- Building learning communities
- Collaboratively organizing knowledge
- Connecting prior knowledge to new knowledge
- Facilitating peer evaluation of other's work
- Generating high-quality MCQs for retrieval practice


1Cademy's Objectives

University of Michigan - Ann Arbor

We have iteratively designed and developed a knowledge mapping platform, 1Cademy, to meet two objectives: 
- Large-Scale Knowledge Representation
- Asynchronous Collaborative Development

1Cademy: A Learnersourcing Platform to Collaboratively Summarize, Visualize, Evaluate, and Improve Knowledge

We conducted a field-study over ten weeks, where 29 undergraduate and graduate students collaboratively summarized two data science textbooks and some recent research papers. They created 934 nodes. Of these, 573 were leaf nodes with no children; among non-leaf nodes, on average each was identified as a prerequisite of 2.66 other nodes. Students submitted a total of 2,131 proposals, including 721 for edits to nodes and 1,410 for revisions to links.

1Cademy's Field-Study

1Cademy: A Visual, Learner-oriented Wikipedia

Over the 10 weeks of the field trial, the knowledge map grew to 934 nodes. This scale is made possible through:
- The hybrid content structure
- The ability to personalize the map view

Large-Scale Knowledge Representation

Throughout the semester, the 29 students collaborated to make 2,131 proposals for revisions to the map, improving the community's learning. This was accomplished through:
- The democratic peer review process
- The proposal mechanism
- The linking constraint

Learn Before

Related

Learn After