Mapping a clear path through the Common Core Standards for educational leaders, teachers, parents and students.
COVID-19 has disrupted learning across the country. While some schools have implemented online learning, online learning is not universally accessible to all students.
Due to this disruption, many students will not be prepared for the next school year, or the year after next, when students are expected to build on learning outcomes they would have learned during this time.
At the MIT Mapping Lab, we have applied our network modeling methodologies to the Common Core Standards to generate dynamic maps to be used for lesson planning, helping disadvantaged students learn and for curriculum re-organization.
For Teachers
Pinpoint why students are struggling and specific ways to help them address gaps →
For Parents and Students
Target specific learning outcomes and find specific resources to help you learn →
For Educational Leadership
See inter-grade connections and the big-picture impact across all grades →
The analysis here is based on an example syllabus from Cambridge Public Schools grade 6, but as school days do not vary widely, the analysis largely applies to all schools implementing the Common Core.
17
Direct Micro-outcomes impacted
52
Downstream Micro-outcomes impacted
7
Grades impacted
For a student who is currently in Grade 6, this student will have 17 Micro-outcomes disrupted during the 2020 school year. Further on, the student will continue to have 52 Micro-outcomes disrupted as a result from Grades 7 through the end of high school.
The Common Core Math Standards consist of “Standards” (see Common Core Math) organized by grade bands K – High school. These Standards are statements that describe what a student should be able to do. States that have implemented the Common Core have designed syllabi that cover a grade band's Standards as a student progresses through a school year.
As a first step, for each Standard, we examined whether or not we could break them down into more fine-grained learning statements. These entities we call Micro-outcomes. For example:
Know the formulas for the area and circumference of a circle and use them to solve problems; give an informal derivation of the relationship between the circumference and area of a circle.
State the formulas for the area and circumference of a circle.
Use formulas for the area and circumference of a circle to solve problems.
Give an informal derivation of the relationship between the circumference and area of a circle.
Breaking up Standards in this way enable us to draw meaningful relationships between entities. For example, we can now meaningfully and precisely say that: State the formulas for the area and circumference of a circle is a prerequisite to Use formulas for the area and circumference of a circle to solve problems.
This lets us make a much more precise map of learning without loss of validation — these are still the original Standards, but chunked into more fine-grained statements.
Next, we drew has-prerequisite-of relationships between Micro-outcomes. This determination of whether or not a certain Micro-outcome requires another is a decision made by our subject matter experts.
This process results in a graph (or network) structure that is very powerful for analytics. Because of this network modeling, we're able to perform analyses quickly and use the data in many different applications.
More detail on modeling, the decision-making process of drawing relationships and analytics methodology is given in our paper, but we'll forego detail here in this overview.
For Teachers
Pinpoint why students are struggling and specific ways to help them address gaps →
For Parents and Students
Target specific learning outcomes and find specific resources to help you learn →
For Educational Leadership
See inter-grade connections and the big-picture impact across all grades →