Elementary Students’ Computational Thinking Practice in A Bridge Design and Building Challenge (Fundamental)

ion Reducing complexity to make sense of things. The abstraction process allows building complex designs and large systems (An & Lee, 2014; Lee et al. 2011; Wing, 2006) CT Component Description Algorithm Applying specific set of tools or sequence of steps (processes) to solve problems (Barr, Harrison, & Conery, 2011; Yadav, Zhou, Mayfield, Hambrusch, & Korb, 2011) Communication Written and oral descriptions supported by graphs, visualizations, and computational analysis (Astrachan & Briggs, 2012) Conditional logic Using strategy such as an “if-then-else” construct to clarify problems and solutions (Wing, 2006) Data collection Gathering data to define or solve a problem (Grover & Pea, 2013; CSTA, 2009) Data structures, analysis and representation Exploring data to find patterns, causes, trends, or results to facilitate the knowledge construction and problem solving (Grover & Pea, 2013; CSTA, 2009) Decomposition Simplifying problems or specifying steps to solve problems (Catlin & Woollard, 2014) Heuristics Applying experience-based strategy that facilitates problem solving, such as "trial and error” (Yadav et al., 2011) Pattern recognition Recognizing repeated patterns such as iteration or recursion (Grover & Pea 2013; 2018) Simulation and Modeling Manipulating data or concepts through controlled programs or exercises or creating such programs for data manipulations (CSTA, 2009) Although CT has traditionally been implemented in only one or two subject areas at a time, more recent research studies/practices have taken an integrated STEM approach involving more than one subject or content areas (Yang et al., 2018). Regardless of differences in CT integration approaches or real-world implementation challenges, research from the National Research Council (NRC) stated that CT can be effectively integrated into K-12 STEM education and inquiry (Yang et al., 2018). To develop the abstraction CT component with middle and high school students, Lee et al. (2011) outlined how students were tasked with designing a robot that could sense and react to stimuli in simulated environmental conditions. Students needed to consider how to convert the interactions to abstract true-false (or numerical) values usable by the software control program. Brennan and Resnick (2012) used Scratch to elicit various CT components, such as conditional logic, where students would program objects to perform a desired action only if a particular condition was met. Yang and her colleagues (2018) designed a STEM+CT curriculum that showcased how CT components were embedded into inquiry activities and engineering design challenges where students collected data about Mars, extrapolated (i.e., abstraction) the environmental conditions, and communicated their findings with peers. Lee et al. (2011) noted that there are multiple possible domains (e.g., web design, mobile app development, robotics) that can be used to help develop CT practice in students. Moreover, what CT exactly looks like in practice can be dependent to some degree on the specific domain or field in which it is applied (Weintrop et al., 2016; Wing, 2010; Yang et al, 2018). Nevertheless, despite the variability in terms of potential methods of CT realization, there are numerous benefits when including CT practices in a discipline, and these benefits are not limited to scientists, mathematicians, engineers, programmers, computer scientists, or related professions/fields (NRC, 2011; Wing, 2010). The NRC (2011) highlighted the use of CT as part of the core practices for the scientific and engineering practices in its framework for K-12 science education. However, little research has been conducted on how students practice CT in their engineering practice.