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Peer production projects involve people in many tasks, from editing articles to analyzing datasets. To facilitate mastery of these practices, projects offer a number of learning resources, ranging from project-defined FAQsto individually-oriented search tools and communal discussion boards. However, it is not clear which project resources best support participant learning, overall and at different stages of engagement. We draw onSørensen's framework of forms of presence to distinguish three types of engagement with learning resources:authoritative, agent-centered and communal. We assigned resources from the Gravity Spy citizen-science into these three categories and analyzed trace data recording interactions with resources using a mixed-effects logistic regression with volunteer performance as an outcome variable. The findings suggest that engagement with authoritative resources (e.g., those constructed by project organizers) facilitates performance initially. However, as tasks become more difficult, volunteers seek and benefit from engagement with their own agent-centered resources and community-generated resources. These findings suggest a broader scope for the design of learning resources for peer production

Researchers studying user behaviors in online communities often conduct analyses of user interaction data recorded in system logs e.g., an edit in Wikipedia. Such analysis relies on collating interactions by a unique identifier such as a user ID. However, if users can contribute without being logged-in (i.e., anonymously) analysis of interaction data omit part of a user's experience. Problematically, anonymous traces are unlikely to be randomly distributed, so their omission can change statistical conclusions, with implications for both research and practice. To understand the impacts on conclusions of leaving out anonymous traces, we conducted an analysis of system logs from two online citizen science projects. Attributing anonymous traces with user IDs, we found that (1) many users contribute anonymously, though with varied patterns; and (2) attributing anonymous traces diminishes empirical evidence used to support theory and change the results of system algorithms. These results suggest anonymous traces have implications for research on user behaviors and the practices associated with using such data to tailor user experiences in online communities.

Existing literature points to scaffolded training as an effective yet resource-intensive approach to help newcomers learn and stay motivated. Experts need to select relevant learning materials and continuously assess learners' progress. Peer production communities such as Wikipedia and Open Source Software Development projects face the additional problem of turning volunteers into productive participants as soon as possible. To address these challenges, we designed and tested a training regime combining scaffolded instruction and machine learning to select learning materials and gradually introduces new materials to individuals as their competences improve. We evaluated the training regime on 386 participants that contribute to Gravity Spy, an online citizen science project where people are asked to categorize glitches to assist scientists in the search for gravitational waves. Volunteers were assigned to one of two conditions; (1) a machine learning guided training (MLGT) system that continuously assesses volunteers skill level and adjusts the learning materials or (2) an unscaffolded training program where all learning materials were administered at once. Our analysis revealed that volunteers in the MLGT condition were more accurate on the categorization task (an average accuracy of 90% vs. 54%), executed more tasks (an average of 228 vs. 121 tasks), and were retained for a longer period (an average of 2.5 vs. 2 sessions) than volunteers in the unscaffolded training. The results suggest that MLGT is an effective pedagogical approach for training volunteers in categorization tasks and increases volunteers’ motivation.

Increasingly, citizen scientists do work beyond the primary goal of the project (i.e., advanced work) such as writing articles. These activities often take place in discussion boards and have a set of linguistic norms for contributing. For newcomers, learning this language presents a challenge since there are no formal opportunities for them to learn the language and volunteers who join later need to learn more than volunteers who join earlier in a project life-cycle. In this poster, we examine how newcomers language use shifts over the course of two citizen science projects. We find that, although, newcomers joining later might face obstacles, newcomer language associated with advanced work increase over the project's life-cycle. The analysis can help the science team assess whether newcomers on the talk page have either adopted advanced terminologies or they need to have a more formal resource such as tutorial or blog posts.

In this paper, we describe the results of an online field experiment examining the impacts of messaging about task novelty on the volume of volunteers' contributions to an online citizen science project. Encouraging volunteers to provide a little more content as they work is an attractive strategy to increase the community's output. Prior research found that an important motivation for participation in online citizen science is the wonder of being the first person to observe a particular image. To appeal to this motivation, a pop-up message was added to an online citizen science project that alerted volunteers when they were the first to annotate a particular image. Our analysis reveals that new volunteers who saw these messages increased the volume of annotations they contributed. The results of our study suggest an additional strategy to increase the amount of work volunteers contribute to online communities and citizen science projects specifically.

