Abstract
AbstractEducational robotics, as emerging technologies, have been widely applied in the field of STEM education to enhance the instructional and learning quality. Although previous research has highlighted potentials of applying educational robotics in STEM education, there is a lack of empirical evidence to investigate and understand the overall effects of using educational robotics in STEM education as well as the critical factors that influence the effects. To fill this gap, this research conducted a multilevel meta-analysis to examine the overall effect size of using educational robotics in STEM education under K-16 education based on 30 effect sizes from 21 studies published between 2010 and 2022. Furthermore, we examined the possible moderator variables of robot-assisted STEM education, including discipline, educational level, instructor support, instructional strategy, interactive type, intervention duration, robotic type, and control group condition. Results showed that educational robotics had the moderate-sized effects on students’ STEM learning compared to the non-robotics condition. Specifically, educational robotics had moderate-sized effects on students’ learning performances and learning attitudes, and insignificant effects on the improvement of computational thinking. Furthermore, we examined the influence of moderator variables in robot-assisted STEM education. Results indicated that the moderator variable of discipline was significantly associated with the effects of educational robotics on STEM learning. Based on the findings, educational and technological implications were provided to guide future research and practice in the application of educational robotics in STEM education.
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Reference100 articles.
1. Anwar, S., Bascou, N. A., Menekse, M., & Kardgar, A. (2019). A systematic review of studies on educational robotics. Journal of Pre-College Engineering Education Research, 9(2), 1–10. https://doi.org/10.7771/2157-9288.1223
2. Assink, M., & Wibbelink, C. J. (2016). Fitting three-level meta-analytic models in R: A step-by-step tutorial. The Quantitative Methods for Psychology, 12, 154–174. https://doi.org/10.20982/tqmp.12.3.p154
3. Atman Uslu, N., Yavuz, G. Ö., & Koçak Usluel, Y. (2022). A systematic review study on educational robotics and robots. Interactive Learning Environments, 31(9), 5874–5898. https://doi.org/10.1080/10494820.2021.2023890
4. Augello, A., Daniela, L., Gentile, M., Ifenthaler, D., & Pilato, G. (2020). Robot-assisted learning and education. Frontiers in Robotics and AI, 7, 591319. https://doi.org/10.3389/frobt.2020.591319
5. Batdi, V., Talan, T., & Semerci, C. (2019). Meta-analytic and meta-thematic analysis of STEM education. International Journal of Education in Mathematics, Science and Technology, 7(4), 382–399. https://ijemst.net/index.php/ijemst/article/view/803
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