Adaptive Learning Based On Cognitive and Learning Science From Carnegie Mellon

Audience Level: 
All
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Strands (Select 1 top-level strand. Then select as many tags within your strand as apply.): 
Abstract: 

New approaches to instructional design, combined with learning data and predictive analytics can help determine a student’s knowledge state and find the best path to achieve mastery, making learning more efficient and saving educators time.

Extended Abstract: 

New approaches to instructional design, combines with learning data and predictive analytics can help determine a student’s knowledge state and find the best path to achieve mastery, making learning more efficient and saving educators time.

In this session, see how Acrobatiq, an early stage-start up from Carnegie Mellon University is using content, data, design and technology to generate actionable information about each students’ learning state. In addition, learn how educators and instructional design teams are collaborating using new online curriculum development tools to create highly effective learning experiences for students grounded in the latest research from learning science.
 

Session Sponsor: 
Acrobatiq
Conference Session: 
Concurrent Session 2
Session Type: 
Solutions Showcase