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Project Page Data Driven Instruction


Intent of Project

The intent of this project is for teachers to learn how to analyze student data. Data driven instruction is an important process being implemented now more than ever. It is vital that teachers look at more than just a number grade. Rather, it is vital that teachers look at what a student learned, what they didn't learn, how does the teacher know, and what the teacher can do to fix that. Looking at data is a complex process that cannot be simply defined in this course, but a general view of the process is given for educators to begin the data cycle.

Needs Analysis

1. Instructional problem: The need for an educator to walk through the data cycle to effectively inform their teachings resulting in student learning. The common attitude with the several mandates is to simply cover the material rather than fully learn and understand the content.

2. The nature of what is to be learned: Educators will know how to work with the several types of data that can be used to inform their instruction. As a result, the curriculum and instruction will result in all students learning and achieving.

3. About the learners: Workshop participants are pre-service educators, practicing educators, administrators, and data coaches. The partipants will come from any discipline due to the generalization of the content. Many will have prior teaching experience and be able to apply the workshop into their own practice in real time. Furtermore, the participants will be seeking this course due to their external or intrinsic motivation.

4. Instructional context: This mini course will occur in a hybrid format due to the collaborative nature of the data cycle. The instruction will occur in the online environment, but the collaboration will occur in a person to person format with other teachers and professionals. There will be opportunities to follow the data cycle individually, but the data cycle becomes less effective.

5. Explore instructional problem/solution: The learner will have several opportunities to learn, practice, and reflect on the data cycle and instruction throughout the course. The course will also provide teachers and administrators to effective use their learning in their own classroom.

6. Generate goals: For the learner to learn about the data cycle, what data are effective, how to use their own student data in their own classroom, and generate a plan to ensure all student learning.


Performance Objectives

  • The learner will classify data driven instruction in relation to their specific instructional content and level.
  • The learner will demonstrate finding data that is relevant to the data cycle.
  • The learner will demonstrate data analysis of learner's strengths, weaknesses, and needs in whole groups, small groups, or an individual basis.

Task Analysis

Course Purpose


As a result of participating in this workshop, educators will gain an understanding of the data cycle to inform them of student needs. As a result, educators will generate a plan to meet student's needs in whole group, small group, and on an individual basic in conjunction with the classroom curriculum.

Learning Outcomes


Upon completion of this course, participants will be able to:

  • The learner will classify data driven instruction in relation to their specific instructional content and level.
  • The learner will demonstrate charting data.
  • The learner will demonstrate data analysis of learner's strengths, weaknesses, and needs in whole groups, small groups, or an individual basis.


Prerequisite Skills

  • Be a teacher!
  • Discriminate content areas and content levels.
  • Demonstrates creating graphs and spreadsheets.

Curriculum Map

Please click on the link to view the Instructional Curriculum Map.

Curriculum Map

Resources and References

Bambrick-Santoyo, P. (2010) Driven by data: A practical guide to improve instruction. San Francisco, CA: Jossey-Bass.

Bambrick-Santoyo, P. (2012) Leverage leadership: A practical guide to building exceptional schools. San Francisco, CA: Jossey-Bass.

Bambrick-Santoyo, P. (2013) Proceedings from Leadership for Educational Achievement Foundation: Data Driven Instruction. Albany, NY.

Data analysis [Online image]. (2011). Retrieved May 8, 2013 from http://infolytics.wordpress.com/category/data-analysis/

Dufour, R., & Marzano, R. J. (2011) Leaders of learning. Bloomington, IN: Solution Tree Press.

Gagne, R. M., Wager, W. W., Golas, K. C., & Keller, J. M. (2005) Principles of instructional design. Belmont, CA: Wadsworth, Cengage Learning.

Love, N., Stiles, K. E., Mundry, S, & DiRanna K. (2008) The data coach’s guide to improving learning for all students. Thousand Oaks, CA: Corwin Press.