Home Articles Reader Opinion Editorial Book Reviews Discussion Writers Guide About TCRecord
transparent 13

Executive Summary

Tomorrow’s EdTech Today: Establishing a Learning Platform as a Collaborative Research Tool for Sound Science

by Korinn S. Ostrow, Neil T. Heffernan & Joseph Jay Williams — 2017

To view the full-text for this article you must be signed-in with the appropropriate membership. Please review your options below:

   Store a cookie on my computer that will allow me to skip this sign-in in the future.
    Send me my password -- I can't remember it
Purchase this Article
Purchase Tomorrow’s EdTech Today: Establishing a Learning Platform as a Collaborative Research Tool for Sound Science
Individual-Resource passes allow you to purchase access to resources one resource at a time. There are no recurring fees. The pass is valid for the lifetime of your membership -- no renewal is necessary.
Become a Member
Online Access
With this membership you receive online access to all of TCRecord's content. The introductory rate of $25 is available for a limited time.
Print and Online Access
With this membership you receive the print journal and free online access to all of TCRecord's content.

Cite This Article as: Teachers College Record Volume 119 Number 3, 2017, p. 1-36
http://www.tcrecord.org ID Number: 21779, Date Accessed: 9/25/2018 11:20:14 AM
Article Tools
Related Articles

Related Discussion
Post a Comment | Read All

About the Author
  • Korinn Ostrow
    Worcester Polytechnic Institute
    E-mail Author
    KORINN S. OSTROW is a Ph.D. candidate in Learning Sciences & Technologies at Worcester Polytechnic Institute. Her concentrations include applied educational statistics and cognitive psychology, with research interests in learning interventions, experimental methods at scale, learning analytics within adaptive technologies, and enhancing student motivation and engagement. She expects to graduate in 2018. Recent publications include “The Future of Adaptive Learning: Does the Crowd Hold the Key?” in the International Journal of Artificial Intelligence in Education, and “The Assessment of Learning Infrastructure (ALI): The Theory, Practice, and Scalability of Automated Assessment,” in the Proceedings of the 6th International Conference on Learning Analytics and Knowledge.
  • Neil Heffernan
    Worcester Polytechnic Institute
    E-mail Author
    NEIL T. HEFFERNAN is a Professor of Computer Science and the director of the Learning Sciences and Technologies Graduate Program at Worcester Polytechnic Institute. He is best known for creating ASSISTments. He has used the platform to conduct and publish two dozen randomized controlled experiments and now strives to expand the platform as a tool for others to do the same. In addition, he has published three dozen papers on predictive analysis, using large educational datasets to predict student performance on standardized state tests, affective states like boredom and frustration, and even college admission years later. He cares deeply about helping others learn about personalized learning in a methodically rigorous way.
  • Joseph Williams
    Harvard University
    E-mail Author
    JOSEPH JAY WILLIAMS is a Research Fellow in the Vice Provost for Advances in Learning Research Group at Harvard, where he conducts human-computer interaction and statistical machine learning research on digital education. This bridges his postdoctoral work at Stanford's Graduate School of Education conducting randomized experiments in MOOCs and Khan Academy to motivate learners through psychological interventions. He received his Ph.D. from UC Berkeley, where he focused on computational cognitive science and developed the subsumptive constraints account of why generating self-explanations enhances learning. He also developed the MOOClet Framework for designing intelligent digital lessons that personalize learning through randomized comparisons of crowdsourced content. Recent publications include "Generating Explanations at Scale with Learnersourcing and Machine Learning," in ACM Learning at Scale, and "Revising Learner Misconceptions without Feedback: Prompting for Reflection on Anomalous Facts," in Computer-Human Interaction.
Member Center
In Print
This Month's Issue