In this session, we will consider how data use in schools has evolved, as well as an overview of the skills needed to use data effectively in the classroom. We will also start building our understanding of data types, collection, and organization.
Please complete these prior to our first meeting.
We will use the skills list in the article below to organize our learning throughout the course. As you read, think about which skills you have and which ones you would like to build experience with.
- Mandinach, E. B., & Gummer, E. S. (2016). What does it mean for teachers to be data literate: Laying out the skills, knowledge, and dispositions. Teaching and Teacher Education, 60, 366-376.
Nearly all of you have placements in districts that use the Danielson Framework to evaluate teachers. The indicators below are the ones which speak directly to data use.
- Danielson 1f - Using student assessments
- Danielson 3d - Using assessment in instruction
- Danielson 4b - Maintaining accurate records
- Welcome and introductions
- Data viz critique
- Effective data use in schools: past, present, and future
- Tabletop data: Paper spreadsheet
We are going to practice opportunities to capture data, then share what we learn. Select one of the options from Observe, Collect, Draw! below to complete. Printed copies will also be provided at our first meeting. Students who are auditing the course are not required to complete this assignment. Bring the completed assignment with you to the second class meeting (Wednesday, February 19).
- For this assignment, focus on the process and not the product. This means that you want to be aware of your thinking as you try to either capture elements from your day or from a shelf of books.
- You do not have to create a visual strictly according to the directions. It's okay to just use pencil and scratch paper or other materials. The goal here is to recognize and represent different elements of everyday things. Building this "muscle" will help you in your classroom work as you try to notice student behaviors, document learning spaces, or looking for patterns in conversations.
My Books | Balancing My Schedule
The articles below are not required reading. They are included here as reference only.
Datnow, A., & Hubbard, L. (2016). Teacher capacity for and beliefs about data-driven decision making: A literature review of international research. Journal of Educational Change, 17(1), 7-28.
Farrell, C. C., & Marsh, J. A. (2016). Contributing conditions: A qualitative comparative analysis of teachers’ instructional responses to data. Teaching and Teacher Education, 60, 398-412.
Hoogland, I., Schildkamp, K., van der Kleij, F., Heitink, M., Kippers, W., Veldkamp, B., & Dijkstra, A. M. (2016). Prerequisites for data-based decision making in the classroom: Research evidence and practical illustrations. Teaching and teacher education, 60, 377-386.
Mandinach, E. B., & Jimerson, J. B. (2016). Teachers learning how to use data: A synthesis of the issues and what is known. Teaching and Teacher Education, 60, 452-457.
Park, V., Daly, A. J., & Guerra, A. W. (2013). Strategic framing: How leaders craft the meaning of data use for equity and learning. Educational Policy, 27(4), 645-675.
Schildkamp, K., & Kuiper, W. (2010). Data-informed curriculum reform: Which data, what purposes, and promoting and hindering factors. Teaching and teacher education, 26(3), 482-496.
Vanlommel, K., Vanhoof, J., & Van Petegem, P. (2016). Data use by teachers: The impact of motivation, decision-making style, supportive relationships and reflective capacity. Educational Studies, 42(1), 36-53.
Zadra, J. R., & Clore, G. L. (2011). Emotion and perception: The role of affective information. Wiley interdisciplinary reviews: cognitive science, 2(6), 676-685.