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Data Analysis Processes: Cause and Effect Linking Data Analysis Processes to Teacher Evaluation Name of School

Data Analysis Processes: Cause and Effect Linking Data Analysis Processes to Teacher Evaluation

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Name of School. Data Analysis Processes: Cause and Effect Linking Data Analysis Processes to Teacher Evaluation. Objectives for Today. Discuss the meaning of cause and effect as it relates to the teacher evaluation system. - PowerPoint PPT Presentation

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Page 1: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Data Analysis Processes:Cause and Effect

Linking Data Analysis Processes to Teacher Evaluation

Name of School

Page 2: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Objectives for Today

• Discuss the meaning of cause and effect as it relates to the teacher evaluation system.

• Understand how an effective data analysis process can determine cause and effect.

Page 3: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Using Cause and Effect Data

Page 4: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

FEAP’s: Practice Indicators Related to Cause and Effect & Data Analysis

Continuous Professional Improvementa. Designs purposeful professional goals to strengthen the

effectiveness of instruction based on students’ needs  b. Examines and uses data-informed research to improve instruction

and student achievement c. Uses a variety of data, independently and in collaboration with

colleagues, to evaluate learning outcomes, adjust planning, and continuously improve the effectiveness of the lessons 

d. Collaborates with the home, school, and larger communities to foster communication and to support student learning and continuous improvement 

e. Engages in targeted professional growth opportunities and reflective practices

 

Page 5: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

1. Instructional Design & Lesson Planning

a. Aligns instruction with state adopted standards at the appropriate level of rigor

b. Sequences lessons and concepts to ensure coherence and required prior knowledge

c. Designs instruction for students to achieve mastery

d. Selects appropriate formative assessments to monitor learning

e. Uses diagnostic student data to plan lessons

f. Develops learning experiences that require students to demonstrate a variety of applicable skills and competencies

FEAP’s: Practice Indicators Related to Cause and Effect & Data Analysis

Page 6: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

State Model (based on Marzano research)

Indicator: Evaluating the Effectiveness of Individual Lessons and UnitsThe teacher determines how effective a lesson or unit of

instruction was in terms of enhancing student achievement and identifies causes of success or difficulty.

Indicator: Evaluating the Effectiveness of Specific Pedagogical Strategies and BehaviorsThe teacher determines the effectiveness of specific

instructional techniques regarding the achievement of subgroups of students and identifies specific reasons for discrepancies.

Domain 3 – Reflecting on Teaching

Page 7: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Danielson Framework

Effective teaching requires both assessment of learning and assessment for learning. Assessments of learning ensure that teachers know that students have achieved the intended outcomes. Assessments for learning enable teachers to incorporate assessments directly into the instruction and to modify or adapt instruction as needed to ensure student understanding. Even though such assessments are used during instruction, teachers must design them during the planning process. Such formative assessment strategies are ongoing, and both teachers and students can use them to monitor progress toward instructional outcomes.

Component: 1f. Designing Student Assessments

Page 8: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Learning Activity 1

How do you define

cause and effect?

Page 9: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Causal Instructional Strategies Key strategies revealed by research to have the highest probability of impacting student learning when used appropriately and in appropriate instructional contexts. These are the controllable actions in a school that impact student learning.

Florida’s Common Language Document

Page 10: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Florida’s Common Language Document

Causal Model of Teacher Evaluation Describes the link between classroom practices and behaviors that have a direct impact on student learning and assigns greater importance in evaluation ratings to factors having the most direct link to student learning (based on contemporary research).

Page 11: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Cause and Effect Data Sets Effect data: Outcomes or

student achievement results

Cause data: Professional practices, actions of adults, that create specific effects or results

Page 12: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Application of Antecedents of Excellence

Resu

lts I

nd

icato

rs

High results, high understanding

Replication of success likely

LosingLow results, low understanding

Replication of mistakes likely

LearningLow results, high understanding

Replication of mistakes unlikely

High results, low understanding

Replication of success unlikely

Leadership and Learning Matrix

LeadingLucky

Cause Data

Eff

ect

Dat

ap. 36-37

Page 13: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Learning Activity 2Think of a student

achievement challenge we wish to conquer.

Place an X in the quadrant that best

describes our status and provide a justification for

the quadrant you selected. Be prepared to share your thinking with

the group in five minutes.

Page 14: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Through effective data collection, teachers and leaders can make the link between actions of adults and results in student achievement data.

Page 15: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Monitor the implementation of a

few strategies that have the greatest

impact on student learning.

Page 16: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Provide timely, specific focused feedback for growth, and allow for

focused practice.

Page 17: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Sept.Oct. Nov. Dec.

Jan. Feb.

Percent of Staff Proficient in Using Nonfiction Writing in Content

Percent of students proficient or higher in Algebra I

Percent of students proficient or higher in reading

Cause and Effect Data

Page 19: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Learning Activity 3

Collecting Cause Data:

Higher Order Questioning Techniques

Page 20: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Collecting cause data on the proficiency and implementation of specific strategies …

…and effect data on student

learning, provides clarity on what works

best.

Page 21: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Data Analysis for Cause & Effect

Collaborative Processes to Improve Teaching

Page 22: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Data Teams are a model for continuous, collaborative action that inspires and empowers professionals to

discover cause and effect relationships.

Page 23: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Data Team meetings are collaborative,

structured, scheduled

meetings that focus on the

effectiveness of teaching and

learning.

Page 24: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Data Teams have a common

focus or common standard, a

common formative

assessment, and a common

scoring guide.

Page 25: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

25

Benefits of Formative Assessments

Clarify

Learning

Intentions

Elicit

Evidence of Learning

Promote

Feedback

Encourage Learners to Own TheirLearning

Page 26: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Formative

What students should know

How instruction needs to be

adjustedHow to

improve student

skills

Assessment FOR learning

Page 27: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Summative

After instruction

occurs

Used when determining

grades

Various audiences for

the data

Assessment OF learning

Page 28: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Remember…

It isn’t the method that determines whether the assessment is summative or formative, it is how the results are used.

Page 29: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Formative assessment is

capable of triggering big

boosts to students’

achievement – the educational

equivalent to the cure for the

common cold.

James Popham, 2010Strategic Priorities for School

Improvement, Harvard Education Letter, No. 6

Page 31: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

The Data Teams Process

Six Steps to Data-Driven Instructional Decisions

Page 32: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

The Data Team Process

1. Collect & Chart Data

2. Analyze & Prioritize

3. Set & Review SMART Goals

4. Select Instructional Strategies

5. Determine Results Indicators

6. Monitor & Evaluate Results

Page 33: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Learning Activity 4

The Data Teams Process

Page 35: Data Analysis Processes: Cause and Effect   Linking Data Analysis Processes to Teacher Evaluation

Questions and Reflection