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Vol.15, No.1, 2023, BECE 1796 

 

 

 

 

Technology-Supported Teaching Interventions and 

Student Computational Thinking: A Meta-Analysis 

Based on 37 Empirical Studies 

By Zhou, Q. & Deng, Y. 
Correspondence to: Qin Zhou, Southwest University, China. E-mail: 

zhqjojo@126.com  

OMPUTATIONAL thinking, which integrates a wide variety of think-

ing activities such as problem-solving, system design, and comprehend-

ing human behavior, has become a critical thinking ability in the context of 

accelerated digital transformation. Numerous studies from various counties 

posited that technology-supported teaching interventions (TSTI) had the po-

tential to foster the development of computational thinking skills in students, 

whereas some suggested that the potential was insignificant. This article em-

ployed the meta-analytical technique to research into 37 domestic and for-

eign empirical studies published between January 2006 and October 2022, 

with a focus on examining the impact of TSTIs on student computational 

thinking. Research findings are as follows. 

i. TSTIs had positive effects on the development of students’ computa-

tional thinking skills. 

ii. The effectiveness of computational thinking training differed in various 

disciplines; there were prominent inter-group differences in the efficacy 

of teaching interventions. The outcomes of computational thinking 

training were insignificant in English and information science courses, 

but significant in Spanish and dance classes.  

iii. The intervention effects of graphical/ modular programming languages 

and game-based programming contexts were significant, indicating that 

these two types of tools were substantially beneficial for cultivating stu-

dents’ computational thinking skills. That means the ideal match be-

tween the tool and the learning agent can result in desirable teaching 

outcomes. 

iv. Among evaluation tools of student computational thinking, formative 

assessment based on the programming environment were timelier and 

more authentic, though posing higher requirements for technical devel-

opment compared to other forms of assessment. Furthermore, there was 

no one single evaluation tool that suited all teaching settings. 

v. Teaching interventions for small-size class, junior secondary school 

students, and lasting 6-11 weeks had better effects, and there were no 

C 

mailto:zhqjojo@126.com


 

Vol.15, No.1, 2023, BECE 1797 

significant gender differences in their impact on computational thinking 

development of students. 

Recommendations were made based on the foregoing findings. (i) 

Place high premiums on computational thinking development of students and 

design teaching intervention strategies corresponding to differential catego-

ries of computational thinking skills. (ii) Contextualize teaching inventions in 

real-world situations and give students opportunities to showcase their com-

putational thinking skills, which can potentially increase students’ ability to 

transfer and apply computational thinking skills in a variety of disciplines. 

(iii) Employ intervention tools that can train multidimensional computational 

thinking skills in students as well as meeting their problem-solving and ad-

vanced learning needs. (iv) Introduce foreign evaluation tools for computa-

tional thinking that pertain in China’s education settings and strengthen de-

veloping localized ones. (v) Adopt small-size class teaching with special fo-

cus on junior secondary school students; place emphasis on the development 

of computational thinking skills in both male and female students to forego 

the stereotype of computer science-related disciplines being dominated by 

male students. 

 
Source: Journal of Southwest University (Natural Science Edition), 2023; 45(6):44-56. 


