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Anne Bubnic

Continuous Improvement: It Takes More Than Test Scores [Bernhardt] - 0 views

  • Schools in our country hear that data makes the difference in improving student achievement. Not all schools, however, have felt the positive impact from what they believe is data-driven decision making. The most common reason: Most school districts in this country believe they are being data-driven when they have analyzed the dickens out of their state assessment results.
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    Continuous Improvement: It takes more than test scores. Analyzing state assessment results is only the beginning of effective data-driven decision making. There is no question that the passage of No Child Left Behind in 2001 has impacted schools in at least two ways: First and foremost, NCLB has made the use of data to improve student achievement imperative; and second, NCLB has increased the need for continuous improvement processes within schools. Summative data just the beginning
Anne Bubnic

AASA: Using Data To Improve Schools [pdf] - 0 views

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    Using Data to Improve Schools: What's Working is an easy-to-read guide to using data to drive school improvement. School system leaders and their staffs can learn from this book how to build a districtwide culture of inquiry that values the use of data for sound decision-making. School board members, parents and community members interested in helping improve schools will find tools for their work as well in this guide. It describes the challenges and the successes of educators from districts both large and small committed to using data.
Anne Bubnic

The Benefits of Teacher Collaboration [PLC's] - 0 views

  • Researcher Ken Futernick (2007), after surveying 2,000 current and former teachers in California,concluded that teachers felt greater personal satisfaction when they believed in their own efficacy, were involved in decision making, and established strong collegial relationships.
  • School leaders who foster collaboration among novice and veteran teachers can improve teacher retention and teacher satisfaction, according to studies conducted by Susan Kardos and Susan Moore Johnson.
  • n Tennessee, school performance coaches receive specialized training to facilitate improvements in low-performing schools and districts. Helping teachers collaborate in meaningful ways is part of the work.
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  • The researchers suggest that school leaders foster a sense of shared responsibility, engage veteran teachers in the induction of new teachers and in their own professional growth, and earmark resources to support collaborative planning, mentoring, and classroom observations.
  • To determine the relationship between teacher collaboration and student achievement, the researchers used reading and math achievement scores for 2,536 fourth-graders, controlling for school context and student characteristics such as prior achievement. They found a positive relationship between teacher collaboration and differences among schools in mathematics and reading achievement.
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    Teacher collaboration and professional learning communities are frequently mentioned in articles and reports on school improvement. Schools and teachers benefit in a variety of ways when teachers work together. A small but growing body of evidence suggests a positive relationship between teacher collaboration and student achievement.
Anne Bubnic

Teaming for Success in Underperforming Schools - 0 views

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    Like never before, today's classroom teachers routinely are being asked to collaboratively analyze student data, develop or implement new mandated curricula, and assess the effectiveness of these innovations. Ironically, few preservice preparatory or in-service professional development programs actively train classroom instructors in the use of team-based inquiry or collaborative data- driven problem solving. Framed within the context of the literature and governmental efforts to achieve school reform, this article describes one such in-service program, in practice at public and charter schools in high-need communities in New York City. The Inquiry Based School Improvement Program (IBSIP) was created and designed to help schools serving high-need communities in New York City engage in the types of team-based inquiry and data-driven problem solving needed to meet the everchanging institutional demands on these schools to improve.
Anne Bubnic

A Principal's Role in Improving Student Achievement: School Improvement in Maryland - 0 views

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    If our end goal is to improve student achievement to meet AYP, then a critical intermediate goal is to determine where each of our students is in relation to the state content standards. While the logic is clear, most schools do not collect evidence of or for learning on an ongoing basis. We don't know what to teach students to take them to proficiency on indicators/objectives without knowing where they currently are on those indicators/objectives.
Anne Bubnic

Improving Teaching and Learning with Data-Based Decisions - 0 views

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    "Data-based decisions"-the phrase has become a buzzword in education over the last few years. However, it does make sense that using information to help clarify issues, identify alternative solutions to problems, and target resources more effectively will lead to better decisions. The real question should not be whether to integrate the use of data in decision making, but how.Finding good data and using it effectively is actually a complex process-one that many schools and districts are just beginning to address. One specific type of data-based decision making that shows promise for helping schools dramatically increase student achievement is the use of assessment data to drive instructional improvement
Anne Bubnic

NCREL: School Improvement Through Data-Driven Decision Making - 0 views

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    NCREL has gathered a selection of web-based tools for collecting information, ranging from checklists to surveys, and including information about software tools for data collection and analysis. A tutorial provides an overview of the use of data in school improvement; a bibliography and background section are also included.
Anne Bubnic

