Table 2 Grounded collaborative analysis with codes, descriptors, and examples

Reflective, comparative data analysis (65, 50%)

During analysis, teachers were comparative to identify areas of strength and weakness.

(1) So, if one, or as a group, one class is successful, and one is not as strong. Or if across all classrooms there is an error, you can address what is wrong, go back to a reteach, or try to scaffold it with instruction throughout the next unit (Pam, interview).

(2) I think it’s very important to see what teachers are strong at, and what other teachers, aren’t. [Then you are] able to ask, ‘well how did you teach that?’ (Hermione, interview).

(3) We are not looking at just the way that the data is laid out we’re not looking individually at how each teacher did. You did a good and you did it bad, it’s more like, it’s like what do we need to do to bring that teak percentage up (Hermione, interview).

Multi-faceted view of data (28, 22%)

Teachers used overall, standards-based, and item performance in their analysis.

(4) I … look at overall standards performance. And then I do look at individual students. And if there is like a big problem with one of the standards, then I will ask her [points to Hermione’s classroom next door] (Katie, interview).

(5) I look at the class, at their grades. Then I look at each class by assessment item to decide which items were most missed. Then I look at, what choices they made. Like, did everyone choose this answer as the wrong one, or is it more erratic with the distractors. So, I start with each class, then break it down by individual question. Um, then break down classes by Pre-AP and Aca[demic] (Tina, interview).

Collaborative DBDM (22, 17%)

Collaborative analysis to provide multiple perspectives on data.

(6) I think [data analysis] … without collaboration cannot truly be successful. I can look at data across all 8th grade teachers, [but] I only get to see one side of the data because I cannot see what is going on in the classroom…Without collaboration we would not be able to see that. We would only have one side and be partially successful (Pam, focus-group interview)

Application of historical data (14, 11%)

Teachers relied on historical data to determine effective and ineffective teaching strategies.

(7) Teachers look at past years lesson plans to determine how teaching and assessment align. For standards with high performance, they stick to what has been done in the past, with minor adjustments based on current needs. For standards with low performance, adjustments to activities are made to better address students

(PLC observation).

(8) The teachers look at historical trends from state and district assessments to find areas of strength and weakness to help tailor their review time for the upcoming state assessment (PLC observation)

(9) Teachers are viewing different data sources in this PLC. First, they look at historical data curated by district personnel. This is an excel workbook that shows student performance by standard on state assessments 2016–2019 (2020 state assessments were cancelled due to COVID 19) (PLC observation).