News & Events
June 19, 2019
Please respond to this call for applications to attend the NSF Education Data Analytics Collaborative Workshop on December 5-6, 2019. Approved applicants will attend as an NSF Data Collaborative Fellow and will be matched into a datasprint team with educators (teachers, principals, superintendents) as well as other education data scientists. Teams will first encounter and discuss a variety of current and possible design ideas through a structured set of discussions and education data science and data use examples, and then work together to create and design visualizations and code.
We aim to accept about 15 applicants, depending on proposal topics, identified datasprint team needs, and event space restrictions. We will inform applicants by mid-September 2019 of the status of their application. The deadline for submissions is Friday August 16, 2019 at 5pm EDT. Please email application submission materials in PDF form and CV/resume to Alex J. Bowers (Bowers@tc.edu).
The full description of the event and directions on how to apply are found below and in the event announcement.
National NSF Education Data Analytics Collaborative Workshop
Smith Learning Theater, Teachers College, Columbia University, New York City December 5 & 6, 2019
Currently across K-12 education, schools and districts are investing in Instructional Data Warehouses (IDW) and School Information Systems (SIS) in an effort to provide actionable information for educators to inform evidence-based practice and decision-making. Yet, across research and practice, much work remains to understand the types of data to display that are most helpful to teacher, principal, and central office decision making, as well as what types of data dashboards, visualizations, and UX best serve the needs of schooling communities [1-3]. This work requires insights from both educators in schools as well as the current work of education data scientists working at the intersection of research and practice [4-7]. As part of a larger National Science Foundation funded project, we are gathering educators and education data scientists together for an exciting interactive two-day event to learn together through a datasprint design-based collaborative workshop. The goal of the event is to work to understand the needs of educators around education data and data dashboards, and then iteratively build prototype visualizations and code together to help address educator data use needs across the system. The event will be held on December 5 and 6, 2019, at Teachers College, Columbia University’s state-of-the-art 21st century collaborative learning space, the Smith Learning Theater. This NSF funded project is part of a larger Building Community and Capacity (BCC) collaboration with the 56 school districts of Nassau County Long Island, New York.
We are requesting applications to attend the event from education data scientists as an NSF Data Collaborative Fellow. If accepted, over the two days of the workshop you will be matched into a datasprint team with educators (teachers, principals, superintendents) as well as other education data scientists. Teams will first encounter and discuss a variety of current and possible design ideas through a structured set of discussions and education data science and data use examples, and then work together to create and design visualizations and code. Space is limited, so we are requesting applications to attend as a data scientist participant. To apply to attend the event, please submit a CV/resume and an application letter of 1,000-2,000 words that includes the following (word limit excludes any tables, figures, or references):
- Applicant name, job title, affiliation, and contact information.
- Experience as an education data scientist, including collaborations with educators around data use and/or proficiency in open-source coding environments such as R or Python.
- A discussion of the current issues in the field of education data science, including successes
and challenges at the intersection of school decision making, evidence-based improvement
cycles, data analytics, and data visualization for improvement.
- An example of how you have addressed an education data science issue in your work, with
prototype or final data visualization or analysis, linked to a discussion of impact (or potential
impact) on the organization.
- A discussion of any of the current central questions in education data science [3, 5-7] of data
privacy, equity, ethics, algorithmic fairness, or data management among others.
As an invited participant, accepted applicants are expected to contribute a chapter as an author to the proceedings from the meeting workshop, including publication of an essay, or research and application paper brief (3-5 pages) on the datasprint outcomes, and/or participant perspectives on data use, data visualization, and data science in education research and practice. Results from the workshop will be provided to participants for additional data analysis for the proceedings contribution. The chapter is intended to build from and extend the submitted application materials. Proceedings from the meeting will be published online in mid-2020 in an open access e-book, including visualizations, and prototype code, with author contributions due in late March, 2020.
While the event is free to attend for accepted applicants (no registration fee), due to limited
funding, applicants will need to provide their own travel and housing accommodations for the two days of the event. Lunch and refreshments will be provided each day of the event to attendees.
By applying, please note that you are agreeing to the following:
- Have the work of teams from the workshop be made publicly accessible online.
- Agree to be audio and video recorded within the Learning Theater space for archival and research purposes.
- Participate in pre- and post-event surveys.
- Agree, that if accepted, you will pledge to attend the event, which will be held 9:00am-5:00pm on December 5, and 9:00am to 4:00pm on December 6, 2019.
We aim to accept about 15 applicants, depending on proposal topics, identified datasprint team needs, and event space restrictions. We will inform applicants by mid-September 2019 of the status of their application. The deadline for submissions is Friday August 16, 2019 at 5pm EDT. Please email application submission materials in PDF form and CV/resume to Alex J. Bowers
April 8, 2019Event
AERA has announced the schedule for the 2019 conference. There are eight sessions planned for the SIG on Data-Driven Decision Making in Education.
Please note a special session on Tuesday morning (April 9th) at 8:00 AM which will be a two-hour interactive brainstorming event to discuss important topics in the field. It is intended to move the field of data use forward in terms of next steps for research, policy, and practice.
