Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework
Sengupta et al demonstrates that computation thinking (CT) draws on student knowledge of practices and concepts essential to computer science including epistemic and representational practices, which can take various forms such as representing problems, abstracting, decomposing problems, simulating, verifying, and predicting. Arguments have recently been made to incorporate CT into K-12 STEM curricula.
The four proposed tenants of the framework are the synergy between CT and scientific modeling, choosing specific programming paradigms, selecting specific scientific topics in the curricula, and principles of designing systems. I immediately see the benefits of CT for discovering relationships between graphical variables, such as distance, velocity, and acceleration in kinematics.
CT and scientific modeling can benefit students in various ways, including lowering the threshold for learning by using intuitive CT, representing core scientific ideas, developing key graphing concepts, and teaching programming more easily.
Various worlds that work to implement CT into STEM thinking include the construction, enactment, and envisionment worlds.
Computational Thinking in K-12: A Review of the State of the Field
Grover and Pea demonstrate the seven big ideas of CT include computing is a creative human activity, abstraction reduces information and detail to focus on relevant concepts, information facilitates the creation of knowledge, algorithms are tools to develop and express solutions to problems, programming is a creative process, digital devices foster computation, and computing enables innovation in other fields.
Curricula focuses on including aspects of CT such as abstraction and generalizing patterns, processing information, representing symbols, using algorithms to depict control flow, modularizing by decomposing problems, recursive thinking, conditional logic, and debugging. These skills are vital not only to those in computer science fields but also for all learners.
As a future teacher, I see the connections that are vital to create using CT. Like we've mentioned in class, CT can help us visualize long processes such as evolution or micro-processes such as DNA replication. In this way, CT is vital. However, I'm curious what limitations CT has in the classroom, besides lacking resources like computers.