2,434 research outputs found
The Challenges in Modeling Human Performance in 3D Space with Fittsâ Law
With the rapid growth in virtual reality technologies, object interaction is
becoming increasingly more immersive, elucidating human perception and leading
to promising directions towards evaluating human performance under different
settings. This spike in technological growth exponentially increased the need
for a human performance metric in 3D space. Fitts' law is perhaps the most
widely used human prediction model in HCI history attempting to capture human
movement in lower dimensions. Despite the collective effort towards deriving an
advanced extension of a 3D human performance model based on Fitts' law, a
standardized metric is still missing. Moreover, most of the extensions to date
assume or limit their findings to certain settings, effectively disregarding
important variables that are fundamental to 3D object interaction. In this
review, we investigate and analyze the most prominent extensions of Fitts' law
and compare their characteristics pinpointing to potentially important aspects
for deriving a higher-dimensional performance model. Lastly, we mention the
complexities, frontiers as well as potential challenges that may lay ahead.Comment: Accepted at ACM CHI 2021 Conference on Human Factors in Computing
Systems (CHI '21 Extended Abstracts
Combining relevance information in a synchronous collaborative information retrieval environment
Traditionally information retrieval (IR) research has focussed on a single user interaction modality, where a user searches to satisfy an information need. Recent
advances in both web technologies, such as the sociable web of Web 2.0, and computer hardware, such as tabletop interface devices, have enabled multiple users to collaborate on many computer-related tasks. Due to these advances there is an increasing need to support
two or more users searching together at the same time, in order to satisfy a shared information need, which we refer to as Synchronous Collaborative Information Retrieval.
Synchronous Collaborative Information Retrieval (SCIR) represents a significant paradigmatic shift from traditional IR systems. In order to support an effective SCIR search, new techniques are required to coordinate users' activities. In this chapter we explore the effectiveness of a sharing of knowledge policy on a collaborating group. Sharing of knowledge refers to the process of passing relevance information across users,
if one user finds items of relevance to the search task then the group should benefit in the form of improved ranked lists returned to each searcher.
In order to evaluate the proposed techniques we simulate two users searching together through an incremental feedback system. The simulation assumes that users decide on an initial query with which to begin the collaborative search and proceed through the search by providing relevance judgments to the system and receiving a new ranked list. In order to populate these simulations we extract data from the interaction logs of various
experimental IR systems from previous Text REtrieval Conference (TREC) workshops
Next Steps for Human-Computer Integration
Human-Computer Integration (HInt) is an emerging paradigm in which computational and human systems are closely interwoven. Integrating computers with the human body is not new. however, we believe that with rapid technological advancements, increasing real-world deployments, and growing ethical and societal implications, it is critical to identify an agenda for future research. We present a set of challenges for HInt research, formulated over the course of a five-day workshop consisting of 29 experts who have designed, deployed and studied HInt systems. This agenda aims to guide researchers in a structured way towards a more coordinated and conscientious future of human-computer integration
Next steps for Human-Computer Integration
Human-Computer Integration (HInt) is an emerging paradigm in which computational and human systems are closely interwoven. Integrating computers with the human body is not new. However, we believe that with rapid technological advancements, increasing real-world deployments, and growing ethical and societal implications, it is critical to identify an agenda for future research. We present a set of challenges for HInt research, formulated over the course of a five-day workshop consisting of 29 experts who have designed, deployed, and studied HInt systems. This agenda aims to guide researchers in a structured way towards a more coordinated and conscientious future of human-computer integration
Scim: Intelligent Skimming Support for Scientific Papers
Researchers need to keep up with immense literatures, though it is
time-consuming and difficult to do so. In this paper, we investigate the role
that intelligent interfaces can play in helping researchers skim papers, that
is, rapidly reviewing a paper to attain a cursory understanding of its
contents. After conducting formative interviews and a design probe, we suggest
that skimming aids should aim to thread the needle of highlighting content that
is simultaneously diverse, evenly-distributed, and important. We introduce
Scim, a novel intelligent skimming interface that reifies this aim, designed to
support the skimming process by highlighting salient paper contents to direct a
skimmer's focus. Key to the design is that the highlights are faceted by
content type, evenly-distributed across a paper, with a density configurable by
readers at both the global and local level. We evaluate Scim with an in-lab
usability study and deployment study, revealing how skimming aids can support
readers throughout the skimming experience and yielding design considerations
and tensions for the design of future intelligent skimming tools
Revisiting revisitation in computer interaction: organic bookmark management.
According to Milic-Frayling et al. (2004), there are two general ways of user browsing i.e. search (finding a website where the user has never visited before) and revisitation (returning to a website where the user has visited in the past). The issue of search is relevant to search engine technology, whilst revisitation concerns web usage and browser history mechanisms. The support for revisitation is normally through a set of functional built-in icons e.g. History, Back, Forward and Bookmarks. Nevertheless, for returning web users, they normally find it is easier and faster to re-launch an online search again, rather than spending time to find a particular web site from their personal bookmark and history records. Tauscher and Greenberg (1997) showed that revisiting web pages forms up to 58% of the recurrence rate of web browsing. Cockburn and McKenzie (2001) also stated that 81% of web pages have been previously visited by the user. According to Obendorf et al. (2007), revisitation can be divided into four classifications based on time: short-term (72.6% revisits within an hour), medium-term (12% revisits within a day and 7.8% revisits within a week), and long-term (7.6% revisits longer than a week)
Computational Adaptation of XR Interfaces Through Interaction Simulation
Adaptive and intelligent user interfaces have been proposed as a critical
component of a successful extended reality (XR) system. In particular, a
predictive system can make inferences about a user and provide them with
task-relevant recommendations or adaptations. However, we believe such adaptive
interfaces should carefully consider the overall \emph{cost} of interactions to
better address uncertainty of predictions. In this position paper, we discuss a
computational approach to adapt XR interfaces, with the goal of improving user
experience and performance. Our novel model, applied to menu selection tasks,
simulates user interactions by considering both cognitive and motor costs. In
contrast to greedy algorithms that adapt based on predictions alone, our model
holistically accounts for costs and benefits of adaptations towards adapting
the interface and providing optimal recommendations to the user.Comment: 5 pages, 1 figure, 1 table. CHI 2022 Workshop on Computational
Approaches for Understanding, Generating, and Adapting User Interface
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