Also, the business meeting is Monday night (April 8th). Please try and attend. The SIG will be holding elections for some posts and there will be an interactive panel following the business portion of the meeting.
December 20, 2018
DDI colleagues will be presenting at the International Congress for School Effectiveness and Improvement 2019 Conference in Stravanger, Norway.
- Amanda Datnow will provide the keynote “Data Use with Purpose: Promoting Equity and Professional Collaboration in School Improvement”
- Kim Schildkamp, Amanda Datnow, and Jo Jimerson will participate in the symposium “Data Use In Education: Filling in the Gaps”
- Ellen Mandinach will serve as discussant for the symposium “Conditions for Data-Informed Decision-Making: Collaboration, Sensemaking, and Distributed Leadership”
- Ellen Mandinach and Kim Schilkamp will facilitate a discussion on “Misconceptions in Data-Driven Decision Making in Education”
- Ellen Mandinach will present “Data Literacy in Teacher Preparation”
- Ellen Mandinach, Kim Schildkamp, Cindy Poortman, and Amanda Datnow will participate in the symposium “Teachers Using Data: Professional Development and Teacher Preparation”
- Diana Nunnaley will participate in the symposium “Effects of Data Feedback on Teaching Quality”
December 20, 2018
A new article explores the nature of the information parents seek to make decisions about their child’s education and provides insight on the characteristics of data displays that would make education information accessible and understandable.
“Parental Educational Decision Making: The Information They Seek and What They Want from Data Systems” will be published in Teachers College Record. The authors (Dr. Ellen B. Mandinach, Dr. Ryan C. Miskell, and Dr. Edith S. Gummer) find parents seek qualitative data sources that supply descriptions of schools and districts. They want not only test scores and school grades but also information that helps them understand the schools: details about the teachers, leaders, and programs offered and information about safety and processes. Parents want the information presented in accessible and understandable formats that include better graphics and more easily understood details.
December 20, 2018
Dr. Ellen B. Mandinach and Dr. Edith S. Gummer have released a new book that addresses the issue of data use in educator preparation programs toward continuous programmatic improvement.
With an aim to increase the rigor in both research and practice in educational administration and teacher education, this volume will analyze the longstanding quality concerns about teacher and leadership preparation and standards for programs and educators, as well as controversies concerning national accreditation and federal efforts to mandate program reporting data. By exploring the policies and practices that influence departments of education, this volume examines the increasing pressures to improve institutional functioning within a complex system of university, state, and national structures and organizations.
- Introduction and Overview
- Landscape View of the Continuous Improvement Process
- Creating a Data Culture in Educator Preparation: The Role of the States
- Building Capacity and Commitment for Data Use in Teacher Education Programs
- Moving Toward Common Measures to Accelerate Improvement: A Roadmap for Educator Preparation Programs
- Connected for Improvement: The Teacher Preparation Data Model and TPP Dashboard
- Learning to Walk the Walk of Continuous Improvement
- Visualizing Data: Necessary but Not Sufficient for Educator Preparation Program Continuous Improvement
- Lessons Learned While Building a Data Use Culture
- Conclusions: Challenges, Opportunities, and Next Steps
June 6, 2018
WestEd, as part of REL Mid-Atlantic, has organized the Maryland State Department of Education Connections Summit in Towson, MD on June 6 and 7. Participants will take part in presentations from local, state, and national leaders on ways to bridge educartion data, research, policy, and practice.
Dr. Elizabeth Farley-Ripple of the University of Delaware will give the keynote speech, “Making Evidence Matter.” Ellen Mandinach of WestEd will speak on data literacy and data use. Ellen Mandinach and Ryan Miskell will speak about parental use of information to make educational decisions.
The WestEd Data for Decisions Initiative is pleased to announce the publication of the Data Literacy Assessments Project. These resources are available to educational professionals, professors and students in college and graduate courses, and to researchers.
The Data Literacy Assessments Project at WestEd, in collaboration with Using Data Solutions, has produced four scenario-based exercises that can be used to measure data literacy. The materials can be used as assessments, as supplemental instructional materials to develop data literacy for educational professionals in professional development or college and graduate courses, and for research purposes. The scenarios are designed to depict typical instances when teachers need to use data to make decisions in the course of their practice or personal experiences. They will allow users to demonstrate a variety of data literacy skills as outlined in the construct Data Literacy for Teachers (DLFT) developed by Ellen Mandinach and Edith Gummer.
The resources are available through the DDI website or by typing the URL into your internet browser: https://datafordecisions.wested.org/data-use-in-action/data-literacy-assessments/
A new book focuses on data use according to the Data Team™ Procedure, which schools throughout the Netherlands have been implementing in a supervised manner since 2009.
Essential to improving teacher quality is ensuring that the right data are available to inform the policy and practice changes needed to continuously improve educator preparation program (EPP) quality, teacher effectiveness, and ultimately student learning. Unfortunately, that data are not uniformly available today.
This paper describes how data sharing among states, EPPs, and K-12 leaders can help ensure quality teaching and learning. The paper:
- Discusses challenges to using data to improve educator preparation
- Presents state policy recommendations
- Profiles policy in action in Massachusetts, Tennessee, and Missouri
WestEd’s Ellen Mandinach served as a member of the working group for this paper, developed collaboratively over one year with a group of national, EPP, and state-level experts.
