Promoting Erroneous Divergent Opinions Increases the Wisdom of Crowds

The aggregation of many lay judgments generates surprisingly accurate estimates. This phenomenon, called the "wisdom of crowds," has been demonstrated in domains such as medical decision-making and financial forecasting. Previous research identified two factors driving this effect: the accuracy of individual assessments and the diversity of opinions. Most available strategies to enhance the wisdom of crowds have focused on improving individual accuracy while neglecting the potential of increasing opinion diversity. Here, we study a complementary approach to reduce collective error by promoting erroneous divergent opinions. This strategy proposes to anchor half of the crowd to a small value and the other half to a large value before eliciting and averaging all estimates. Consistent with our mathematical modeling, four experiments (N = 1,362 adults) demonstrated that this method is effective for estimation and forecasting tasks. Beyond the practical implications, these findings offer new theoretical insights into the epistemic value of collective decision-making.

Leveraging collective action and environmental literacy to address complex sustainability challenges

Developing and enhancing societal capacity to understand, debate elements of, and take actionable steps toward a sustainable future at a scale beyond the individual are critical when addressing sustainability challenges such as climate change, resource scarcity, biodiversity loss, and zoonotic disease. Although mounting evidence exists for how to facilitate individual action to address sustainability challenges, there is less understanding of how to foster collective action in this realm. To support research and practice promoting collective action to address sustainability issues, we define the term "collective environmental literacy" by delineating four key potent aspects: scale, dynamic processes, shared resources, and synergy. Building on existing collective constructs and thought, we highlight areas where researchers, practitioners, and policymakers can support individuals and communities as they come together to identify, develop, and implement solutions to wicked problems. We close by discussing limitations of this work and future directions in studying collective environmental literacy.

Understanding crowdsourcing in science

Over the past 16 years, the concept of crowdsourcing has rapidly gained traction across many research fields. While related debates focused mainly on its importance for business, the public and non-governmental sectors, its relevance for generating scientific knowledge is increasingly emphasized. This rising interest remains in contradiction with its feeble recognition, and excessive simplifications reducing crowdsourcing in science to citizen science. Conceptual clarity and a coherent framework would help integrate the various research streams. The aim of this paper is to extend reflection on crowdsourcing in science by analyzing the characteristics of the phenomenon. We synthesize a consensual definition from the literature, and structure key characteristics into a coherent framework, useful in guiding further research. We use a systematic literature review procedure to generate a pool of 42 definitions from a comprehensive set of 62 articles spanning different literatures, including: business and economics, education, psychology, biology, and communication studies. We follow a mixed-method approach that combines bibliometric and frequency analyses with deductive coding and thematic analysis. Based on triangulated results we develop an integrative definition: crowdsourcing in science is a collaborative online process through which scientists involve a group of self-selected individuals of varying, diverse knowledge and skills, via an open call to the Internet and/or online platforms, to undertake a specified research task or set of tasks. We also provide a conceptual framework that covers four key characteristics: initiator, crowd, process, and technology.

Towards a typology development of crowdsourcing in science

Crowdsourcing in science as collaborative online process through which non-professional and/or professional scientists incorporate a group of individuals of varying, diversity knowledge and skills, via an open call to the Internet and/or online platforms, to undertaking of a task in science, is an important strategy to support scientific research that has gained attention in academia and practitioners. While research efforts to date have focused on the benefits of crowdsourcing in science, its typology has yet to mature. Typologies are important in describing complex, multidisciplinary organisational forms such as crowdsourcing in science. The main purpose of this article is to identify and provide a typology of crowdsourcing in science. Based on the thematic analysis of publications collected in a systematic manner and focused group interviews, 12 types of crowdsourcing in science are identified. The proposed crowdsourcing in science typology matrix may be a starting point for future research and decision-making by practitioners regarding the choice of a specific type of crowdsourcing in science.

A Sociomaterial Lens on Crowdsourcing for Learning

Crowdsourcing is increasingly being applied in educational contexts to explore the ideation and problem-solving capacity of large, networked groups. Research is emerging on the use of crowdsourcing in education, yet little is known about how the particular affordances of crowdsourcing platforms facilitate student learning. This paper applies sociomaterial theory to analysing a case study of a crowdsourcing experiment undertaken at the University of Sydney. It reflects on the crowdsourcing experiment as an assemblage of different relations, dynamics and materials, building on a recent typology for analysing social learning software through a sociomaterial lens. We contribute to the growing discourse around sociomaterial approaches by exploring how the material affordances of a unique online learning environment participate to produce certain kinds of learning experiences. This supports future research into the potentialities of crowdsourcing pedagogies at a time when increased online and blended learning brought about by the Covid-19 pandemic has galvanised educators’ interest in exploring different online environments and approaches.