BayLAN 2019
Stanford University
SCHEDULE
Schedule
Saturday, March 2, 2019
11:15 - 12:15 Parallel session I
8:30 - 9.00 Registration and breakfast (Light breakfast provided)
9:00 - 9:15 Opening
9:15 - 10:45 Invited session I
Mitchell Stevens
Director of the Center of Advanced Research through Online Learning (CAROL)
Personalization, Prediction, Tracking: Parsing Responsible Use of Student Data in Higher Education
Alina von Davier
Senior Vice President, ACTNext
An Illustration of an AI-based Educational Assistant and Its Underlying Learning Analytics
Shivani Rao
Senior Applied Researcher, LinkedIn
An overview of AI problems applied to the domain of Online Learning
1a: Recommendation and prediction in online environments
Yuchi Huang, David Edwards, Lu Ou and Saad Khan (ACTNext)
GMMC: Generating Multimodal Micro Content
Priya Venkat, Sanghamitra Deb and William Ford (Chegg)
Using weak supervision techniques to improve student experiences at Chegg
Shamya Karumbaiah and Ryan S Baker (University of Pennsylvania)
Predicting Quitting in Students Playing a Learning Game
1b: Tutoring
David Lang, Sigtryggur Kjartansson, Jayadev Bhaskaran and Lucianna Bennoti (Stanford University)
Modeling Student Response Times: Towards Efficient One-on-one Tutoring Dialogues
Katherine Stasaski and Marti Hearst (UC Berkeley)
Foreign Language Tutoring via Grounded Dialogue
Zoha Zargham, Sakshi Bhargava and Sanghamitra Deb (Chegg)
Personalization at Chegg
12:15 - 1:25 Lunch with topic discussions (Light lunch provided)
1:25 - 2:00 Parallel session II
2a: Learning analytics
Petr Johanes (Stanford University)
Putting the Philosophy of Modeling to Work for Learning Analytics
Ryan Montgomery and Eric Greenwald (UC Berkeley)
Learning and Analytics, Centered around Evidence ⚡️
TeachFX: a revolutionary new way to measure student engagement⚡️
2b: MOOCs
Varun Ganapathi, Byung-Hak Kimand Ethan Vizitei (Stanford University/Udacity)
Predicting and Improving Student Performance with Machine Learning
David Lang (Stanford University )
Predicting Clickstream Engagement in MOOCs using Transcript Level Features ⚡️
Yu Su (ACT)
Assessing Self-Learning Outcomes for Complex/Abstract Concepts under Virtual Reality Environment ⚡️
2:00 - 2:30 Invited session II
Adam Blum
Senior Director, Emerging Technologies, ACT
Methods of Intersystem Measurement of Instructional Resource Efficacy
2:45 - 3:45 Best practices in efficacy research
Speakers from Digital Promise, Empirical Education, Khan Academy and Rosetta Stone will discuss the intersection of learning analytics and evidence for product efficacy and facilitate a group discussion
4:00 - 5:00 Invited Session III
Zachary Pardos
Assistant professor of Education and Information, UC Berkeley
Approaches to Scalable Personal Guidance in MOOCs and On Campus
Emma Brunskill
Assistant professor in Computer Science, Stanford University
AI for Adaptive Curriculum
5:00 - 5:15 Wrap up and networking