Introducing Computational Thinking to Young Learners: Practicing Computational Perspectives Through Embodiment in Mathematics Education

A science, technology, engineering, and mathematics-influenced classroom requires learning activities that provide hands-on experiences with technological tools to encourage problem-solving skills (Brophy et al. in J Eng Educ 97(3):369–387, 2008; Matarić et al. in AAAI spring symposium on robots and robot venues: resources for AI education, pp 99–102, 2007). The study aimed to bring computational thinking, an applicable skill set in computer science, into existing mathematics and programming education in elementary classrooms. An essential component of computational thinking is the ability to think like a computer scientist when confronted with a problem (Grover and Pea in Educ Res 42(1):38–43. doi:10.3102/0013189X12463051, 2013). Computational perspectives (Berland and Wilensky in J Sci Educ Technol 24(5):628–647. doi:10.1007/ s10956-015-9552-x, 2015) refer to the frame of reference programmers or computer scientists adopt when approaching a problem. The study examined the effects of taking computational perspectives through various degrees of embodied activities (i.e., full vs. low) on students’ achievement in mathematics and programming. The study employed a 2 (full vs. low embodiment) 9 2 (with vs. without computational perspective taking) factorial condition to evaluate four learning conditions from a combination of embodiment and computational perspective-taking practice. The results from this experimental study (N = 66 kindergarten and first graders) suggest that full-embody activities combined with the practice of computational perspective-taking in solving mathematics problem improved & Woonhee Sung [email protected] Junghyun Ahn [email protected] John B. Black [email protected] 1 Department of Mathematics, Science and Technology, Teachers College, Columbia University, 525 W. 120th Street, New York, NY 10027, USA 2 Department of Human Development, Teachers College, Columbia University, 525 W. 120th Street, New York, NY 10027, USA 123 Tech Know Learn (2017) 22:443–463 DOI 10.1007/s10758-017-9328-x