Search for: All records

Phenological response to global climate change can impact ecosystem functions. There are various data sources from which spatiotemporal and taxonomic phenological data may be obtained: mobilized herbaria, community science initiatives, observatory networks, and remote sensing. However, analyses conducted to date have generally relied on single sources of these data. Siloed treatment of data in analyses may be due to the lack of harmonization across different data sources that offer partially nonoverlapping information and are often complementary. Such treatment precludes a deeper understanding of phenological responses at varying macroecological scales. Here, we describe a detailed vision for the harmonization of phenological data, including the direct integration of disparate sources of phenological data using a common schema. Specifically, we highlight existing methods for data harmonization that can be applied to phenological data: data design patterns, metadata standards, and ontologies. We describe how harmonized data from multiple sources can be integrated into analyses using existing methods and discuss the use of automated extraction techniques. Data harmonization is not a new concept in ecology, but the harmonization of phenological data is overdue.We aim to highlight the need for better data harmonization, providing a roadmap for how harmonized phenological data may fill gaps while simultaneously being integrated into analyses. 

Attempting the hands-on activities typical of makerspaces without in-person expert facilitation can lead to frustration and decreased engagement. This study aims to explore the collaboration affordances of REACH, a novel communication device that allows users to share gestures around a common artifact while in separate locations. Using a modified version of the divergent collaborative learning mechanisms framework (DCLM), this paper highlights the affordances of REACH to support students in collaboratively engaging in joint attention and boundary spanning perception and action, even when they are physically disparate. 

In education, we cherish success and fear failure. But not every learning experience is a success right away, in fact failing and making mistakes and then learning from them is the norm rather than the exception. In this symposium, we present different perspectives on how failure can contribute to constructionist learning and teaching, examining how learners identify and address failures in their designs and how distinct approaches to failure can support learners in collaboratively creating personally meaningful projects. Taking a holistic approach to failure—that incorporates cognitive, social, and affective factors—we argue that failure should play a key role in constructionism and present different perspectives for finding a more productive stance that turns failures into rich opportunities for constructionist learning and teaching. 

Abstract The CMS collaboration is building a new inner tracking pixel detector for the High-Luminosity LHC. Each pixel readout chip will be controlled with a single serial input stream at 160 Mb/s and will send out data via four current mode logic (CML) 1.28 Gb/s outputs. The readout chips will be grouped in modules and connected with up to 1.6 meters long low-mass electrical links to Low-Power Gigabit Transceivers (lpGBT) and Versatile Link PLUS Transceiver (VTRx+) modules that send the data optically to off-detector electronics at 10 Gb/s. The characterization of these components and system tests of the readout chain are presented. 

Bots are increasingly being used for governance-related purposes in online communities, yet no instrumentation exists for measuring how users assess their beneficial or detrimental impacts. In order to support future human-centered and community-based research, we developed a new scale called GOVernance Bots in Online communiTies (GOV-BOTs) across two rounds of surveys on Reddit (N=820). We applied rigorous psychometric criteria to demonstrate the validity of GOV-BOTs, which contains two subscales: bot governance (4 items) and bot tensions (3 items). Whereas humans have historically expected communities to be composed entirely of humans, the social participation of bots as non-human agents now raises fundamental questions about psychological, philosophical, and ethical implications. Addressing psychological impacts, our data show that perceptions of effective bot governance positively contribute to users' sense of virtual community (SOVC), whereas perceived bot tensions may only impact SOVC if users are more aware of bots. Finally, we show that users tend to experience the greatest SOVC across groups of subreddits, rather than individual subreddits, suggesting that future research should carefully re-consider uses and operationalizations of the term community. 

Maker activities help students connect to STEAM content through hands-on activities that emphasize the roles of mentors, peers, and in-person interaction with physical artifacts. Despite the positive affordances of these activities, they do not translate well to online settings. Without immediate in-person feedback mechanisms, unstructured making activities may lead to frustration and decreased engagement. How do communities help students develop identities as future engineers if local help and mentorship is not available? The proposed study aims to address challenges of scaffolding collaboration during remote maker sessions through investigation of a novel projection device that allows users to talk & share gestures around a common physical artifact while in separate locations. 

Structured data peer production (SDPP) platforms like Wikidata play an important role in knowledge production. Compared to traditional peer production platforms like Wikipedia, Wikidata data is more structured and intended to be used by machines, not (directly) by people; end-user interactions with Wikidata often happen through intermediary "invisible machines." Given this distinction, we wanted to understand Wikidata contributor motivations and how they are affected by usage invisibility caused by the machine intermediaries. Through an inductive thematic analysis of 15 interviews, we find that: (i) Wikidata editors take on two archetypes---Architects who define the ontological infrastructure of Wikidata, and Masons who build the database through data entry and editing; (ii) the structured nature of Wikidata reveals novel editor motivations, such as an innate drive for organizational work; (iii) most Wikidata editors have little understanding of how their contributions are used, which may demotivate some. We synthesize these insights to help guide the future design of SDPP platforms in supporting the engagement of different types of editors.