Fostering Computational Thinking Among Underrepresented Students in STEM

Strategies for Supporting Racially Equitable Computing

Jacqueline Leonard, Jakita Thomas, Roni Ellington, Monica Mitchell, Olatokunbo Fashola

• Publisher: Routledge
• Year: 2021
• ISBN:
  9781000408898
• Edition: 1
• Topic: Bildung
• Subtopic: Bildungstechnologie

This book broadly educates preservice teachers and scholars about current research on computational thinking (CT). More specifically, attention is given to computational algorithmic thinking (CAT), particularly among underrepresented K–12 student groups in STEM education.

Computational algorithmic thinking (CAT)—a precursor to CT—is explored in this text as the ability to design, implement, and evaluate the application of algorithms to solve a variety of problems. Drawing on observations from research studies that focused on innovative STEM programs, including underrepresented students in rural, suburban, and urban contexts, the authors reflect on project-based learning experiences, pedagogy, and evaluation that are conducive to developing advanced computational thinking, specifically among diverse student populations.

This practical text includes vignettes and visual examples to illustrate how coding, computer modeling, robotics, and drones may be used to promote CT and CAT among students in diverse classrooms.

1 The Advent of Computational Thinking

Jacqueline Leonard and Jakita O. Thomas

Six children built a go-cart using the wheels and frame of a little red wagon, wood, rope, and cardboard boxes. They nailed wood horizontally above and beneath the frame to make the chassis. Another piece of wood was nailed vertically at a 90-degree angle across the chassis to turn the go-cart right or left with their feet. A rope was also tied to the frame to steer wheels, and the sides of the go-cart were made of cardboard boxes. The go-cart was placed at the top of the entrance to an alleyway, and the children took turns riding. When it was Jenni’s (pseudonym) turn, she found it difficult to steer the go-cart because it was traveling faster than she anticipated. Jenni turned sharply to the left and crashed. With minor injuries, she and the other children took the go-cart to the yard and tinkered with it to make the steering more manageable. These children, all under the age of 12, were limited only by their imagination and the materials they had on hand. This event could have taken place in any neighborhood regardless of place, ethnicity, or race. However, the go-cart was created by Black children during the 1960s. They were engaged in STEM before the term was ever spoken. They used engineering to design the go-cart, physics when they placed it at the top of the alleyway, mathematics when they placed horizontal and vertical parts at 90-degree angles, and computational thinking (i.e., conditional reasoning) to improve the steering. Moreover, they engaged in computational participation as evidenced by their planning, trial runs, and tinkering to improve the go-cart.

The vignette mentioned earlier is an authentic example of computational thinking (CT), which was popularized and defined by Wing (2006) as a “problem-solving approach that draws on concepts fundamental to computer science by ‘reformulating a seemingly difficult problem into the one we know how to solve, perhaps by reduction, embedding, transformation, or simulation’” (p. 33). The children in the vignette used reduction to solve the go-cart problem by examining how each part functioned in concert with the others. Consistent with Wing’s (2006) argument that CT is not just for computer scientists, these children were engaged in algorithmic thinking approaches similar to those posited by Pólya (1973), Sengupta et al. (2013), and others regarding the problem-solving process (i.e., translating, integrating, planning, and executing).

The impetus for building the go-cart, in part, was the popular television show, Speed Racer (Yoshida, 1967–1968) in which Trixie was a female character. Thus, the children translated what they saw in the cartoon into an actual image. Integration involved finding the necessary parts to create the go-cart. Planning occurred during the initial construction and refinement stages as the children tinkered with the go-cart to optimize its performance. Execution took place when the children tested the go-cart by steering it down the alleyway. Such occasions provide children with authentic experiences that predispose them to careers in science, technology, engineering, and mathematics (STEM). To illustrate this point, Jenni (pseudonym) in the aforementioned vignette is the first author of this text, Jacqueline Leonard. She recalled the excitement that she felt while building the go-cart and realized it was an example of CT. As a Black woman, Jacqueline believes she is fortunate to be born after Brown vs. Board of Education (1954). What factors influenced her to become a mathematics educator/researcher?

Recollections of her childhood and schooling revealed a broad interest in mathematics and science. Jacqueline participated in at least two science fairs while attending a predominantly Black urban K-8 public school, and school records showed a composite Iowa Test of Basic Skills score of 11.0 (i.e., 11th grade, 0-month grade-level equivalency) in grade eight. Mathematics was her favorite subject, and she excelled in algebra I, algebra II/trigonometry, biology, and chemistry in high school. Obtaining a full scholarship to Boston University she double-majored in physical therapy and pre-med. Although she worked as a candy striper at a hospital in her community where she was mentored by a medical supply technician, Jacqueline did not have a clear understanding of what physical therapy entailed. Lacking exposure to role models and being unfamiliar with health science and medicine, Jacqueline decided to become a science and mathematics teacher. Black women in her community, as well as an aunt, were teachers and role models. Moreover, she enjoyed sharing her knowledge and enthusiasm with children to ensure they had adequate preparation and opportunities to succeed. Jacqueline completed a Bachelor of Arts degree and teacher certification at Saint Louis University. Her love of learning later led her to obtain a Master of Arts in Teaching Mathematical Sciences from the University of Texas at Dallas. A teacher colleague—Dr. William F. Tate IV—who obtained his PhD at the University of Maryland and became an assistant professor in Wisconsin, led her to do the same. In 1997, Jacqueline received a PhD in Curriculum and Instruction and began a tenure-track position in mathematics education at Temple University.

