Equity-Oriented Learning Analytics
NYU-LEARN
Equity-Oriented Learning Analytics
56:00
The Power of Programming Analytics
NYU-LEARN
The Power of Programming Analytics
29:11
Understanding Learners through Data in Computer Science Education
NYU-LEARN
Understanding Learners through Data in Computer Science Education
1:00:46
Data Literacy in the 21st Century
NYU-LEARN
Data Literacy in the 21st Century
56:55
Using Multimodal Learning Analytics to Address the Challenges of Online Collaboration
NYU-LEARN
Using Multimodal Learning Analytics to Address the Challenges of Online Collaboration
58:50
Bigger than Just a Course: Using Analytics to See and Improve Educational Degrees
NYU-LEARN
Bigger than Just a Course: Using Analytics to See and Improve Educational Degrees
57:58
The Power of Learning Analytic Tools for Large Introduction Classes
NYU-LEARN
The Power of Learning Analytic Tools for Large Introduction Classes
1:03:23
Upping Your Advising Game with Learning Analytics: A Conversation
NYU-LEARN
Upping Your Advising Game with Learning Analytics: A Conversation
58:56
What is Learning Analytics?
NYU-LEARN
What is Learning Analytics?
21:16
Fairness & Equity in Learning Analytics: A Conversation
NYU-LEARN
Fairness & Equity in Learning Analytics: A Conversation
59:44
Scaling Up Learning Analytics: A Conversation
NYU-LEARN
Scaling Up Learning Analytics: A Conversation
1:02:46
Carolyn Rosé | The Next Frontier of AI-Enabled Collaborative Learning
NYU-LEARN
Carolyn Rosé | The Next Frontier of AI-Enabled Collaborative Learning
58:46
Roberto Martinez- Maldonado | Multimodal Data Stories to Support Reflection in Clinical Simulations
NYU-LEARN
Roberto Martinez- Maldonado | Multimodal Data Stories to Support Reflection in Clinical Simulations
54:33
College in the Time of Corona: Survey Results & Community Discussion
NYU-LEARN
College in the Time of Corona: Survey Results & Community Discussion
41:24
Can We Trace Professional Identity Development through (Mixed-Methods) Data Mining?
NYU-LEARN
Can We Trace Professional Identity Development through (Mixed-Methods) Data Mining?
57:23