Data Snapshots
Data for Educators
Collaborative teams engage in professional learning when they focus on the results of their own efforts.
In a professional learning community, data from team-developed common formative assessments (CFAs) serve as the linchpins of success for PLC success in positively impacting student achievement and learning.
In PLC groups that do not have formative assessments in common, examining student work is another powerful way to engage in professional learning to impact students' results. Content is not always need to be common if learning is the focus.
In a professional learning community, data from team-developed common formative assessments (CFAs) serve as the linchpins of success for PLC success in positively impacting student achievement and learning.
In PLC groups that do not have formative assessments in common, examining student work is another powerful way to engage in professional learning to impact students' results. Content is not always need to be common if learning is the focus.
The Challenge of Time
Too often, teams are bogged down by data: the data set is too big, the opportunities for gathering the data are too sparse (just one or two common assessments in a quarter), the organization of the data is too time-consuming, the meeting time to discuss the results is too short, etc. For these many reasons, teams often confess they spend more time planning their efforts than examining the results of their efforts.
Planning isn’t bad; it just isn’t sufficient in a professional learning community. Healthy and productive teams always examine the impact of their best-laid plans.
Planning isn’t bad; it just isn’t sufficient in a professional learning community. Healthy and productive teams always examine the impact of their best-laid plans.
What is an Answer to the Challenge of Time? Data in Smaller Doses.
As an alternative, try having data moments in every meeting rather than just awaiting the more formal but infrequent data meetings. Bring small sample sizes of data or even single artifacts of student work to explore together during the first five minutes of your meeting time.
Significant conversations and meaningful next steps can happen during data moments as teams explore questions such as the following:
Significant conversations and meaningful next steps can happen during data moments as teams explore questions such as the following:
Alternative #1--Data Snapshots with Single Artifacts
- What score(s) would we give this student based on this work? Do we have inter-rater reliability? If not, what could we do to become more consistent?
- What are the students’ strengths? Has the student demonstrated growth over time (e.g. from earlier indications with prior assessments)?
- What are the students’ opportunities for growth?
- What instruction have we planned and/or delivered that should have addressed the challenges this student is still facing?
- What could we still do to help this student move forward?
- Do we have the right criteria? The right performance descriptors?
- Is there anything we should change about our assessments and attending tools (rubrics, scales, scoring guides, etc.)?
PLC Teacher Examples Shared with Single Artifacts:
- Student graphic organizer
- Student notes
- Answer to warm up questions / Collin's / essay questions
- Student projects
- Homework papers
- Any formative assessment
- Worksheet
- Student reflection
- Study guide
- KLQ (key lesson question) response
- Pre-test
- Classwork
- Quiz
- Essay answer
- Lab report
- Canvas discussion
- Exit ticket
- Kahoot / Quizziz / Socrative results
- Nearpod results
- Group poster
- Writing sample / journal
- Group poster
- Quizlets
- ExploreLearning Assessments
- Writing a sentence / Picture with a Caption / a Meme
- Student project
- Test
- Discussion post response
- Screencast
- Lab
- Graph
- Padlet post
- Ticket out the door
- Flocabulary
Alternative #2--Data Snapshots with Small Sample Sizes
- What score(s) would we give these students based on the provided work? Do we have inter-rater reliability?
- What has everyone mastered within the sample size?
- What errors and misconceptions are evident in the sample size?
- Based on our collective expertise, is this sample of evidence representative of the larger group? If so, how do we know? If not, what additional evidence might we need to bring to the table at the next meeting?
- Are there artifacts in the sample set that we could use anonymously in our individual classrooms (use anonymous work from someone else’s classroom to avoid exposing your own students) to help students understand strong and weak work?
- How else could we use these few artifacts to help all of our students improve?
- What program improvements (curriculum, instruction, and assessment) do the samples suggest we might need to consider?
- What are plausible next steps for the students represented here, and would those next steps be beneficial to the larger group as well?
PLC Teacher Examples Shared for Small Sample Sizes:
- KLQ (Key Lesson Questions)
- Exit slip
- Kahoot
- Quizizz
- Response sheet
- Canvas quiz
- Viewing classwork
- Canvas discussion
- Student response
- Collins writing prompt (Type 1 or Type 2)
- Short response writing
- Test analysis (single question)
- Homework
- Warm ups
- Smiley quiz
- Ask some kids a question
- Whiteboards
- Data table for just one class
- "Is...Is not"
- GoFormative
- Interactive notebooks
- Warm Up ("Daily Buzz")
- KWL
- 3-2-1
- Quizizz
Technology
There are many ways that teachers might use technology to gather class data.
- Quizizz
- Canvas quizzes
- Kahoot
- Google Forms
- Quizlet
- Answer Garden
- Socrative
- Flocabulary Quiz
- Class Dojo
- Active Engage
- Apple Classroom
- Common Lit
- Flipgrid
- Google Docs
- Padlet
- Purpose Games
- Nearpod
- Khan
- Canvas
- GoFormative to analyze questions, strengths, or needs of individuals, class, or team
- Explore Learning Assessment Questions
- Grade Hound
- Quizlet Live
- Quizlet teacher data
- Educreations
- Edpuzzle
- ExploreLearning Assessments
- Google Clasroom Check Ins
- Common Lit
It’s surprising how much a team can learn after five short minutes of examining data evidence and artifacts. When teams become experienced with data snapshots, they can be more adept in data meetings.
A steady stream of data snapshots can provide more focus and clarity for a team’s planning efforts in the rest of the team meeting.
A steady stream of data snapshots can provide more focus and clarity for a team’s planning efforts in the rest of the team meeting.