For a number of years now, labor-intensive DH projects–especially those involving text editing and transcription, data tagging and markup, image and text analysis, metadata and data creation, etc.–have incorporated crowd sourcing tools and methods into their workflows. In this session, we propose that participants investigate, discuss, demonstrate, or design methods for integrating this DH building work into teaching practices and student learning objectives. What are best practices for incorporating DH-scholarship into the classes we all teach or facilitate as members of the academic community? How technical can these projects be? How can DH-crowdsourcing engage students at multiple levels of humanistic study? In what ways can involvement in DH-crowdsourcing projects develop students’ academic skills both within and beyond the scope of a particular humanistic discipline? How can DH projects open themselves up to pedagogy in the most productive ways (without sacrificing quality work)? And what ethical standards should we use when we incorporate student labor into our projects?
