Dwayne Brathwaite

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Back to home Dwayne Brathwaite

Project home Data analysis for differentiated instruction

ETAP 623 Spring 2009

Intent of Project

Data analysis for differentiated instruction

The intent of this course is to show educators how to effectively take student data and turn it into useful instruction for each student.

Topics that will be covered:

  • Purpose and benefits of differentiated instruction
  • Identifying useful data
  • How computerized models can help data analysis
  • How data analysis can be done by hand
  • Applying data analysis to instruction

Needs Analysis for Data Analysis for Differentiated Instruction

1. Problem: Learners in each teacher's classroom come in a variety of forms. Some students have mastered skills with which others struggle and no student has mastered every skill given. Therefore, teachers need to identify the skills for practice of each student in order to give each student the best possible education. This course will help teachers find ways to analyze data from their students to provide beneficial differentiated instruction.

2. What is to be learned: Learners will become familiar with ways to effectively analyze data from student work. This analysis can assist teachers in knowing how to differentiate instruction for each student or groups of students.

3. The Learners: The learners will be teachers of any level, elementary through college, that need knowledge in how to begin differentiating instruction. Many teachers today need to prepare students for state and standardized assessments. If teachers know what skills each individual student has mastered and needs to practice, they can provide the necessary instruction and possibly increase testing scores.

4. Instructional Context: Most activities in this course will occur online and by the individual. Computerized data analysis models and models that can be performed by hand will be discussed so learners can choose which works best for their teaching situation.

5. Exploring the problem and solution: Learners will have a chance to learn, practice, and reflect on course activities. Learners will explore why data analysis is an important step to differentiating instruction and how it can work for their classrooms.

6. Goals: For teachers to learn more about their individual students to offer the best possible education to them and for teachers to feel comfortable employing new ways of looking at student data.

Performance Objectives

  • Learners will be able to identify the meaning, goals, and construction of differentiated instruction.
  • Learners will be able to identify useful data to analyze for implementation into differentiated instruction lessons to increase student scores on assessments.
  • Learners will be able to analyze identified student data, using related computer programs for data analysis when needed.
  • Learners will be able to design and choose to use appropriate differentiated instruction activities in response to data analysis results.

Task Analysis

Course Purpose

The purpose of this course is to help teachers feel more confident in their ability to analyze assessment data from students in order to provide better individualized differentiated instruction.

Learning Outcomes

  • At the conclusion of this course, students will be able to:
    • State the meaning of differentiated instruction
    • Identify data useful to analyze
    • Explain how computer programs can be useful for data analysis
    • Perform at least one method of data analysis by hand
    • Interpret analysis for appropriate application to classroom instruction
    • State examples of differentiated instruction that can be used in response to data analysis
    • Understand the benefits of differentiated instruction

Prerequisite Skills

Essential Prerequisites

  • In order to reach outcomes, students must know/learn to:
    • Understand what differentiated instruction is
    • Determine the learning problem and purpose for data analysis
    • Understand how to use different methods of data analysis
    • Apply results of data analysis to creating differentiated learning materials for instruction

Supportive Prerequisites

  • For easier access to reaching outcomes, students should:
    • Be open to learning about and using DI in the classroom
    • Understand the purposes of state assessments
    • Be open to the experience of analyzing data
    • Know trends in content and have deep understanding of content standards
    • Be open to discussing ideas with others
    • Be open to self-reflection

Curriculum Map

Take a look at the curriculum map for this course Media:Cb_icm.pdf‎

Resources and References

Carolan, J. and Guinn, A. (2007). Differentiation: Lessons from master teachers. Educational Leadership, 64 (5), 44-47.

Celebrate Your Smarts png. London District Catholic School Board 2006.

Colorful ducks (pic) mrhamada.edublogs.org

DI tools (pic) www.education-world.com

Kaufeldt, M. (2005). Teachers, Change Your Bait! Brain-compatible differentiated instruction. Crown House Publishing Ltd.: Bethel, Connecticut.

Levy, H. M. (2008). Meeting the needs of all students through differentiated instruction: Helping every child reach and exceed standards. The Clearing House, 81 (4), 161-164.

Reed, S.L. (2006). Hooked on Data: The Classroom Teacher’s Guide to Making Data Analysis Easy. The MASTER Teacher, Inc.; Manhattan, KS.

Ysseldyke, J., Spicuzza, R. , Kosciolek, S., Teelucksingh, E., Boys, C., & Lemkuil, A. (2003). Using a curriculum-based instructional management system to enhance math achievement in urban schools. Journal of Education for Students Placed At Risk, * (2), 247-265.

Back to home Colleen Bryla

Project home Data analysis for differentiated instruction

ETAP 623 Spring 2009