Big Data in Education

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Quiz Questions

1.
How are decisions made about data and systems across your organization?
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- A.
  People make decisions and stuff gets done. Or not.
- B.
  Each department leader makes decisions for his/her department.
- C.
  We have a decision-making process that involves our entire organization that everyone utilizes.
- D.
  We collaborate with our external partners and stakeholders and across our organization. It takes time, but it's worth it.
- E.
  Some departments will work together to make decisions.
2.
What kind of training and support is offered/provided as related to your data systems?
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- A.
  We provide basic training on a few systems. It's not required and we don't do as much as we'd like to.
- B.
  We don't provide much formal training and support. Good systems should be easy for anyone to use.
- C.
  We provide on-demand training and support based on the different situations and roles across our organization and for our external partners and stakeholders when they are using our data systems.
- D.
  We provide basic role-based training and support for data tools/systems.
- E.
  We have personalized options to help advance data literacy and use for each user by role and need.
3.
How are you governing your data?
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- A.
  Each department sets its own rules for its data.
- B.
  We have robust data governance standards, policies, and procedures that include and extend to our external stakeholders and partners who share data with us.
- C.
  Departments collaborate on establishing data rules, policies, and procedures.
- D.
  We have organization-wide data governance policies and procedures that are embedded into our systems/tools.
- E.
  We know we need to be doing more here, but we're not sure where to start or why this is important.
4.
How would you classify the quality of your data?
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- A.
  Sometimes good, sometimes bad, often the same data conflicts depending on how it is being used. Each department handles checking quality internally and the capacity really varies.
- B.
  We have known data quality issues and cleaning up our data takes a lot of time and I'm not sure if we're always getting it right and who is responsible.
- C.
  We have organization-wide data quality checks that are embedded into our systems/tools.
- D.
  We have clearly defined data quality standards, policies, and procedures that are built into our systems and business practices and our external stakeholders and partners who share data with us have also adopted the same.
- E.
  We've done a lot of work to improve data quality across the organization by collaborating across departments and between admin and school sites on key areas of focus.
5.
How well are you ensuring that your data is kept private?
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- A.
  We have clearly defined privacy standards, policies, and procedures that meet/exceed FERPA (etc.) compliance and extend to our external stakeholders and partners who share data with us.
- B.
  Individual departments handle the privacy of their data and who has access to it. Oftentimes, access to data is based on relationships rather than clear protocols.
- C.
  We have role-based access to data that is regularly monitored. We're working on developing organization-wide data privacy policies and procedures.
- D.
  We are compliant with FERPA (etc.), but we don't have a clear data privacy policies or procedures.
- E.
  We have clearly defined data quality standards, policies, and procedures that are built into our systems and business practices across our organization.
6.
How do you primarily use data across your organization?
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- A.
  Individual departments and schools have outcomes and metrics that they track periodically and annually.
- B.
  We use data primarily for state and federal reporting.
- C.
  Beyond state and federal reporting, we have some organizational goals with metrics that we track annually.
- D.
  We have clear metrics and outcomes for student success that are widely embraced by our internal and external stakeholders and partners. All data collected is utilized to better understand how we are doing relative to those metrics and outcomes and to help us continously improve our work in serving students and their families.
- E.
  All of our metrics across schools and departments are linked to organizational goals and metrics. We track these in real-time (where practical) to help drive decision-making and continuous improvement.
7.
How would you describe your data tools in relation to each other?
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- A.
  Seamlessly integrated. All of our internal and external stakeholders know where to go to add data or get the data insights they need and can do so with ease.
- B.
  Our data tools work well together (for the most part). We have a few data hubs--student, employee, financial--and within those areas, the tools are integrated.
- C.
  Seamlessly integrated, internally. All of our internal stakeholders know where to go to add data or get the data insights they need and can do so with ease. External data sharing is still a challenge.
- D.
  We mostly use individual tools (excel/paper/some databases) and we have to manually import and export data.
- E.
  Some of our data plays well together, but we still do a lot of work to manually manipulate it and combine it, as needed.
8.
How would you describe your (back end) data architecture?
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- A.
  We have a data warehouse and our internal *and external* stakeholders have real-time analytics/insights about student progress and needs so they can respond accordingly.
- B.
  We've been able to consolidate most of our data systems and tools into a few key hubs--student, financial, employee data--with bi-directional interfaces.
- C.
  We have some one-way point-to-point integration between tools (i.e. special education data application and student information system). But not all of our data tools are integrated.
- D.
  We have a data warehouse and our internal stakeholders have analytics/insights about student progress and needs so they can respond accordingly. We're still working with our external partners on this.
- E.
  We haven't given much thought to this yet/ it is minimal/I have no idea how it all works behind the walls.

Quiz Outcomes

1.
Level 1: Initial
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You know you're collecting a lot of data and you've started developing tools and systems to help you manage it. You know you need to be doing more, but you're not sure where or how to start.
2.
Level 2: Emerging
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You're off to a good start, but silos in your organization are a challenge. You're ready to lead a collaborative process to improve your data ecosystem.
3.
Level 3: Integrated
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You're well on your way to having your data house in order. Having a healthy data ecosystem is clearly an organizational priority. You are nearly on the cutting edge of big data use in education, but you may be feeling unsure of the next best step for your organization.
4.
Level 4: Optimizing
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Congratulations!! You've made it to the basecamp of education data ecosystems! Your organization has optimized its data internally and you're ready for your data Everest: bringing in external partner data and sharing. We want to learn from you, help you be a model for others, and be your sherpas as you ascend to level five!
5.
Level 5: Responsive
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You're a rockstar! Would you be interested in being a case study/model of awesome for other districts/CMOs/state departments of education? The sector needs to learn from you and we want to help.

Big Data in Education

How well is your data ecosystem supporting your teaching and learning goals?

Quiz Questions

Quiz Outcomes