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A review of intuitive robot programming environments for educational purposes

Authors: Flor A. Bravo; Alejandra M. Gonzalez; Enrique Gonzalez;

A review of intuitive robot programming environments for educational purposes

Abstract

This paper examines the main robot programming strategies and how they are used in the educational context. We analyze the advantages and drawbacks of the most common programming strategies in educational robotics such as textual, visual, and tangible based programming. Additionally, it explores the approach of programming by demonstrations PbD in an educational context. We identify the main PbD techniques, such as demonstrations through manipulation of the body of the learner robot or a model of the robot, demonstrations through the body motions of a human o robot teacher, demonstrations through the behavior of an object, among others. The paper also identifies the programming techniques that allow non-programmers to create a robot program easily. Furthermore, we present research opportunities of intuitive robot programming in an educational context. Currently, the scope and impact of robot-based activities have primarily focused on the teaching and learning of technical subjects. In this paper, we discuss some characteristics that robot programming environments should have to facilitate the integration of educational robotics in the learning and teaching processes of non-technical school subjects.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Top 10%
Average
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