9,622 research outputs found
Supporting peer interaction in online learning environments
This paper reports two studies into the efficacy of sentence openers to foster online peer-to-peer interaction. Sentence openers are pre-defined ways to start an utterance that are implemented in communication facilities as menuâs or buttons. In the first study, typical opening phrases were derived from naturally occurring online dialogues. The resulting set of sentence openers was implemented in a semi-structured chat tool that allowed students to compose messages in a freetext area or via sentence openers. In the second study, this tool was used to explore the studentsâ appreciation and unprompted use of sentence openers. Results indicate that students hardly used sentence openers and were skeptical of their usefulness. Because both measures were negatively correlated with studentsâ prior chat experience, optional use of sentence openers may not be the best way to support studentsâ online interaction. Based on these findings, alternative ways of using sentence openers are discussed and topics for further research are advanced
Explorations in engagement for humans and robots
This paper explores the concept of engagement, the process by which
individuals in an interaction start, maintain and end their perceived
connection to one another. The paper reports on one aspect of engagement among
human interactors--the effect of tracking faces during an interaction. It also
describes the architecture of a robot that can participate in conversational,
collaborative interactions with engagement gestures. Finally, the paper reports
on findings of experiments with human participants who interacted with a robot
when it either performed or did not perform engagement gestures. Results of the
human-robot studies indicate that people become engaged with robots: they
direct their attention to the robot more often in interactions where engagement
gestures are present, and they find interactions more appropriate when
engagement gestures are present than when they are not.Comment: 31 pages, 5 figures, 3 table
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A corpus-based analysis of route instructions in human-robot interaction
This paper investigates how users employ spatial descriptions to navigate a speech-enabled robot. We created a simulated environment in which users gave route instructions in a dialogic real-time interaction with a robot, which was
operated by naĂŻve participants. The ability of robot monitoring was also manipulated in two experimental conditions. The results provide evidence that the content of the instructions and strategies of the users vary depending on the conditions and
demands of the interaction. As expected, the route instructions frequently were underspecified and arbitrary. The findings of
this study elucidate the complexity in interpreting spatial language in HRI. However, they also point to the need for
endowing mobile robots with richer dialogue resources to compensate for the uncertainties arising from language as well
as the environment
Virtual reality in theatre education and design practice - new developments and applications
The global use of Information and Communication Technologies (ICTs) has already established new approaches to theatre education and research, shifting traditional methods of knowledge delivery towards a more visually enhanced experience, which is especially important for teaching scenography. In this paper, I examine the role of multimedia within the field of theatre studies, with particular focus on the theory and practice of theatre design and education. I discuss various IT applications that have transformed the way we experience, learn and co-create our cultural heritage. I explore a suite of rapidly developing communication and computer-visualization techniques that enable reciprocal exchange between students, theatre performances and artefacts. Eventually, I analyse novel technology-mediated teaching techniques that attempt to provide a new media platform for visually enhanced information transfer. My findings indicate that the recent developments in the personalization of knowledge delivery, and also in student-centred study and e-learning, necessitate the transformation of the learners from passive consumers of digital products to active and creative participants in the learning experience
The RobotCub Approach to the Development of Cognition
This paper elaborates on the workplan of an
initiative in embodied cognition: RobotCub. Our
goal here is to provide background and to
motivate our long-term plan of empirical
research including brain and robotic sciences
following the principles of epigenetic robotics
A collaborative interface agent for Lotus eSuite mail
Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (leaves 79-80).by Ada Hoi-Fay Cheung.S.B.and M.Eng
Symbol Emergence in Robotics: A Survey
Humans can learn the use of language through physical interaction with their
environment and semiotic communication with other people. It is very important
to obtain a computational understanding of how humans can form a symbol system
and obtain semiotic skills through their autonomous mental development.
Recently, many studies have been conducted on the construction of robotic
systems and machine-learning methods that can learn the use of language through
embodied multimodal interaction with their environment and other systems.
Understanding human social interactions and developing a robot that can
smoothly communicate with human users in the long term, requires an
understanding of the dynamics of symbol systems and is crucially important. The
embodied cognition and social interaction of participants gradually change a
symbol system in a constructive manner. In this paper, we introduce a field of
research called symbol emergence in robotics (SER). SER is a constructive
approach towards an emergent symbol system. The emergent symbol system is
socially self-organized through both semiotic communications and physical
interactions with autonomous cognitive developmental agents, i.e., humans and
developmental robots. Specifically, we describe some state-of-art research
topics concerning SER, e.g., multimodal categorization, word discovery, and a
double articulation analysis, that enable a robot to obtain words and their
embodied meanings from raw sensory--motor information, including visual
information, haptic information, auditory information, and acoustic speech
signals, in a totally unsupervised manner. Finally, we suggest future
directions of research in SER.Comment: submitted to Advanced Robotic
CollabCoder: A GPT-Powered Workflow for Collaborative Qualitative Analysis
The Collaborative Qualitative Analysis (CQA) process can be time-consuming
and resource-intensive, requiring multiple discussions among team members to
refine codes and ideas before reaching a consensus. To address these
challenges, we introduce CollabCoder, a system leveraging Large Language Models
(LLMs) to support three CQA stages: independent open coding, iterative
discussions, and the development of a final codebook. In the independent open
coding phase, CollabCoder provides AI-generated code suggestions on demand, and
allows users to record coding decision-making information (e.g. keywords and
certainty) as support for the process. During the discussion phase, CollabCoder
helps to build mutual understanding and productive discussion by sharing coding
decision-making information with the team. It also helps to quickly identify
agreements and disagreements through quantitative metrics, in order to build a
final consensus. During the code grouping phase, CollabCoder employs a top-down
approach for primary code group recommendations, reducing the cognitive burden
of generating the final codebook. An evaluation involving 16 users confirmed
the usability and effectiveness of CollabCoder and offered empirical insights
into the LLMs' roles in CQA
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