Ellen B. Mandinach contributed a blog post, which can be found below, on data literacy in early education to the National Institute for Early Education Research (NIEER).
Data have been used in education for many years. Good teachers and administrators have been using data to inform their practice and make decisions. Why is data use important? Because it is no longer acceptable for educators to solely use anecdotes and gut feelings to make decisions. Educators need hard evidence. To that end, there has been a growing emphasis for the past 15 years to make education a more evidence-based and data-driven discipline.
Data have ranged from accountability and compliance data to data for continuous improvement at all levels of education, but one issue that has loomed large is the conflation of data literacy with assessment literacy. The two constructs have been confounded for many years (Mandinach & Gummer, 2016a; Mandinach & Kahl, 2014). When educators and the general public think about data, they typically think about test results and student performance. They fail to think about all the other sources of data that help educators to inform their practice. Until fairly recently, there has been no clear definition of data literacy and certainly no analyses of the skills, knowledge, and dispositions that are needed to use data effectively and responsibly (Data Quality Campaign, 2014; Gummer & Mandinach, 2015; Mandinach & Gummer 2016a, 2016b). The work of Mandinach and Gummer, based on several years of research, has attempted to lay out what it means for educators to be data literate.
A foundation of data literacy is the consideration and use of diverse sources of data, not just the limitation to only student performance data. For educators to have a comprehensive understanding of their students, they must look to behavioral, attitudinal, motivational, medical, attendance, home context, and other kinds of data. Even though measures of teacher readiness such as the edTPA (SCALE, 2013) contain an assessment rubric, it makes clear that teacher candidates must be able use contextual information, “assets,” to inform their understanding of student performance.
Diverse sources of data are particularly important in early childhood education where teachers often must look beyond student performance results to understand a child. As Dwyer (2015) notes, some of the data most relevant in early childhood settings other than assessments (formative, summative, and diagnostic) include screening results, informal check-ins, child characteristics and experiences, attendance, health information, family language/education experiences, family conditions for learning, classroom observations, participation, walkthroughs, and staff experience and education. In workshops conducted across Pennsylvania for early childhood educators, Dwyer, Mandinach, Nunnaley, and Saylor (2015) noted several purposes for data use in early learning:
- Improve child outcomes
- Improve teachers’ skills
- Identify gaps in achievement
- Realign resources
- Facilitate parental engagement
- Improve program quality
- Increase access to high quality programs
- Change adult behavior
Dwyer and colleagues (2015) reflected on why data use is important in early learning settings, recognizing that evidence is important. They noted that there needs to be realistic expectations for how data use can inform and improve daily practice. Through effective data use, educators can:
- Reflect on practice
- Check assumptions
- Get others’ views
- Commit to new actions
- Attend to the effects of changes in practice
- Make practice public
But how does this happen? More than eight years ago, the Institute for Education Sciences (IES) commissioned a comprehensive review of the literature that existed at the time, recognizing that data-driven decision making was only then emerging as a hot topic in educational research (Hamilton, Halverson, Jackson, Mandinach, Supovitz, & Wayman, 2009). Some 3,000 research and implementation studies were identified with only a handful meeting the strict criteria for rigorous research laid out by the What Works Clearinghouse. Five recommendations were noted. For there to be effective data use at any level of education, schools and districts must:
- Make data part of an ongoing cycle of instructional improvement
- Teach students to examine their own data and set learning goals
- Establish a clear vision for schoolwide data use
- Provide supports that foster a data-driven culture within the school
- Develop and maintain a districtwide data system (p. iii)
These five recommendations have stood the test of time. The growing research in data use further confirms the recommendations. Much of the work firmly espouses the need for the introduction of data teaming, leadership, and the creation of data cultures within schools and districts. Data systems have morphed from data warehouses to dashboards and apps that provide real-time data for instructional decision making.
Yet despite having much of the infrastructure in place, particularly the billions of dollars spent on technology at the federal, state, and local levels, attention to the human infrastructure remains problematic. Fulfilling all of the five recommendations from the IES practice guide is an important step forward. However, if educators do not know how to use data both effectively and responsibly, the investment in attaining the recommendations will go for naught. Even though the field recognizes the importance of data use, the delivery of consistent and comprehensive professional development is often lacking and falls below other competing priorities.
As Means, Padilla, and Gallagher (2010) noted, professional development for data use must be ongoing, not sporadic. As Mandinach and Gummer (2016a) note, waiting until educators are in practice to acquire data literacy skills is too late. They must begin to acquire such skills at the earliest stages of their professional careers, that is, during pre-service preparation. Because of this growing need, WestEd and its collaborator, Using Data Solutions, is working toward the development of curriculum materials that can be used in teacher preparation programs to teach data literacy. The objective is for teacher preparation programs across the country to begin to integrate the construct, data literacy for teachers (Mandinach & Gummer, 2016a, 2016b) into their curricula. The ultimate objective is to create a teaching corps that knows how to use data.