Integrating citizen science with online learning to ask better questions

TL;DR

This paper investigates whether framing research questions as assignments with unknown answers enhances online learners' motivation and ability to generate novel hypotheses, using a citizen science platform about the human gut microbiome.

Contribution

It introduces Gut Instinct, a tool that integrates citizen science with online learning to foster hypothesis generation and engagement in microbiome research.

Findings

Learners generate useful hypotheses about the microbiome.

Participants perform better on learning tasks than traditional MOOC students.

Increased engagement with learning material observed.

Abstract

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.