Big Data in Education:

1. #DataSoWhat Big Data in Education: How Can Data Analytics Be Effectively Harnessed to Benefit Students, Industry, and the Country? Imah Effiong, Ayushman Banerjee, Silvia Ciobotaru, Jackie Lively, Conor McKay

2. Current Landscape • Federal v. States/Provinces • Differences between data and systems; Jurisdictional divides; Lack of collaboration and sharing • Lag in Policy • Lack of consensus; Difficult to change standards for students midstream; Technology evolving faster than policy can keep up • Capacity Limitations • Data analysts, technology, infrastructure, data systems • Privacy Issues • How is data used? Who has access? Role of 3rd party vendors? Lack of codified standards and principles

3. What Needs to Be Done? Recommended Positioning: 1) Establishing a framework 2) Creating Private Public Partnerships 3) Building Capacity

4. Recommendation #1 Establish Framework Appoint a Big Data in Education Task Force to Establish a Framework • Bring together State/Provincial, Federal, Industry, Union reps, and other stakeholders, charged with: • Identifying best practices • Codifying privacy principles • Establishing data system standards & guidelines

5. Recommendation #2: Are Private Public Partnerships the Answer? YES! 1. Money 2. People and Infrastructure 3. Bypass Federal v. State/ Province Divide Non-Profit Organizations/ Foundations: Gates Foundation, Maintree Foundation, Canadian Council on Learning Research Universities: University of Michigan, University of Toronto EdTech: Simplisico, Eduvee, Spongelab Interactive Federal Government

6. Recommendation #3: Building Capacity • Training in analytics • Modern data systems • Better infrastructure and technology systems • Buy-in from stakeholders

7. Big Data: Pros/Cons