Imagine what Black¹ children in the 21st century may invent or create using Shuri from the movie, Black Panther (Coogler, 2018), as their role model or impetus. What gendered and racial examples do children see and experience in the 21st century that allow them to see themselves in STEM? What impact will the COVID-19 pandemic have on children’s interest in STEM in this decade? Understanding how viruses grow exponentially and how computers can be used to model growth curves are of interest to society at large as well as K-12 students. The foregoing vignette, as well as others presented in this text, will be used as a springboard for discussing research and practice that foster CT and computational participation among underrepresented students, including girls and students of color. Strategies that have been successful in broadening STEM participation for underrepresented and underserved K-12 students are advanced in this work, which begins with self-efficacy and expectancy value as conceptual frameworks, which are followed by the underpinnings of CT.

Theoretical Framework

The projects referenced in this text were funded by the National Science Foundation’s (NSF), Innovative Technology Experiences for Students and Teachers (ITEST) program. Two projects—uGame-iCompute (2013–2017) and Bessie Coleman (2018–2021)—were grounded in self-efficacy theory (Bandura, 1997) and expectancy-value theory (Wigfield & Eccles, 2000). Bandura (1997) contended that mastery experiences, vicarious experiences, verbal persuasion, and affective states contribute to efficacy. Mastery experiences include activities that allow a person to develop skills in a particular field, such as serving as an intern in a specific occupation. Schunk (2020) contended that observing or listening to human, nonhuman (e.g., cartoon characters or animated creatures), or multimedia sources (e.g., television, movies, DVDs, books, etc.) results in vicarious learning. Research has shown that role models (Bracey, 2013; Jacob et al., 2018; Ryoo, 2019; Thomas et al., 2018), whether real or imaginary, are important vicarious figures when it comes to broadening participation in STEM. Efficacy drawn from vicarious experiences entails seeing the qualities of others who excelled at a particular endeavor in oneself. Verbal persuasion occurs when a perceived expert affirms or disaffirms one’s ability to pursue a specific career. Thus, parents, teachers, and counselors can play an important role in students’ persistence in STEM. Affective states refer to students’ preferences or desire to pursue a specific career. Exposure to specific career paths may lead students to pursue those paths. One purpose of the projects was to expose underrepresented students to computer science through robotics/game design (i.e., uGame-iCompute) and computer modeling/drones (i.e., Bessie Coleman Project).

In terms of expectancy-value theory, Wigfield and Eccles (2000) contended that “individuals’ choice, persistence, and performance can be explained by their beliefs about how well they do on [an] activity and the extent to which they value the activity” (p. 68). The value one places on a subject or task predicts future participation in similar subjects or tasks (e.g., enrolling in advanced STEM courses, pursuing STEM careers, etc.). Leonard (2019), Ryoo (2019), Scott et al. (2015), and Thomas et al. (2018) are some of the researchers who suggest that culturally responsive computing and intersectional computing are needed to increase access and equity in computer science. Thus, role models, culturally responsive computing, and intersectional computing along with educational innovation and real-world applications, are crucial elements for sustaining interest, increasing self-efficacy, and developing STEM identity among females and ethnically/racially diverse students.

The Emergence of Computational Thinking in Education

Yadav et al. (2017) traced the development of CT from the problem-solving process work of Pólya (1973), a mathematician whose How to Solve It publication made important contributions to mathematics education. Without the benefit of computer science, Pólya articulated how to solve problems in a systematic way (Yadav et al., 2017). In the 1980s, CT became associated with Seymour Papert, who pioneered the notion that children can use procedures to engage in LOGO programming (Grover & Pea, 2013). In Papert’s seminal text entitled, Mindstorms (1980, 1993), the LOGO programming language provided an example of how technology can be used to promote CT (Kafai & Burke, 2014; Leonard, 2019). Papert believed that LOGO provided students with opportunities to use the computer to influence how people think (Yadav et al., 2017). This is important because ability to think and engage in mental processes is the crux of learning and cognition (Schunk, 2020).

In the 1950s and 1960s, problem solving gave way to algorithmic thinking (Rich & Langston, 2016), which is defined as the ability to formulate a solution to a problem in algorithmic form and then implement it as a computer program (Syslo, 2015). Yet, others emphasize the importance of using a computer to solve problems (Barr & Stephenson, 2011). Moreover, Sengupta et ...