Welcome to CommonLit Formative Insights! This article lays out some quick tips for how to get started finding key insights about teacher and student usage within CommonLit.
Track Usage Over Time
View the Assignments Due by Week chart at the district or school level to get a sense for how many assignments are being created, on average, per week. Do spikes at particular times correspond to expected curriculum plans?
Are assignments being created with Guided Reading Mode the majority of the time? Has there been a change in the trend of the percentage of weekly assignments created with Guided Reading Mode? If you do notice a recent uptick or downtrend in assignments with Guided Reading Mode, use your date range filter to determine whether this change in assigning with Guided Reading Mode affected overall scores for that date range.
Compare Assignments by Genre
Compare the literary average and informational average for your school or district during your determined date range. Scroll down to the Most Assigned Texts tables and see if one genre - literary or informational - is being assigned to more students than the other. Here, you can draw connections between whether a high or low average can be attributed to more or less exposure to that genre.
Within a genre, determine if students are being assigned passages that are appropriate for their grade level, or across a wide range of grades and Lexiles. When you drill down to the teacher level, you can more accurately determine whether specific teachers are assigning texts at an appropriate levels.
At the teacher, class, and student level, you can determine whether more exposure to one genre leads to increases in literary or informational standard averages.
Review Your Most Active Teachers
Use the Educators table at the school or district level to discover which teachers are creating the most assignments. Which of your top assigning teachers have the highest and lowest average scores. You can filter by these teachers to learn more about their assignments, scores, and standards-level data.