Enabling & Evaluating Real-Time Collaboration in Online Learning Platforms

Peter Halpin & Yoav Bergner, with a seed grant from the Moore-Sloan Data Science Environment, will prototype a new tool for bringing collaborative problem solving to online learning at scale

Educators and potential employers frequently emphasize the importance of collaboration in classrooms and workplaces.

Even policy-makers, at both state and federal levels, have acknowledged the significance of collaboration, notably apparent in the Every Student Succeeds Act. Consequently, online courses, flipped classrooms, and other personalized online learning experiences have faced criticism for neglecting the social aspects of learning.

But with a joint research project focused on developing applicable solutions, Peter F. Halpin, CDS Affiliated Faculty and Assistant Professor of Applied Statistics at NYU Steinhardt, and Yoav Bergner, Assistant Professor of Learning Sciences and Educational Technology at NYU Steinhardt, intend to provide ways for online education and training programs to better incorporate real-time collaboration.

While current software for real-time collaboration like Google Drive and Skype is abundant and widely used, Halpin and Bergner point out that such software does not accommodate structured learning activities for small groups.

The researchers plan to integrate open-source real-time collaboration software like TogetherJS with OpenEdx, an online learning management system that will allow instructors and content authors to design and deploy collaborative exercises. They also aim to develop new types of group learning activities, such as curriculum-aligned collaborative physics problems. In these problems, subsets of information required to reach solutions are distributed among students who must strategize how to share the information.

Halpin and Bergner propose that integrating real-time collaboration software with a learning management system will provide opportunities for the collection and analysis of data regarding user behavior during collaborative exercises. Halpin has developed an algorithm to model student engagement in online chat groups. While he has shown how his algorithm can be used to evaluate the intensity of collaborative engagement in past research, this project will involve modeling student engagement across multiple groups and multiple time periods.

The outcome of Halpin and Bergner’s project will supply an accurate, quantitative method to evaluate collaborative skills based on the intensity of user engagement with group members.

In the future, their method could be applied to evaluate educational programs, assess collaboration skills, and track student progress. With current methods for these types of evaluation sometimes relying on self-reporting, Halpin and Bergner’s method will be a welcome advance for educational accountability.

Their future plans also include developing their proposed prototype for a new collaborative learning management system into a commercially available software as a service.

By Paul Oliver

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