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Systematic literature review: teaching novices programming using robots

Teaching novices programming using robots
Authors: Louis Major; Theocharis Kyriacou; O. Pearl Brereton;

Systematic literature review: teaching novices programming using robots

Abstract

Background: Teaching programming to novices is a difficult task due to the complex nature of the subject, as negative stereotypes are associated with programming and because introductory programming courses often fail to encourage student understanding. Aim: This study investigates the effectiveness of using robots as tools to aid the process of teaching programming and to determine whether such technology can help to overcome the current barriers for learners in this context. Method: The Systematic Literature Review (SLR) methodology has been selected to discover how effective the use of robotics has been in the teaching of introductory programming concepts. Nine electronic databases, the proceedings from six conferences and two journals have been searched for literature relevant to the study. Results: After applying inclusion and exclusion criteria 34 articles have been accepted in the SLR. 74% of included literature report robots to be an effective teaching tool and one that can help novice programmers in their studies. Conclusion: Robots can be a powerful and effective tool when used in an introductory programming course but the potential remains to further investigate methods for their implementation. Thoughts on the use of the SLR methodology from the perspective of a PhD student are also given.

Country
United Kingdom
Related Organizations
Keywords

robotics, learning, control engineering computing, systematic literature review, computer-aided instruction, novices, programming, teaching, SLR, robots, computer science education, innovative, educational courses

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    selected citations
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    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).
    52
    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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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!
52
Top 10%
Top 10%
Top 10%
gold