Research on newcomer roles in peer production sites (e.g., Wikipedia) is characterized by a broad and relatively well articulated set of functionally and culturally recognizable roles. But not all communities come with well-defined roles that newcomers can aspire to occupy. The present study explores activity clusters newcomers create when faced with few recognizable roles to fill and limited access to other participants' work that serves as an exemplar. Drawing on a mixed method research design, we present findings from an analysis of 1,687 newcomers' sessions in an online citizen science project. Our analysis revealed three major findings: (1) newcomers' activities exists across six session types; (2) newcomers toggle between light work sessions and more involved types of production or community engagement; (3) high-level contributors contribute large volumes of work but comment very little and another group contributes large volumes of comments, but works very little. The former group draws heavily on posts contributed by the latter group. Identifying shifts and regularities in contribution facilitate improved mechanisms for engaging participants and for the design of online citizen science communities.

This paper describes the results of an online field exper-iment where we designed and analyzed the effects of a goal-setting tracker in an online citizen science project -Floating Forest. The design of our tracker was influenced by psychology theories of anchoring and goal-setting. Our results of our experiment revealed: (1) setting goals increases annotations in a session; (2) numeric anchors influence goals; and (3) participants in the treatment who saw a prompt but did not set a goal, contributed more an-notations than the participants in the control group. Our research shows how goal-setting and anchoring combine to increase work in online communities.

How online community members learn to become valuable contributors constitutes a long-standing concern of Community & Technology researchers. The literature tends to highlight participants' access to practice, feedback from experienced members, and relationship building. However, not all crowdsourcing environments offer participants opportunities for access, feedback, and relationship building (e.g., Citizen Science). We study how volunteers learn to participate in a citizen science project, Planet Hunters, through participant observation, interviews, and trace ethnography. Drawing on Sorensen's sociomaterial theories of presence, we extend the notion of situated learning to include several modes of learning. The empirical findings suggest that volunteers in citizen science engage more than one form of access to practice, feedback, and relationship building. Communal relations characterize only one form of learning. Equally important to their learning are authority--subject and agent-centered forms of access, feedback, and relationship building.

The paper explores the motivations of volunteers in a large crowd sourcing project and contributes to our understanding of the motivational factors that lead to deeper engagement beyond initial participation. Drawing on the theory of legitimate peripheral participation (LPP) and the literature on motivation in crowd sourcing, we analyze interview and trace data from a large citizen science project. The analyses identify ways in which the technical features of the projects may serve as motivational factors leading participants towards sustained participation. The results suggest volunteers first engage in activities to support knowledge acquisition and later share knowledge with other volunteers and finally increase participation in Talk through a punctuated process of role discovery.

Making visible the process of user participation in online crowdsourced initiatives has been shown to help new users understand the norms of participation [2]. However, in many settings, participants lack full access to others' work. Merging the theory of legitimate peripheral participation [18] with Erickson and Kellogg's theory of social translucence [10, 11, 16] we introduce the concept of practice proxies: traces of user participation in online environments that act as resources to orient newcomers towards the norms of practice. Through a combination of virtual [14] and trace ethnography [12] we explore how new users in two online citizen science projects engage with these traces of practice as a way of compensating for a lack of access to the process of the work itself. Our findings suggest that newcomers seek out practice proxies in the social features of the projects that highlight contextualized and specific characteristics of primary work practice.

Crowdsourced initiatives rely on contributions from experienced and non-experienced contributors rather than on permanent workers. Such new organizational forms challenge existing theories of organ...

An FPGA-based digital-receiver has been developed for a low-frequency imaging radio interferometer, the Murchison Widefield Array (MWA). The MWA, located at the Murchison Radio-astronomy Observatory (MRO) in Western Australia, consists of 128 dual-polarized aperture-array elements (tiles) operating between 80 and 300\,MHz, with a total processed bandwidth of 30.72 MHz for each polarization. Radio-frequency signals from the tiles are amplified and band limited using analog signal conditioning units; sampled and channelized by digital-receivers. The signals from eight tiles are processed by a single digital-receiver, thus requiring 16 digital-receivers for the MWA. The main function of the digital-receivers is to digitize the broad-band signals from each tile, channelize them to form the sky-band, and transport it through optical fibers to a centrally located correlator for further processing. The digital-receiver firmware also implements functions to measure the signal power, perform power equalization across the band, detect interference-like events, and invoke diagnostic modes. The digital-receiver is controlled by high-level programs running on a single-board-computer. This paper presents the digital-receiver design, implementation, current status, and plans for future enhancements., Comment: 14 pages, 7 figures

