Sengupta, etal: Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework
The authors argue that while computational thinking (CT) plays a fundamental role in computer science, it could also have intriguing novel applications in the STEM disciplines by exposing K-12 students to practices of simulation, representation, abstraction, and prediction. According to the article, these computational concepts can support modeling and experimentation practices in science classrooms. The authors argue for agent-based computation via visual programming, meaning that users are able to program certain aspects of their computational models via manipulation of graphical objects. As part of their research, the authors studied the effects of agent-based computation on middle school student learning in ecology and kinematics. Using a program called CTSiM, students were able to create a computational algorithm, run a simulation of said algorithm, compare their simulation to an expert model, and revise their model as needed. The results indicated that significant learning gains were made through computational thinking, but individual student scaffolding is a crucial component of successful computation-based learning.
- · Immersing students in an experience or environment: This immersion is good for learning because it allows students to simulate and manipulate scientific phenomena.
- · Design-based learning: Computation activities can be used to help students focus on experimental design and modes of representation, which helps them engage in alternative scientific models and critical thinking regarding scientific argumentation.
- · Generalizability and decomposition: Due to the general nature of computational modeling and the ability of computer-based models to break down a phenomenon into more digestible components, the authors argue that CT can be used to simplify scientific models over a wide range of applications.
Grover & Pea: Computational Thinking in K-12: A Review of the State of the Field
This article addresses the effect of Jeannette Wing’s celebrated article, “Computational Thinking,” on attitudes towards incorporating computer-based learning in K-12 science education. Wing noted that CT encourages a widely applicable critical thinking skill set, and she elaborated on its role in fostering problem-solving techniques and abstraction. The authors also see these overarching benefits to computer-based modeling, but note that current school curricula do not provide much room for adding additional material. By focusing critical attention on CT’s goals, effectiveness, and its applicability to state standards and assessments, programmers will have a higher shot of incorporating and mainstreaming computational-based materials in schools.
- · Low floor, high ceiling: Effective programming should be easy for the user to interact with while simultaneously providing significant room for students to grow and explore.
While both articles advocated for the potential usefulness of CT in K-12 education, the Grover & Pea reading seems to believe that certain applications of computer-based learning have yet to be investigated thoroughly. They argue that without knowing what CT skills students are expected to have and be assessed on, computational modeling will continue to struggle to gain mainstream incorporation in the American education system. As a future educator, I think that CT can help students reach valuable learning goals. However, Grover & Pea bring up an interesting point: how, in a current system that is implicitly run by standardized testing, can we incorporate CT to align with “testable” goals? Can we afford to take time away from explicitly-stated education standards? I hope so, but it is hard to tell without actually having taught.