Development of computational thinking and collaborative learning in kindergarten using programmable educational robots

Author(s):  
Yen Air Caballero González ◽  
Ana García-Valcárcel Muñoz-Repiso
2021 ◽  
Vol 30 (3) ◽  
pp. 334
Author(s):  
Lap Kei Lee ◽  
Tsz Kin Cheung ◽  
Lok Tin Ho ◽  
Wai Hang Yiu ◽  
Nga In Wu

Author(s):  
Angelo Magno De Jesus ◽  
Ismar Frango Silveira

Computational Thinking (CT) can amplify learners’ skill sets so that they become excellent problem-solvers. Game-Based Learning and Collaborative Learning are two approaches that may aid in the development of CT skills. This paper describes a framework based on Game and Problem-Based Learning Strategies which aims to enhance the CT teaching and improves students’ social skills, considering aspects of fun. The framework stands out for including collaborative learning features defined in the main literature. Also, the strategy was developed specifically to fit the games’ dynamics. The approach was evaluated via metacognitive and transactive analysis and by a survey. The results showed evidence that the method is able to stimulate interaction among students to apply problem-solving strategies.


2021 ◽  
Vol 30 (3) ◽  
pp. 334
Author(s):  
Lap Kei Lee ◽  
Tsz Kin Cheung ◽  
Lok Tin Ho ◽  
Wai Hang Yiu ◽  
Nga In Wu

2021 ◽  
pp. 073563312199407
Author(s):  
Yanjun Zhang ◽  
Ronghua Luo ◽  
Yijin Zhu ◽  
Yuan Yin

Due to the interdisciplinary nature of robotics, more and more attention has been paid to its effectiveness in the field of education in recent years. This systematic review evaluated existing studies in improving K-12 students’ computational thinking and STEM attitudes. Research articles published between 2010 and 2019 were collated from major databases according to six criteria, and 17 studies were eligible. A meta-analysis was conducted to evaluate the effectiveness of educational robots in terms of standardized mean differences (SMD) or mean differences (MD) of test scores as outcome measures. The overall effect size was medium (SMD = 0.46, 95% CI: 0.23–0.69). Subgroup analysis found that some groups to have better effectiveness. Specifically, the effect of STEM attitudes (SMD = 0.01) was smaller than computational thinking (SMD = 0.48). Educational robots had more significant effect on boys (MD = 0.39) than girls (MD = 0.27). The effect in primary school (SMD = 0.27) was higher than in middle school (SMD = 0.04), and the effect was great on short-term instruction with educational robots (SMD = 0.35). Based on these results, the study makes some recommendations for educators about strengthening the influence of educational robots on STEM attitudes, improving the persistence of their learning effects, and further exploring their application models.


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