The educator guides students through iteratively creating and evaluating a computational model by comparing it with a phenomenon the student is studying.
Computational models are simulations that recreate the behavior of systems of interrelated parts. A system is any group of things which affect each other, such as plants and animals in a food web, parts of a machine, or images in a poem. Because systems often have relationships between many different parts, they are hard to think about intuitively and their behavior is hard to predict with simple equations. Small changes in specific parts of a system can have surprising effects through the whole system. Computational tools are well-suited for creating models because they work in a reliable, repeatable fashion.
Creating a computational model—for example, with a computer simulation environment, a programming language, or a robotics kit—is an effective way to simulate a system quickly and reliably, but you may even design an “unplugged” simulation for students to physically act out a repeated process to recreate the behavior of the system. When students use computational models to make predictions about the behavior of systems, they can develop and test their own intuitions for how real-world systems work. (“Understanding systems with computational models” is focused on helping students construct understandings from computational models of systems.)
The predictions of a reliable computational model should match what happens in the real world. When students create computational models, they often begin with hypotheses about how real-world systems work, defining rules either for the system as a whole or for how individual participants in the system should behave. The process of improving a model is an iterative cycle of comparing its behavior with the real world, making a hypothesis to account for mismatches, and then making changes to the model. Through this process, students develop systematic understandings of the real-world systems they are modeling and can generate questions for further investigation.
To earn the micro-credential, you must earn a “passing” evaluation for Parts 1 and 3, and a “Yes” for each component of Part 2. In the assessment of this micro-credential, an educator will plan and teach a lesson in which students iteratively develop a computational model of a real-world system. The educator will analyze student learning in the lesson and reflect on the lesson’s successes and limitations. The three parts of the assessment should fit together as evidence of professional reflective practice.
(200-word limit total)
Please answer the following questions:
To earn this micro-credential, please submit the following:
1) Student artifacts
Submit one or more artifacts documenting students’ iterative processes of developing a computational model. These artifacts should reflect the work of two students (or two student groups). They may include a video recording, the teacher’s or another colleague’s observation notes, a student’s journal, screenshots, or other artifacts which show the development of the students’ models.
2) Analysis of student artifacts
(800-word limit total)
As you answer the following questions, refer to specific evidence from the artifacts submitted.
Note: If students worked in groups, you may choose to analyze one student’s learning within each group, or to analyze the learning of the groups as wholes.
(300-word limit total)
Please submit a reflection that addresses the following guiding questions: