ensuring quality instruction through data collection, analysis, and reflection

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at the Mitchell Institute 22 Monument Square, Suite 404 Portland, Maine 04101 GreatSchoolsPartnership.org

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at the Mitchell Institute 22 Monument Square, Suite 404 Portland, Maine 04101 GreatSchoolsPartnership.org. Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection. Presenters Duke Albanese & David Ruff Co-Executive Directors Great Schools Partnership. - PowerPoint PPT Presentation

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Page 1: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

at the Mitchell Institute22 Monument Square, Suite 404Portland, Maine 04101GreatSchoolsPartnership.org

Page 2: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Presenters

Duke Albanese & David Ruff Co-Executive Directors

Great Schools Partnership

September 12, 2007

2007 Education Leaders Conference

Page 3: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Strengthening Today’s Strengthening Today’s SchoolsSchools

for the World of Tomorrowfor the World of Tomorrow

Our VisionAn equitable, academically rigorous,

and personalized public education system that prepares all students for

college, work, and citizenship.

Page 4: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Our MissionIn collaboration with Maine and national

educators, develop, implement, and advocate for high-quality instructional

practice; effective and expanded leadership capacity; and student-

centered organizational design and culture, all built on strong community

connections that lead to the realization of our vision.

Page 5: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Table Conversation

What roadblocks (logistical, financial, cultural, and emotional) hamper the

collection and analysis of data on instructional practice?

What impedes this analysis from impacting teacher beliefs and

practices as well as overall school change?

Page 6: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Concerns We’ve Been Hearing• Traditional evaluation and supervision procedures are

infrequent and disconnected from instructional improvement

• Limited time and capacity to conduct classroom observations

• No collective understanding of the prevailing instructional strategies, patterns, and trends within a school or district

• No “hard” data on classroom instruction• Faculties don’t know where to begin or what to address• Busy schedules and large workloads postpone or

impede instructional improvement• Fear

Page 7: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Better instruction is in your hands.

Page 8: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

The iWalkthrough Tools and Process

• Based on relatively short, but frequent, classroom observations that are collected over time

• Focused on clearly observable characteristics that are tied to improving student achievement and aspirations

• Records, archives, and visually displays data electronically, eliminating paper work and increasing time for thoughtful conversations on instruction

• Establishes credibility and staff buy-in through broad participation in data collection and analysis

• Enables educators to generate detailed, customized reports on individual, departmental, and school-wide instructional patterns and trends

Page 9: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Examples in PracticeSacopee Valley

High School

• Rural high school of 450 students

• 800 observations conducted in 2006-2007

• Principal, assistant principal, and teacher-leaders record and analyze observations as part of their ongoing responsibilities

• Observation process built into faculty expectations

• System in place for regular grade-level analysis

Page 10: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Examples in PracticeOxford Hills Comprehensive

High School

• Rural consolidated high school of 1,250 students from dozens of sending communities

• 700 observations conducted in 2006-2007

• Observations conducted by principal, assistant principal, and grade-level teacher-leaders

• System in place for regular grade-level, multi-grade, and cross-teams analysis

Page 11: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Examples in Practice

• Urban high school of 1,000+ students

• 750 observations conducted in 2006-2007

• All teachers trained to conduct observations

• All teachers are expected to team up with a colleague and complete a series of observations

• System in place for analyzing data within each content area

Page 12: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

• Content Area

• Grade Level

• Class Size

• Visit Time

• Engagement in Learning

• Bloom’s Taxonomy Level

• Class Configuration

• Teacher Interactions

• Student Interactions

• Learning Approaches

• School Choice

• Date of Observation

Observation FormCategories

Page 13: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Coaching/conferencing Facilitating discussion Monitoring One-on-one Posing questions Presenting Independent teacher

work

Teacher InteractionsData Fields

Page 14: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Homepage

Page 15: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection
Page 16: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection
Page 17: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

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Student Engagement and Bloom’s Taxonomy

Page 21: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Table ConversationHow would you interpret these data?

0–50% 51–75% 76–90% 91–100%

Remembering/understanding 8.2% 12.5% 29.3% 49.9%

Applying 2.5% 8.6% 26.0% 62.9%

Analyzing/ evaluation 0.8% 4.1% 22.1% 73.0%

Creating 2.7% 8.1% 19.2% 70.0%

Examining Student Engagement

and Bloom’s Taxonomy

Page 22: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Table Conversation• If these data had been collected in a

school, what strategies and professional development would you use to begin improving the quality of classroom instruction?

• If these data had been collected in your state or district, what policies, strategies, and professional development would you use to begin improving the quality of classroom instruction?

Page 23: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Lessons Learned

• Changing instructional beliefs requires educators having the ability to archive, sort, and compare data from classroom observations on their time table.

• Educators need immediate, real-time data on instruction to influence their practice.

• Educators need practical and targeted information to identify the most important school-wide instructional needs for professional development.

MORE

Page 24: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Lessons Learned

• Growth requires the ability to archive and use data over multiple years.

• Deep understanding of practice requires educators being able to disaggregate observation data by date, content area, grade level, and several other criteria.

• Instructional observation systems need to maximize conversations and focus on bettering instruction rather than on process and data collection.

MORE

Page 25: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Lessons Learned

• Hands-on tools and process encourage more active participation of school administrators in the instructional life of their school, fostering a greater understanding of school-wide curricula, instruction, and assessment.

• Participation by the faculty (more is better) encourages greater investment in and support for instructional improvement.

• When educators can manipulate data to get at the issues that matter most to them, we see more rapid changes in instructional beliefs and practices.

Page 26: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection
Page 27: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

Questions about…

The iWalkthrough process?

How schools have used the tools?

How the system has impacted instructional practices?

What we’ve learned about changing instruction?

Page 28: Ensuring Quality Instruction Through Data Collection, Analysis, and Reflection

at the Mitchell Institute22 Monument Square,

Suite 404Portland, ME 04101207.773.0505Fax 207.773.4044GreatSchoolsPartnership.

org