Accountability That Works - 0 views

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    Teachers understand the importance of accountability and they embrace it. But an accurate and fair school accountability system remains elusive.Accountability has become a 'gotcha game'-designed to blame and punish, rather than to build capacity for improvement. Article describes four pillars of a new system of accountability.
Anne Bubnic

Data Wise: A Step-by-Step Guide to Using Assessment Results to Improve Teaching and Lea... - 0 views

  • The scenarios that illustrate each chapter come from two case studies, one based on a K-8th grade scenario and the other a 9th-12th grade setting. Data Wise grounds its discussion in examples from those contexts, keeping the material accessible and focused on realistic problems and solutions. Data Wise's process depends on collaboration and full faculty participation. With a sympathetic understanding of the inevitable limits on staff time, the authors discuss the best ways to structure collaborative faculty time and include three protocols to involve faculty and staff in gaining insight from data.
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    Demystify that data! A powerful asset to data driven inquiry and improvement, Data Wise comes out of a work group of Boston Public School leaders and Harvard Graduate School of Education faculty and doctoral students and is informed by the development of a data system now used by all Boston Public Schools. Data Wise guides schools and school systems through the growth of comprehensive data systems that encompass classroom work samples as well as standardized tests.
Anne Bubnic

State's schools improve, achievement gap persists - 0 views

  • But the good news came paired with bad as state Superintendent of Public Instruction Jack O'Connell declared that the education of African American students has reached a crisis stage. Scores of that group remained well below those of white and Asian American students, he said, while black students' English skills generally match those of Latino students - many of whom are just learning the language.
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    The state's public school students improved in reading, writing and mathematics this year, marking five years of near-steady growth on the tough California Standards Test, results released Thursday show.
Anne Bubnic

Leading Your School Through School Improvement: A Principal's Role - 0 views

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    Analyzing your data is a process you will want to involve your entire staff. There are a number of variables that will help you determine the best strategy for your school including the size of staff, organization of teams, availability of computers with Internet, and the amount of staff meeting time. The critical piece is that you model the importance of data analysis and that you involve (mandate) all staff in the process. The odds of teachers making the instructional changes needed for improved student achievement are much greater when the data and what it tells them about current achievement.
shoaibhashmi

Razer Surround Pro 2.0 Crack & Activation Key Full Free - 0 views

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    Razer Surround Pro 2.0 Crack & Activation Key is an professionally & improved no doubt agreed 7.1 virtual surround sound engine that is great new feature in
Anne Bubnic

How are Educators Using Data? [MCREL Report] - 0 views

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    A Comparative Analysis of Superintendent, Principal, and Teachers' Perceptions of Accountability Systems. The purpose of this technical report is to develop a better understanding of the assessment and accountability practices and policies that educators are implementing in the classrooms, schools, and districts and to examine whether those policies are associated with perceived school and student improvements in achievement.\n\nThe study provides descriptive information about the need for schools and districts to effectively use data, how schools and districts use data to guide classroom practice, and the difference in data use based on the level of student proficiency in individual schools.
Anne Bubnic

NSBA links: Data-Driven Decision Making - 0 views

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    Increasingly, school board members from around the country are using data to help make good decisions about improving public education for all children. As school districts across the country grapple with how to think systemically and strategically about reaching student achievement goals and forging creative solutions from standardized test data, data-driven decision making can be used to inform board decisions.
Anne Bubnic

Program Improvement (PI) Training Materials - Virtual Library - 0 views

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    From the California Department of Education
Anne Bubnic

High Schools That Work - 0 views

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    The HSTW Assessment, administered to seniors, is used by HSTW states, districts and schools to document school improvement efforts. It is comprised of three subject tests (reading, mathematics and science) coupled with a student survey. This assessment provides comprehensive school-level data that disaggregate students' achievement by their perceptions of school and classroom experiences. These results have given schools, districts and states a unique opportunity to determine what is and is not working to increase student achievement. The assessment is administered by all HSTW sites in even-numbered years.
Anne Bubnic

Data Intersections [Victoria Bernhardt] - 0 views

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    Journal of Staff Development. New routes open when one type of data crosses another. As educators become more familiar with collecting and interpreting school data, they can begin "running data at each other," framing questions that require analysis of multiple types of information. Educators can cross two, three, and four categories of data in ways that can provide new insight into student learning and how to improve it.
Anne Bubnic

