TY - JOUR
T1 - Introducing Algorithmic Thinking and Sequencing Using Tangible Robots
AU - Evripidou, Salomi
AU - Amanatiadis, Angelos
AU - Christodoulou, Klitos
AU - A. Chatzichristofis, Savvas
N1 - Publisher Copyright:
© 2008-2011 IEEE.
PY - 2021/2
Y1 - 2021/2
N2 - Today, in the era of robotics, different types of educational robots have been used extensively in school classrooms to facilitate teaching activities related to a variety of computer science concepts. Numerous studies have been performed that attempt to examine the effects of using tangible interfaces to enhance collaborative learning experiences. In most of these studies, feedback, which is a vital function for a successful game activity, is mainly provided by the trainers. However, this kind of feedback can be considered as static and general, while each trainee seeks clear, consistent, and even personalized feedback. This article proposes an interactive learning tool for introducing algorithmic thinking and sequencing using educational robots suitable for elementary and intermediate students. In more detail, in this article, we leverage a fuzzy-rule-based system and computer vision techniques to provide immediate, personalized feedback and recommendations to young students while they perform a series of activities using tangible robots. These activities relate to teaching programming skills and improve the algorithmic thinking of students. Experimental results revealed that participants were able to increase their algorithmic/programming thinking skills while developing a positive attitude toward programming. The interactive gaming factor that is embedded in the use of tangible robots, while participating in the activities, was proved to be a compelling and a rewarding experience. The article concludes that the use of the proposed feedback mechanism, when placed in a robot game environment, can lead to a positive and more effective learning process.
AB - Today, in the era of robotics, different types of educational robots have been used extensively in school classrooms to facilitate teaching activities related to a variety of computer science concepts. Numerous studies have been performed that attempt to examine the effects of using tangible interfaces to enhance collaborative learning experiences. In most of these studies, feedback, which is a vital function for a successful game activity, is mainly provided by the trainers. However, this kind of feedback can be considered as static and general, while each trainee seeks clear, consistent, and even personalized feedback. This article proposes an interactive learning tool for introducing algorithmic thinking and sequencing using educational robots suitable for elementary and intermediate students. In more detail, in this article, we leverage a fuzzy-rule-based system and computer vision techniques to provide immediate, personalized feedback and recommendations to young students while they perform a series of activities using tangible robots. These activities relate to teaching programming skills and improve the algorithmic thinking of students. Experimental results revealed that participants were able to increase their algorithmic/programming thinking skills while developing a positive attitude toward programming. The interactive gaming factor that is embedded in the use of tangible robots, while participating in the activities, was proved to be a compelling and a rewarding experience. The article concludes that the use of the proposed feedback mechanism, when placed in a robot game environment, can lead to a positive and more effective learning process.
KW - Algorithmic thinking
KW - educational robots
KW - sequencing
KW - tangible programming
UR - http://www.scopus.com/inward/record.url?scp=85101491068&partnerID=8YFLogxK
U2 - 10.1109/TLT.2021.3058060
DO - 10.1109/TLT.2021.3058060
M3 - Article
AN - SCOPUS:85101491068
SN - 1939-1382
VL - 14
SP - 93
EP - 105
JO - IEEE Transactions on Learning Technologies
JF - IEEE Transactions on Learning Technologies
IS - 1
M1 - 9351683
ER -