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Rapid remediation of student misconceptions and knowledge gaps is one of the most effective ways to help students learn. We present a system for recommending additional resources, such as videos, reading materials, and web pages for students working through on-line course materials. This can provide remediations of knowledge gaps involving complex concepts. The system relies on learners suggesting resources which helped them, leveraging economies of scale as found in MOOCs and similar at-scale settings in order to build a rich body of remediations. The system allows for remediation of much deeper knowledge gaps than in prior work on remediation in MOOCs. We validated the system through a deployment in an introductory computer science MOOC. We found it lead to more in-depth remediation than prior strategies.

We present results from a pilot study where students successfully created complex assessments for a MOOC in introductory electronics -- an area with a very large expert-novice gap. Previous work in learnersourcing found that learners can productively contribute through simple tasks. However, many course resources require a high level of expertise to create, and prior work fell short on tasks with a large expert-novice gap, such as textbook creation or concept tagging. Since these constitute a substantial portion of course creation costs, addressing this issue is prerequisite to substantially shifting MOOC economics through learnersourcing. This represents one of the first successes in learnersourcing with a large expert-novice gap. In the pilot, we reached out to 206 students (out of thousands who met eligibility criteria) who contributed 14 complex high-quality design problems. This results suggests a full cohort could contribute hundreds of problems. We achieved this through a four-pronged approach: (1) pre-selecting top learners (2) community feedback process (3) student mini-course in pedagogy (4) instructor review and involvement.

Human behavior increasingly involves digital online software, where the activities and resources that support (1) learning, (2) work, and (3) collaboration overlap and are placed in far greater proximity than the physical world -- often just a browser-tab or window away. What scientific and practical gains in 21st century learning, work, and collaboration can be achieved by integrating and contrasting these three areas' relevant technologies, scientific communities, and industry practitioners?For example: How can software for collaborative work incorporate learning? Which methods are effective for coordinating diverse experts to iteratively improve online educational resources? How can online learning improve the skill set and labor force for crowd work? What kinds of computational frameworks exist to jointly optimize the learning of skills and the use of these skills to achieve practical goals?This workshop tackles such questions by bringing together participants from industry (e.g., platforms similar to Odesk, Amazon Mechanical Turk); education, psychology, and MOOCs (e.g., attendees of AERA, EDM, AIED, Learning at Scale); crowdsourcing and collaborative work (e.g., attendees of CHI, CSCW, NIPS, AAAI's HCOMP).

Rising college tuitions are putting increasing financial pressure on families, while at the same time, teachers are repeating tasks like grading and problem creation thousands of times across campuses. Open educational resources (OERs) have the promise of reducing this inefficiency, offering higher quality education at lower cost. However, the adoption of OERs remains limited in part due to issues with organization, quality, search, and fit to the curriculum of individual classrooms. This paper presents a new format for OERs based on a common course skeleton shared among a community of students and instructors. That community jointly creates and improves educational resources around that skeleton. This model resolves many of the classical problems in finding and organizing OERs. We present ways to use such communities to create richer educational resources, such as intelligent tutoring systems (ITS).