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Well-Oiled Machines: Collaborative Work in Robotics
dc.contributor.author | Slovenski, Steven | |
dc.date.accessioned | 2015-07-30T21:14:07Z | |
dc.date.available | 2015-07-30T21:14:07Z | |
dc.date.issued | 2015-07-15 | |
dc.identifier.uri | http://hdl.handle.net/1803/7141 | |
dc.description | Teaching and Learning Department capstone project | en_US |
dc.description.abstract | This paper explores the benefits and drawbacks of collaboration in robotics education. Robotics programs are growing across the country, but little guidance has been offered so far by research as to how these programs should be structured. The importance of getting it right quickly is paramount in a fast-moving field such as robotics. Most programs involve collaboration in small groups with a competition as the final goal. Some worry that a focus on competition may attract only a small segment of learners, and produce a non-diverse field. Some new programs include collaboration between small groups to achieve larger cooperative goals such as exhibitions. The benefits of collaboration will be discussed including the results of small group work, and the potential for broadening the spectrum of students who engage in robotics. This paper will divide its exploration into four sections: learner, learning context, curriculum, and assessment. Learners are viewed through a constructionist lens and they can be attracted to robotics for different reasons. The learning context of robotics is complex and flowing, and the collaborative nature of the environment produces many complex results for student outcomes. The curricula of robotics programs around the country vary widely, but can be very effective if the learning goal is kept in mind when the curriculum is designed. Assessing learning for collaborative robotics can be aided by several key strategies. Following the consideration of the four perspectives, the implications of the paper will be summarized, limitations will be presented, and areas for further research will be proposed. The author believes that this paper holds important results for the budding field of robotics education, including conclusions about optimal group size, proper teacher involvement, and methods for applying robotics to peripheral subject matter learning. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Vanderbilt University. Peabody College | en_US |
dc.rights | CC0 1.0 Universal | * |
dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
dc.subject | robotics, collaboration, education | en_US |
dc.title | Well-Oiled Machines: Collaborative Work in Robotics | en_US |
dc.type | Capstone | en_US |
dc.description.college | Peabody College of Education and Human Development | en_US |
dc.description.department | Department of Teaching and Learning | en_US |
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