for connecting math with robots. Further, the results suggest that in addition to carefully crafting environments and associated tasks to align math and robots, that instructional designers ought to pay particular attention to helping students frame their approaches to using math productively as a tool for thinking about situations. | |||||||||||||||

Date: | 28 July 2011 | |||||||||||||||

Date Type: | Completion | |||||||||||||||

Defense Date: | 13 June 2011 | |||||||||||||||

Approval Date: | 28 July 2011 | |||||||||||||||

Submission Date: | 25 July 2011 | |||||||||||||||

Access Restriction: | No restriction; The work is available for access worldwide immediately. | |||||||||||||||

Patent pending: | No | |||||||||||||||

Institution: | University of Pittsburgh | |||||||||||||||

Thesis Type: | Doctoral Dissertation | |||||||||||||||

Refereed: | Yes | |||||||||||||||

Degree: | PhD - Doctor of Philosophy | |||||||||||||||

URN: | etd-07252011-202653 | |||||||||||||||

Uncontrolled Keywords: | epistemological framing; learning environments; mathematics in robotics education; mechanistic reasoning | |||||||||||||||

Schools and Programs: | School of Education > Instruction and Learning | |||||||||||||||

Date Deposited: | 10 Nov 2011 14:53 | |||||||||||||||

Last Modified: | 04 Jun 2012 13:22 | |||||||||||||||

Other ID: | http://etd.library.pitt.edu/ETD/available/etd-07252011-202653/, etd-07252011-202653 |

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