Integrating citizen science with online learning to ask better questions
This work addresses the challenge of enhancing engagement and learning outcomes for online learners by integrating them into citizen science projects, though it appears incremental as it builds on existing crowdsourcing and serious games frameworks.
The paper tackles the problem of online learners engaging with assignments that have known answers by proposing a citizen science approach where learners generate hypotheses about the human gut microbiome, aiming to produce novel knowledge and increase motivation through real-world contributions.
Online learners spend millions of hours per year testing their new skills on assignments with known answers. This paper explores whether framing research questions as assignments with unknown answers helps learners generate novel, useful, and difficult-to-find knowledge while increasing their motivation by contributing to a larger goal. Collaborating with the American Gut Project, the world's largest crowdfunded citizen science project, we deploy Gut Instinct to allow novices to generate hypotheses about the constitution of the human gut microbiome. The tool enables online learners to explore learning material about the microbiome and create their own theories around causal variances for microbiome. Building on crowdsourcing or serious games that use people as replaceable units, this work-in-progress lays our plans for how people (a) use their personal knowledge (b) towards solving a larger real-world goal (c) that can provide potential benefits to them. We hope to demonstrate that Gut Instinct citizen scientists generate useful hypotheses, perform better on learning tasks than traditional MOOC learners, and are better engaged with the learning material.