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Register a new userConnected Learning, Collapsed Contexts
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Added by
Caroline Pitt
Publication date
2021
fields
Informatics Engineering
and research's language is
English
Authors
Caroline Pitt
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Researchers and designers have incorporated social media affordances into learning technologies to engage young people and support personally relevant learning, but youth may reject these attempts because they do not meet user expectations. Through in-depth case studies, we explore the sociotechnical ecosystems of six teens (ages 15-18) working at a science center that had recently introduced a digital badge system to track and recognize their learning. By analyzing interviews, observations, ecological momentary assessments, and system data, we examined tensions in how badges as connected learning technologies operate in teens sociotechnical ecosystems. We found that, due to issues of unwanted context collapse and incongruent identity representations, youth only used certain affordances of the system and did so sporadically. Additionally, we noted that some features seemed to prioritize values of adult stakeholders over youth. Using badges as a lens, we reveal critical tensions and offer design recommendations for networked learning technologies.
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Curiosity is a vital metacognitive skill in educational contexts. Yet, little is known about how social factors influence curiosity in group work. We argue that curiosity is evoked not only through individual, but also interpersonal activities, and present what we believe to be the first theoretical framework that articulates an integrated socio-cognitive account of curiosity based on literature spanning psychology, learning sciences and group dynamics, along with empirical observation of small-group science activity in an informal learning environment. We make a bipartite distinction between individual and interpersonal functions that contribute to curiosity, and multimodal behaviors that fulfill these functions. We validate the proposed framework by leveraging a longitudinal latent variable modeling approach. Findings confirm positive predictive relationship of the latent variables of individual and interpersonal functions on curiosity, with the interpersonal functions exercising a comparatively stronger influence. Prominent behavioral realizations of these functions are also discovered in a data-driven way. This framework is a step towards designing learning technologies that can recognize and evoke curiosity during learning in social contexts.
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With the development of advanced communication technology, connected vehicles become increasingly popular in our transportation systems, which can conduct cooperative maneuvers with each other as well as road entities through vehicle-to-everything communication. A lot of research interests have been drawn to other building blocks of a connected vehicle system, such as communication, planning, and control. However, less research studies were focused on the human-machine cooperation and interface, namely how to visualize the guidance information to the driver as an advanced driver-assistance system (ADAS). In this study, we propose an augmented reality (AR)-based ADAS, which visualizes the guidance information calculated cooperatively by multiple connected vehicles. An unsignalized intersection scenario is adopted as the use case of this system, where the driver can drive the connected vehicle crossing the intersection under the AR guidance, without any full stop at the intersection. A simulation environment is built in Unity game engine based on the road network of San Francisco, and human-in-the-loop (HITL) simulation is conducted to validate the effectiveness of our proposed system regarding travel time and energy consumption.
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