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Data Driven Small Learning Communities Richard D. Jones Senior Consultant.

Jan 19, 2018

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Data Driven Small Learning Communities Richard D. Jones Senior Consultant
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Data Driven Small Learning Communities Richard D. Jones Senior Consultant Personality Data Driven Small Learning Communities Richard D. Jones Senior Consultant Bigger isnt always better! Learning is about constructing relationships in which students connect with teachers or subjects. Small schools foster the personalization strategies to support those relationships. Tom VanderArk Why Consider Small Learning Communities? Academic Achievement Social Benefits Attendance and Graduation Rates Safety and Discipline Preparation for High Education Extracurricular Participation Financial Benefits Bringing Best Practices to Scale 1. Small Learning Communities 2. High Expectations 3. 9 th Grade th Grade 6. Curriculum 5. Data 7. Relationships / Reflective Thought 8. Professional Development 9. Leadership Do Small Learning Communities Make a Difference? Increased Attendance Increased Student Achievement Increased Student Participation Increased Student and Parent Satisfaction Increased Positive Student Behavior Greater Focus on Students Interests and Aptitudes Relevancy Leads to High Achievement Smaller Strategies Elementary Reduced Class Size Looping Multi-age Groupings Expanded Use of Adults Learning Centers Differentiated Instruction Smaller Strategies Secondary Schools-within-Schools House Plans Freshman Academy Magnet Schools Career Academies Characteristics Improved Knowledge of Student Needs Longer Term Relationships Personalization of Learning Stronger Instructional Focus Shared Sense of Accountability Rigorous and Relevant Learning Rigor Relevance My only skill is taking tests. All Students Creating Small Learning Communities Driven by Data Improving Student Achievement What are the biggest issues for teachers? Work Harder ? Work Smarter? Why? Changing Nature of Work Why ? Accelerating Technology Employment 1970s High Skill Low Skill Employment 1990s High Skill Semi Skill Low Skill Employment 2010 High Skill Semi Skill Low Skill 1970s 1990s 2010 Translating Standards Into Teaching and Learning Why? Standards Destination vs. Route vs. Vehicle Standards Standards vs. Curriculum vs. Student Work An Overcrowded Curriculum Why? Needed Time McREL 15,465 Hours Available Time 9,042Hours Teachers struggling to teach an overloaded curriculum! Focus on Student Learning Why? Teaching VS. Learning Expectations Standards Tool For School Alignment Why ? Language Arts Need S tandards H M L Language Arts NeedTest Standards HH or L MM LL Language Arts NeedTestInstruction Standards HH or LL MML - M LLM - H Alignment for Improving Instruction Standards State Requirements Instructional Resources Teacher Materials Content Assessment Accountability Instruction Courses and Programs Alignment for Improving Instruction Standards State Requirements Instructional Resources Teacher Materials Content Assessment Accountability Instruction Courses and Programs Explaining Whats Important Why ? Ask Me..... How will I ever use what Im learning today? In schools the status quo persists! Why ? Prepare for THE test? New SAT More Application New Writing Section Expand Critical Reading for Information More Achievement Base on three years of Math Higher Level Math Skills Less Aptitude Eliminate analogies Eliminate simple math reasoning NYS Math A Question June 2003 NYS Math A Question June 2002 Increase Student Motivation Why ? Why SLCs and Data Driven? Changing Nature of Work Translating Standards into Teaching Reduce Overcrowded Curriculum Way to Focus on Student Learning Tool for School Alignment Explain What is Important Prepare for THE test Increase Student Motivation What data do teachers use when deciding what to teach ? Use of Data Data Rich but Analysis Poor Types of Data Curriculum Demographics Student Learning School Processes Perceptions of Quality Types of Data Example Type of DataLiteracy Curriculum Demographics Student LearningPerformance on State Test Processes Perceptions of Quality Types of Data Example Type of DataLiteracy CurriculumLevel of Reading Comprehension on State Test Real World Postsecondary Learning DemographicsIncoming Student Reading Levels Student LearningPerformance on State Test Local Assessment ProcessesReading Levels of Textbooks Teaching Materials Success of Reading Practices Perceptions of QualityStudent Surveys Relationships Clearly Important ? How to Quantify? How to Develop? Relationships are Essential to Student Learning Family Peers Teachers Community Result of combination of support from: Relationship Model 0.Isolated 1.Knowing 2.Assisting 3.Mentoring 4.Enduring 5.Mutually Beneficial Everyone needs support when they take new risks Relationship Model Key to Student Learning 1. Knowing Teachers get to know students and their families 2. Assisting Some positive support, but sporadic 3. Mentoring Moderate support from some individuals 4. Enduring Fully supported from all individuals 5. Mutually Beneficial Mutually supportive learning community Support Behaviors Respect Being There Active Listening Frequent Contact Encouragement Avoiding Put Downs ?????? Experience and research make it very clear that school size does matter-- but they also make it clear that small is no silver bullet Michelle Fine and Janice Somerville Beginning to Use Data Ask Questions and Analyze Avoid Snap Judgments Collect Data to Answer Questions Set Goals Using Data Staying on the Cutting Edge Cutting Edge NYS Staff Development Council Further InformationOr