This project explores the benefits of bringing Social Interaction to Massive Open Online Courses (MOOCs). Students taking MOOCs benefit from being able to do their work anytime and anywhere, but miss out on the benefits of interacting with other students that in-person classrooms offer.
Peer learning has been shown in dozens of in-person classroom studies to improve learning, retention and morale across student demographics; the goal of this work is to see if the benefits seen in face-to-face peer learning can be replicated in MOOCs and SPOCs. As opposed to unstructured team projects, group interactions in peer learning are structured, often brief, and membership of groups is encouraged to be heterogeneous and rotated frequently. Our software automatically places remotely located students into synchronous groups for discussing the ideas behind study questions. In a series of experiments we have found that answers improve after small group discussions when participants are incentivized to help the entire group achieve the correct answer. We have performed initial tests in a >1000 person SPOC as well, with similar promising results.
In massive online courses, we need to get creative about how to give feedback to students about their creative work on assignments. We are developing methods to improve peer feedback on design problems. We suggest a new approach that combines the methods of heuristic evaluation and a simple usability test into one assessment that allows instructors and students to check for outliers in assessments and to rank different designs according to both qualitative and quantitative measures simultaneously.
MOOC Forums are the way students currently interact with one another in most MOOCs. We have experimented with introducing reputation features into MOOC online forums, finding faster response times and larger number of responses per posts, along with differences in how students ask questions, but no differences in grades, retention, or feelings of community. We also found that a course-wide chat system did not engage a significant slice of the student population.
Online, open access, high-quality textbooks are an exciting new resource for improving the online learning experience. Because textbooks contain carefully crafted material written in a logical order, with terms defined before use and discussed in detail, they can provide foundational material with which to buttress other resources. As a first step towards this goal, we explore the automated augmentation of a popular online learning resource – Khan Academy video modules – with relevant reference chapters from open access textbooks.
Ontologies provide a structured representation of concepts and the relationships which connect them. This work investigates how a pre-existing educational Biology ontology can be used to generate useful practice questions for students by using the connectivity structure in a novel way. It also introduces a novel way to generate multiple-choice distractors from the ontology, and compares this to a baseline of using embedding representations of nodes.
Open source software for MOOCChat is available. Two versions of the code have been developed. Use at your own risk; no support is offered.
UC Berkeley professors co-founded the ACM Learning@Scale conference in 2014.
This research is supported by a generous research award from Google's Social Interactions Program and the National Science Foundation under Grant No. IIS 1149799 and IIS 1210836.