Using the final 128 antenna locations of the Murchison Widefield Array (MWA), we calculate its sensitivity to the epoch of reionization (EoR) power spectrum of redshifted 21 cm emission for a fiducial model and provide the tools to calculate the sensitivity for any model. Our calculation takes into account synthesis rotation, chromatic and asymmetrical baseline effects, and excludes modes that will be contaminated by foreground subtraction. For the fiducial model, the MWA will be capable of a 14σ detection of the EoR signal with one full season of observation on two fields (900 and 700 h)., National Science Foundation (U.S.) (Grant AST CAREER-0847753), National Science Foundation (U.S.) (Grant AST-0457585), National Science Foundation (U.S.) (Grant AST-0908884), National Science Foundation (U.S.) (Grant PHY-0835713), United States. Air Force Office of Scientific Research (Grant FA9550-0510247), Smithsonian Astrophysical Observatory, MIT School of Science

The Murchison Widefield Array (MWA) is a Square Kilometre Array (SKA) Precursor. The telescope is located at the Murchison Radio--astronomy Observatory (MRO) in Western Australia (WA). The MWA consists of 4096 dipoles arranged into 128 dual polarisation aperture arrays forming a connected element interferometer that cross-correlates signals from all 256 inputs. A hybrid approach to the correlation task is employed, with some processing stages being performed by bespoke hardware, based on Field Programmable Gate Arrays (FPGAs), and others by Graphics Processing Units (GPUs) housed in general purpose rack mounted servers. The correlation capability required is approximately 8 TFLOPS (Tera FLoating point Operations Per Second). The MWA has commenced operations and the correlator is generating 8.3 TB/day of correlation products, that are subsequently transferred 700 km from the MRO to Perth (WA) in real-time for storage and offline processing. In this paper we outline the correlator design, signal path, and processing elements and present the data format for the internal and external interfaces., Comment: 17 pages, 9 figures. Accepted for publication in PASA. Some figures altered to meet astro-ph submission requirements

The Murchison Widefield Array (MWA) is one of three Square Kilometre Array Precursor telescopes and is located at the Murchison Radio-astronomy Observatory in the Murchison Shire of the mid-west of Western Australia, a location chosen for its extremely low levels of radio frequency interference. The MWA operates at low radio frequencies, 80–300 MHz, with a processed bandwidth of 30.72 MHz for both linear polarisations, and consists of 128 aperture arrays (known as tiles) distributed over a ~3-km diameter area. Novel hybrid hardware/software correlation and a real-time imaging and calibration systems comprise the MWA signal processing backend. In this paper, the as-built MWA is described both at a system and sub-system level, the expected performance of the array is presented, and the science goals of the instrument are summarised., National Science Foundation (U.S.) (Grant AST CAREER-0847753), National Science Foundation (U.S.) (Grant AST-0457585), National Science Foundation (U.S.) (Grant AST-0908884), National Science Foundation (U.S.) (Grant PHY-0835713), United States. Air Force Office of Scientific Research (Grant FA9550-0510247), Smithsonian Astrophysical Observatory, MIT School of Science

The Murchison Wide-Field Array (MWA) is a low-frequency radio telescope, currently under construction, intended to search for the spectral signature of the epoch of reionization (EOR) and to probe the structure of the solar corona. Sited in western Australia, the full MWA will comprise 8192 dipoles grouped into 512 tiles and will be capable of imaging the sky south of 40° declination, from 80 MHz to 300 MHz with an instantaneous field of view that is tens of degrees wide and a resolution of a few arcminutes. A 32 station prototype of the MWA has been recently commissioned and a set of observations has been taken that exercise the whole acquisition and processing pipeline. We present Stokes I, Q, and U images from two ~4 hr integrations of a field 20° wide centered on Pictoris A. These images demonstrate the capacity and stability of a real-time calibration and imaging technique employing the weighted addition of warped snapshots to counter extreme wide-field imaging distortions., National Science Foundation (U.S.) (Grant AST-0457585), National Science Foundation (U.S.) (Grant PHY-0835713), Australian Research Council (Grant LE0775621), Australian Research Council (Grant LE0882938), United States. Air Force Office of Scientific Research (Grant FA9550-0510247), MIT School of Science