Learners and Learning in MOOCs: Findings from Stanford's Lytics Lab
NOTE: The times listed are in EASTERN TIME.
Since establishing the Lytics Lab more than a year ago, Stanford researchers have been investigating learners and learning in MOOCs. In this session, four Lytics researchers will discuss their methodologies and findings. Jon and Chris will share machine learning–based methods for estimating and correcting for grader biases and reliabilities in large-scale peer assessment. Emily will discuss a study to computationally identify four prototypical trajectories of MOOC learners and explore the relationship of these longitudinal patterns with demographics and measures of course participation. Joseph will offer findings from laboratory experiments that suggest explaining "why" a fact is true provides a general boost to attention and engagement and selectively guides people to seek out and discover patterns and generalizations that underlie what they are explaining.
Learning Objectives: Describe Lytics researchers' methodologies and findings from their studies | Reflect on new approaches to exploring learning in MOOCs | Make plans for implementing changes in research and/or teaching practice in response to research findings
Postdoctoral Fellow, Stanford University
Chris PiechPhD Student, Stanford University
Emily SchneiderDoctoral Student, Stanford University
Joseph WilliamsResearcher, Stanford University