"Blended learning" has become a trendy concept in education, but what is it, and what does it look like in the context of professional data education & data academies? I provide a brief overview of the concept of blended learning and propose how to apply it to data education using four delivery methods: in-person learning, online study, work-based projects and hackathons.

1. Using blended learning
for data education

2. What is blended learning?
• Mix of traditional in-person and online deliveries
• Mix of traditional lecture-based and activity-based
class time (think flipped classroom)
And blended learning for professional data education:
• Mix of traditional concept-based instruction and
project-based job tasks
• Done through four main delivery methods…

3. Blended learning + professional data
education
“Traditional” blended learning (whatever that is) plus:
• Mix of traditional concept-based instruction and
project-based job tasks
• Done through four main delivery methods…
• In-person learning
• Online study
• Work-based projects
• Hackathons

4. In-person learning
• Provide a distinct, distraction-free zone for learning
• Help learners articulate questions, communicate
their knowledge

5. Online study
• Self-paced, individual(ized)
• Lots of great ed-tech for teaching data

6. Work-based projects
• Blend the curriculum with real applications
• Learners can look at problems with fresh eyes
• Learners feel more comfortable & confident solving
existing problems

7. Hackathons
• Students work through problems in intense sprint
• Great for creativity, innovation, teamwork, morale

8. LET'S TALK
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stringfestanalytics.com
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george@stringfestanalytics.com
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linkedin.com/in/gjmount