Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
HAI Weekly Seminar with Mitchell Stevens | Stanford HAI
Skip to content
  • About

    • About
    • People
    • Get Involved with HAI
    • Support HAI
    • Subscribe to Email
  • Research

    • Research
    • Fellowship Programs
    • Grants
    • Student Affinity Groups
    • Centers & Labs
    • Research Publications
    • Research Partners
  • Education

    • Education
    • Executive and Professional Education
    • Government and Policymakers
    • K-12
    • Stanford Students
  • Policy

    • Policy
    • Policy Publications
    • Policymaker Education
    • Student Opportunities
  • AI Index

    • AI Index
    • AI Index Report
    • Global Vibrancy Tool
    • People
  • News
  • Events
  • Industry
  • Centers & Labs
Navigate
  • About
  • Events
  • Careers
  • Search
Participate
  • Get Involved
  • Support HAI
  • Contact Us

Stay Up To Date

Get the latest news, advances in research, policy work, and education program updates from HAI in your inbox weekly.

Sign Up For Latest News

Your browser does not support the video tag.
eventSeminar

HAI Weekly Seminar with Mitchell Stevens

Status
Past
Date
Wednesday, April 21, 2021 10:00 AM - 11:00 AM PST/PDT
Overview
Watch Event Recording

Massive: How MOOCs Changed the Landscape of Education Research

Overview
Watch Event Recording
Share
Link copied to clipboard!
Event Contact
Celia Clark
celia.clark@stanford.edu

Related Events

Dan Iancu & Antonio Skillicorn | Interpretable Machine Learning and Mixed Datasets for Predicting Child Labor in Ghana’s Cocoa Sector
SeminarMar 18, 202612:00 PM - 1:15 PM
March
18
2026

Child labor remains prevalent in Ghana’s cocoa sector and is associated with adverse educational and health outcomes for children.

Seminar

Dan Iancu & Antonio Skillicorn | Interpretable Machine Learning and Mixed Datasets for Predicting Child Labor in Ghana’s Cocoa Sector

Mar 18, 202612:00 PM - 1:15 PM

Child labor remains prevalent in Ghana’s cocoa sector and is associated with adverse educational and health outcomes for children.

Caroline Meinhardt, Thomas Mullaney, Juan N. Pava, and Diyi Yang | How Can AI Support Language Digitization and Digital Inclusion?
SeminarApr 15, 202612:00 PM - 1:15 PM
April
15
2026

What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.

Seminar

Caroline Meinhardt, Thomas Mullaney, Juan N. Pava, and Diyi Yang | How Can AI Support Language Digitization and Digital Inclusion?

Apr 15, 202612:00 PM - 1:15 PM

What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.

AI+Science: Accelerating Discovery
ConferenceMay 05, 20268:30 AM - 5:00 PM
May
05
2026

AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery. Experts will separate hype from reality, spotlighting where AI is already enabling genuine breakthroughs and where its limits and risks remain.

Conference

AI+Science: Accelerating Discovery

May 05, 20268:30 AM - 5:00 PM

AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery. Experts will separate hype from reality, spotlighting where AI is already enabling genuine breakthroughs and where its limits and risks remain.

The embrace of massively open online courses (MOOCs) by Harvard, MIT and Stanford from 2012-2014 created buzz and anxiety among educators worldwide. While many were quick to thereafter declare the failure of MOOCs as instructional technologies, their legacy continues to transform the landscape of educational research. MOOCs demonstrated that minute instructional interactions could be observed and experimentally instrumented at scale; lured substantial new talent to educational inquiry from the burgeoning fields of data science and machine learning; dramatically expanded what counts as an instructional environment; and abetted the flow of private capital into a burgeoning sector now called “learning.” In this talk I synthesize recent scholarship to frame the promise and risks attendant to pursuit of learning research in digitally mediated environments. 

Mitchell Stevens
Professor of Education and, by courtesy, of Sociology