The Stanford Transforming Learning Accelerator presents the Winter Lightning Talk Series. The series consists of three conversations that will focus on cutting edge research. Each session will examine research methods, breakthroughs, and opportunities to create new ways forward.

The second of three conversations on cutting edge research features Nilam Ram, Professor in the Departments of Communication and Psychology at Stanford University.

Now that daily and digital life have merged, the ubiquitous devices in our pockets both demand our attention and facilitate engagement with new information – learning. Parents and teachers shape their children’s moment-to-moment experiences so that the children learn to make effective use of emerging attention control, receptive and expressive language, memory, and reasoning skills to regulate their actions and emotions – development of emotion regulation. We have developed a system for recording and analyzing everything people see and do on their screens – screenomics – and a Boolean network analysis that uncovers regularities in individuals’ behavioral sequences – journeys. In this session, Nilam will illustrate how these methods can be used to identify the specific strategy that would effectively guide an individual/child toward desired goals.

This session will be virtual, from 4:00 p.m.- 4:30 p.m. (Pacific), and include time for Q&A. A no-cost registration is required for each talk.

Nilam Ram is a Professor in the Departments of Communication and Psychology at Stanford University. Nilam’s research grows out of a history of studying change. After completing his undergraduate study of economics, he worked as a currency trader, frantically tracking and trying to predict the movement of world markets as they jerked up, down and sideways. Generally, Nilam studies how short-term changes (e.g., processes such as learning, information processing, emotion regulation, etc.) develop across the life span, and how longitudinal study designs contribute to generation of new knowledge. Current projects include examinations of age-related change in children’s self- and emotion-regulation; patterns in minute-to-minute and day-to-day progression of adolescents’ and adults’ emotions; and change in contextual influences on well-being during old age. He is developing a variety of study paradigms that use recent developments in data science and the intensive data streams arriving from social media, mobile sensors, and smartphones to study change at multiple time scales.

Upcoming Sessions

March 1: Elizabeth Kozleski, Learning Differences and the Future of Special Education