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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.
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

Improving Decisions with Data [Doug Johnson] - 0 views

  • Harnessing more powerful data tools and greater amounts of data.
  • Granting teacher, parent and community access to data
  • Planning and utilizing interoperability standards
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  • Guaranteeing integrity, privacy and security
  • Building data analysis and interpretation skills
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    Administrators will face, if they aren't already, five particular challenges in their use of data.
    1.Harnessing more powerful data tools and greater amounts of data.
    2.Granting teacher, parent and community access to data
    3. Planning and utilizing interoperability standards
    4. Guaranteeing integrity, privacy and security
    5. Building data analysis and interpretation skills

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

Integrating Data Into the Decision-Making Equation. - 1 views

  • As school districts embark on the change process, they face many barriers to the adoption of data-driven decision making. School district leaders have not embraced continuous improvement. Priorities are not clear and goals are not tied to measurable objectives. Data is not collected uniformly between organizations and over time. Outdated technology cannot be used effectively. Educators lack training to define data requirements and apply data. Stakeholders do not trust the data collected or how it will be used.
  • Reports need to be timely, tied to objectives, and available to people with the responsibility and ability to act on them. Data reports that show data in different ways such as tables, charts, graphs, and trends enable more people to access and understand the information. Some of the decisions that might be made with data reports include: Tracking student achievement for diagnosis and placement Changing beliefs and attitudes that all students can learn Guiding teacher professional development Linking interventions to results Using data to create school improvement plans and assess progress Allocating district resources
  • The IT infrastructure underpinning most data-driven decision making systems requires a significant investment in hardware, software, implementation, and maintenance.
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    The successful integration of data into a district's decision-making process requires both a culture of change and a data management system to support change. Nice chart of progress quadrants included in the discussion.
Anne Bubnic

Leading the Data Analysis Discussion: Interpreting Your AYP Results - 0 views

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    Analyzing your data is a process in which you will want to involve your entire staff. Good data-driven dialogue keads to data-driven decisions. If you engage staff in an ongoing data dialogue, it is much more likely that you will feel ownership for the data-based decisions you collectively make.
Anne Bubnic

Data: Mining with a Mission - 0 views

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    Data warehousing has become an essential district tool. Historically available only to large corporations due to price and complexity, data warehousing is now an affordable and manageable option for gathering, manipulating and incorporating district data. While the inclusion of a data warehouse can be a boon for districts, the process of its development and support needs careful planning and management.
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

Analyzing and Using the Data - 0 views

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    A major purpose of the monitoring plan is to put in place a system for the ongoing collection of data aligned with the content standard indicators/objectives you are responsible for teaching. You can't analyze data you don't have. And it is not useful to analyze data that is not aligned with your learning outcomes. Once you have the data, you are ready to analyze it.
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

Seven Steps to Creating a Data Driven Decision Making Culture - 0 views

  • In this post I hope to share the essence of some of the main ideas communicated in the speech. The format is: words from the slide followed by a short narrative on the core message of the slide. Hope you find it useful.
  • The biggest challenge in our current environment is that it is trivial to implement a tool, it takes five minutes. But tools are limiting and can just give us data. What compounds the challenge is that we all have this deep tendency to make decisions that come from who we are influenced from our life experiences. Based on my humble experience of the last few years here are seven common sense recommendations for creating a data driven company culture……
  • # 6 Reporting is not Analysis
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  • # 7 Go for the bottom-line (outcomes)
  • # 5 Depersonalize decision making
  • # 4 Proactive insights rather than reactive
  • # 3 Empower your analysts
  • # 2 Solve for the Trinity
  • # 1: Got Process?
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    The title of this presentation at the Washington DC Emetrics summit was: Creating a Data Driven Web Decision Making Culture - Lessons, Tips, Insights from a Practitioner. Although meant for corporations, the advice applies just as well to academic institutions. The goal here was to share tips and insights that might help companies move from just having lots and lots of data to creating cultures where decisions are made not on gut-feel, or the proverbial seat of the pants, but rather based on data.
Pehr Ambesh

Download Groom Exim normal information and Custom Data - 0 views

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Pehr Ambesh

Download Ladies Cotton Exim normal information and Custom Data - 0 views

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Anne Bubnic

Getting Started with Data Warehousing - 0 views

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    Historically available only to large corporations due to price and complexity, data warehousing is now an affordable and manageable option for gathering, manipulating and incorporating district data. While the inclusion of a data warehouse can be a boon for districts, the process of its development and support needs careful planning and management.
Anne Bubnic

Framework for a Comprehensive Ed Data System in California - 0 views

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    The 118 page report, "Framework for a Comprehensive Education Data System in California - Unlocking the Power of Data to Continually Improve Public Education," recommends significantly expanding and linking information from California's K-12 system to data from pre-K, higher education, workforce, and social services data systems to inform decisions that extend beyond K-12.
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

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
Pehr Ambesh

Search HS Code 83111000 Free and Grab Export Data - 0 views

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Pehr Ambesh

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