Building Mathematics + Computational Thinking Trajectories From Existing Literature

• In Event: 41.049 - Stories From the Field: Integrating Computational Thinking Across Curricular Domains

Abstract

Purpose. Given recent calls for integration of computer science (CS) into K-12, scholars and practitioners are exploring how CS concepts might best be developed across grade levels. We conducted a wide-ranging literature review designed to synthesize methodological research about CS learning goals for K-5 into a set of coherent learning trajectories (LTs). We focus specifically on computational thinking (CT) and how it might map onto existing mathematics LTs.

Theoretical Framework. Our project is based on prior work in computational thinking and LTs. Wing (2006) and others note connections between CT and problem-solving strategies of other disciplines. Integration with other subjects is a logical approach to fitting new content into an already-full K-5 curriculum. Hence, CT is a good fit for considering what CS content should be taught in K-5. To examine how content might be developed across grades, we use a LT approach, which has proven successful in mathematics education research (e.g., Clements & Sarama, 2004; Confrey, Malone, & Corley, 2014). We conceptualize LTs as having three fundamental parts: a set of learning goals, a developmentally appropriate path through those goals, and a set of illustrative activities that help students move along the path (Clements & Sarama, 2004). Our review process allows us to extract learning goals from research literature and document information that will help us assemble them into pathways and match them to illustrative activities.

Methods. Curriculum developers are reviewing literature and recording explicitly or implicitly stated learning goals, defined as any statements of what students can or should be able to do in relation to CT. For each goal, we document the grade level(s) (if noted) for which it is claimed to be appropriate and the most closely aligned of the CT concepts identified by Grover and Pea (2013). Researchers are also parsing out the main methodological areas to document the evidence base that will support our LTs. All information is recorded in a database that we will search and sort to organize the learning goals into trajectories.

Data sources. Articles that resulted from a search of various databases with the strings “computational thinking,” “computer science education,” and “computer science” with the additional keywords of “goals,” “ideas,” and “domains.”

Results. Work is ongoing. Thus far, we have noted that less than half of the goals we documented are supported by classroom evidence. Discussion of the learning goal data has suggested the emergence of four domains of CT: (1) Program development process; (2) Computing languages, environment, and constructs; (3) Algorithms and flow of control; and (4) Applications of computing. One and two could form the base of LTs with potential for integration with mathematics. Three suggests that there are CT goals that are best addressed outside the context of another subject. Four may better serve as a source of ideas for filling in gaps in the other trajectories than as its own trajectory.

Significance. These findings have significance for teachers and curriculum developers working to bring CS to K-5. Researchers may find our LTs a useful basis for further research.

Authors

• Kathryn Rich, University of Chicago

• Jelena Pokimica, University of Illinois at Urbana-Champaign

• Quentin Wherfel

• Carla Strickland, University of Chicago

• Cheryl Moran, University of Chicago