Data done right - 0 views

  • This is the NCLB model. Schools are expected to collect data once a year, slice and dice them in various ways, set some goals based on the analyses, do some things differently, and then wait another whole year to see if their efforts were successful. Somehow, this model is supposed to get schools to 100% proficiency on key learning outcomes.
  • he key difference in this model is an emphasis on ongoing progress monitoring and continuous, useful data flow to teachers
  • Under this approach, schools have good baseline data available to them, which means that the data are useful for diagnostic purposes in the classroom and thus relevant to instruction. The data also are timely, meaning that teachers rarely have to wait more than a few days to get results. In an effective data-driven school, educators also are very clear about what essential instructional outcomes they are trying to achieve (this is actually much rarer than one would suppose) and set both short- and long-term measurable instructional goals from their data.
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  • It is this middle part of the model that often is missing in school organizations. When it is in place and functioning well, schools are much more likely to achieve their short- and long-term instructional goals and students are much more likely to achieve proficiency on accountability-oriented standardized tests. Teachers in schools that have this part of the model mastered rarely, if ever, complain about assessment because the data they are getting are helpful to their classroom practice.
  • When done right, data-driven decision-making is about helping educators make informed decisions to benefit students. It is about helping schools know whether what they are doing is working or not
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    Thoughtful analysis from Scott McLeod. In his work with numerous school organizations in multiple states, he has seen the power of data firsthand. When done right, data-driven education can have powerful impacts on the learning outcomes of students. Unfortunately, most school districts still are struggling with their data-driven practice. Much of this is because they continue to think about using data from a compliance mindset rather than using data for meaningful school improvement
Anne Bubnic

What Is a "Professional Learning Community"? |Richard DuFour - 0 views

  • Big Idea #1: Ensuring That Students Learn The professional learning community model flows from the assumption that the core mission of formal education is not simply to ensure that students are taught but to ensure that they learn. This simple shift—from a focus on teaching to a focus on learning—has profound implications for schools.
  • Big Idea #2: A Culture of Collaboration Educators who are building a professional learning community recognize that they must work together to achieve their collective purpose of learning for all. Therefore, they create structures to promote a collaborative culture.
  • Big Idea #3: A Focus on Results Professional learning communities judge their effectiveness on the basis of results. Working together to improve student achievement becomes the routine work of everyone in the school. Every teacher team participates in an ongoing process of identifying the current level of student achievement, establishing a goal to improve the current level, working together to achieve that goal, and providing periodic evidence of progress. The focus of team goals shifts. Such goals as "We will adopt the Junior Great Books program" or "We will create three new labs for our science course" give way to "We will increase the percentage of students who meet the state standard in language arts from 83 percent to 90 percent" or "We will reduce the failure rate in our course by 50 percent."
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    The professional learning community model has now reached a critical juncture, one well known to those who have witnessed the fate of other well-intentioned school reform efforts. In this all-too-familiar cycle, initial enthusiasm gives way to confusion about the fundamental concepts driving the initiative, followed by inevitable implementation problems, the conclusion that the reform has failed to bring about the desired results, abandonment of the reform, and the launch of a new search for the next promising initiative. Another reform movement has come and gone, reinforcing the conventional education wisdom that promises, "This too shall pass."
Anne Bubnic

Taking data to new depths [Nancy Love] - 0 views

  • While collaborative inquiry is appropriate for any content area, it is particularly relevant for mathematics and science because the process mirrors for the adults what students experience in our best mathematics and science classrooms. Data teams investigate not scientific phenomena or mathematics problems, but how to improve teaching and learning. They raise questions, examine student learning and other data, test their hypotheses, and share findings with their colleagues.
  • Typically, one or two teachers, one administrator, and one NSF project staff member become data facilitators for a school. They then convene school-based data teams to focus on improving mathematics and science. Sometimes team members are from the mathematics or science department or are existing grade-level teams. Other times, the team is schoolwide.
  • If data facilitators have only one source of data on student learning, they collect additional data such as local assessments or common grade-level and course assessments for the next data facilitator session. The process emphasizes triangulating data, using three different sources of student learning data before identifying the student learning problem. By triangulating, data facilitators guide data teams to test hunches with other data instead of drawing conclusions from a single measure.
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  • In their data facilitator workshops, data facilitators use the "go visual" principle, first developed by nonverbal communications expert Michael Grinder (1997). Grinder revealed the power of large, visually vibrant and color-coded displays of data in fostering group ownership and engagement. Data facilitators work with the team on one data report at a time to avoid overload and confusion. For each report, they create a colorful newsprint-sized graph displaying the results and post it on their "data wall." Then they record their observations and inferences on additional pieces of newsprint that they post under their chart. As they work with additional data, they add more graphs and more observations and inferences to their data wall.
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    There's a ton of data being collected. The trick is to know how to use it effectively.
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