WeBuild

Fraser, C. Ailie; Grossman, Tovi; Fitzmaurice, George

doi:10.1145/3025453.3026036

Cited by 10 publications

(1 citation statement)

References 38 publications

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“…They showed that using their adaptive Mini-Me avatar led to-among other results-decreases in task completion time and task difficulty, as well as increases in social presence and preference ratings. Fraser et al (2017) propose a system that supports co-located groups of people in assembly tasks (such as IKEA furniture) by giving personalized work instructions and subdividing the tasks based on workers' skills, dependencies between tasks, and available tools. An external dashboard display is used for a task overview.…”

Section: Adapting Uismentioning

confidence: 99%

A Systematic Review of Personalized Collaborative Systems

Neumayr

Augstein

2020

Front. Comput. Sci.

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Personalization, aiming at supporting users individually, according to their individual needs and prerequisites, has been discussed in a number of domains including learning, search, or information retrieval. In the field of human–computer interaction, personalization also bears high potential as users might exhibit varying and strongly individual preferences and abilities related to interaction. For instance, there is a good amount of work on personalized or adaptive user interfaces (also under the notion of intelligent user interfaces). Personalized human–computer interaction, however, does not only subsume approaches to support the individual user, it also bears high potential if applied to collaborative settings, for example, through supporting the individuals in a group as well as the group itself (considering all of its special dynamics). In collaborative settings (remote or co-located), there generally is a number of additional challenges related to human-to-human collaboration in a group, such as group communication, awareness or territoriality, device or software tool selection, or selection of collaborators. Personalized Collaborative Systems thus attempt to tackle many of these challenges. For instance, there are collaborative systems that recommend tools, content, or team constellations. Such systems have been suggested in different domains and different collaborative settings and contexts. In most cases, these systems explicitly focus on a certain aspect of personalized collaboration support (such as team composition). This article provides a broader, concise overview of existing approaches to Personalized Collaborative Systems based on a systematic literature review considering the ACM Digital Library.

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Section: Adapting Uismentioning

confidence: 99%

A Systematic Review of Personalized Collaborative Systems

Neumayr

Augstein

2020

Front. Comput. Sci.

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Understanding the educators’ practices in makerspaces for the design of education tools

Turakhia,

Ludgin,

Mueller

et al. 2023

Education Tech Research Dev

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Makerspaces persist as formal and informal spaces of learning for youth, promoting continued interest in studying how design can support the variety of learning opportunities within these spaces. However, much of the current research examining learning in makerspaces neglects the perspectives of educators. This not only hinders our understanding of educators’ goals and how educators navigate makerspaces but also constrains how we frame the design space of the learning experiences and environments. To address this, we engaged in a set of semi-structured interviews to examine the contexts, goals, values, and practices of seven educators across five makerspaces. A thematic analysis of the data identified six key categories of competencies that these educators prioritize including a range of skills, practices, and knowledge, such as technical proficiency, communication, and contextual reflection. The analysis also identified five categories of strategies to accomplish certain goals, such as scaffolding, collaboration, and relationship building. Last, it also shed light on three categories of challenges faced at the student-level, teacher-level, and institutional level. We conclude with a discussion on our insights into how we can broaden the problem space in the design of educational technologies to support learning in makerspaces.

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