The educator guides students in working with computational models to develop understandings of systems as wholes and as compositions of subsystems, as well as guides students in understanding the role of agents within systems.
Systems thinking is a way of thinking about the relationships between parts of a system. 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. Two ways to study systems are:
Some of the properties commonly observed and studied in systems include:
Systems and models of systems are an increasingly prevalent form of knowledge in the physical and social sciences. Systems thinking can offer rich new ways of answering questions in every discipline. For example, none of the following questions have straightforward answers. Students could construct systems thinking understandings of the relationships involved. For example:
(See Resources section for lesson examples.)
Computational models are useful for examining the relationships between components within systems. Typically these relationships 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. That’s where a computational model is helpful: it offers a reliable, repeatable way to recreate the behavior of a system. Computational tools are well-suited to modeling systems quickly and reliably—for example, a computer simulation environment, a programming language, or a robotics kit—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. Computational models are excellent for exploring the dynamics of a system. Students can develop understandings of the system as a whole by repeatedly changing parameters. Similarly, students can develop understandings of how individual participants affect a system by changing the rules that simulated participants follow within the model.
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 use a computational model to develop systems thinking understandings, analyze one student's 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.
Please answer the following questions:
To earn this micro-credential, please submit the following:
1) Student artifacts
Submit one or more artifacts of three students’ learning in the lesson. These may include artifacts created by the students, student reflection on the lesson, the educator’s or another colleague’s observation notes, a video recording, or other artifacts which provide evidence of student learning.
2) Analysis of student artifacts
(800-word limit total)
As you answer the following questions, choose one student whose work you submitted and refer to specific evidence from the artifact(s) submitted.
(300-word limit total)
Please submit a reflection that addresses the following guiding questions: