Computational thinking (CT), an essential 21st century skill, incorporates key computer science concepts such as abstraction, algorithms, and debugging. Debugging is particularly underrepresented in the CT training literature. This multi-level meta-analysis focused on debugging as a core CT skill, and investigated the effects of various debugging…

The interest in Computational Thinking (CT) development among young learners increases with the number of studies located in literature. In this study, a meta-analysis was conducted to address two main objectives: (a) the effectiveness of empirical interventions on the development of CT in children aged of 3-8 years; and (b) the variables that…

While numerous studies of robot-assisted language learning (RALL) for English-as-a-foreign-language (EFL) learners' language skill development have been done, a comprehensive and theoretically-driven meta-analysis on its effects is still in paucity. To fill the gap, drawing on Activity Theory (AT), this study reported a meta-analysis from 47…

This meta-analysis examines the effects of game-based learning (GBL), compared with traditional instructional methods, on the science achievement of students, ranging from primary school to university. Results from the 41 primary studies of 6256 participants showed heterogeneity among effect sizes. The random effects model results showed a…

The purpose of this research study was to examine the overall effect of adaptive learning systems deployed using artificial intelligence technology across a range of relevant variables (e.g., duration, student level, etc.). Following a systematic procedure, this meta-analysis examined literature from 18 academic databases and identified N = 45…

This meta-analysis determined game-based learning's (GBL) overall effect on students' computational thinking (CT) and tested for moderators, using 28 effect sizes from 24 studies of 2,134 participants. The random effects model results showed that GBL had a significant positive overall effect on students' CT (g = 0.677, 95% confidence interval…

Automated writing evaluation (AWE) has been frequently used to provide feedback on student writing. Many empirical studies have examined the effectiveness of AWE on writing quality, but the results were inconclusive. Thus, the magnitude of AWE's overall effect and factors influencing its effectiveness across studies remained unclear. This study…