A systematic review of computational thinking in science classrooms

2021 ◽  
pp. 1-28
Author(s):  
Ayodele Abosede Ogegbo ◽  
Umesh Ramnarain
2020 ◽  
Vol 148 ◽  
pp. 103798 ◽  
Author(s):  
Xiaodan Tang ◽  
Yue Yin ◽  
Qiao Lin ◽  
Roxana Hadad ◽  
Xiaoming Zhai

2014 ◽  
Vol 081 (05) ◽  
Author(s):  
Cary Sneider ◽  
Chris Stephenson ◽  
Bruce Schafer ◽  
Larry Flick

2015 ◽  
Vol 25 (1) ◽  
pp. 127-147 ◽  
Author(s):  
David Weintrop ◽  
Elham Beheshti ◽  
Michael Horn ◽  
Kai Orton ◽  
Kemi Jona ◽  
...  

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.


2021 ◽  
pp. 073563312110331
Author(s):  
Ndudi O. Ezeamuzie ◽  
Jessica S. C. Leung

This article provides an overview of the diverse ways in which computational thinking has been operationalised in the literature. Computational thinking has attracted much interest and debatably ranks in importance with the time-honoured literacy skills of reading, writing, and arithmetic. However, learning interventions in this subject have modelled computational thinking differently. We conducted a systematic review of 81 empirical studies to examine the nature, explicitness, and patterns of definitions of computational thinking. Data analysis revealed that most of the reviewed studies operationalised computational thinking as a composite of programming concepts and preferred definitions from assessment-based frameworks. On the other hand, a substantial number of the studies did not establish the meaning of computational thinking when theorising their interventions nor clearly distinguish between computational thinking and programming. Based on these findings, this article proposes a model of computational thinking that focuses on algorithmic solutions supported by programming concepts which advances the conceptual clarity between computational thinking and programming.


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