Nguyen is specializing in Teaching, Learning, and Educational Improvement for her doctoral work. Her research interests include design of STEM learning experiences and multimodal assessment to study collaboration and conceptual understanding. She is advised by Professors Mark Warschauer and Rossella Santagata.
Ahn studies learning technologies, research-practice partnerships, human-computer interaction, educational technology, and data use and analytics. His core research interest is understanding how technology and information can enhance the way we learn and deliver education. He serves as faculty director for the Orange County Educational Advancement Network (OCEAN).
Crowdsourcing has shown promise in education domains. For example, researchers have leveraged the wisdom of the crowd to process grading in MOOCs and develop learning resources. An untapped domain is harnessing the crowd to systematically process educational data in classrooms -- data that provide key instructional insights but take time to process, such as paper-based assessments. In this paper, we describe an experiment of a crowdsourcing task to effectively process classroom-based data and explore the potential of crowdsourcing as a learning opportunity for the crowdworkers. We discuss implications for designing crowdsourced assessment tasks to yield both high quality output and enriching learning experiences for those involved in the crowdsourcing task.