Determining a Framework for the Generation and Evaluation of Ambient Intelligent Agent System Designs

Pavlović, Milica; Kotsopoulos, Sotirios D.; Lim, Yihyun; Penman, Scott; Colombo, Sara; Casalegno, Federico

doi:10.1007/978-3-030-32520-6_26

Cited by 8 publications

(2 citation statements)

References 36 publications

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“…Another framework, aimed at assisting the design and evaluation of IEs [26], proposes using storytelling videos to describe and communicate the user values and design scenarios to stakeholders, and then generating design proposals on five factors (context of interaction, required system data, required sensing input, required user input, and desired system output). Evaluation of the proposed solutions targeted at assessing the perceived feasibility and user acceptability, highlighting three main steps towards implementation of the designed solution.…”

Section: Related Workmentioning

confidence: 99%

User Experience Evaluation in Intelligent Environments: A Comprehensive Framework

et al. 2021

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‘User Experience’ (UX) is a term that has been established in HCI research and practice, subsuming the term ‘usability’. UX denotes that interaction with a contemporary technological system goes far beyond usability, extending to one’s emotions before, during, and after using the system and cannot be defined only by studying the fundamental usability attributes of effectiveness, efficiency and user satisfaction. Measuring UX becomes a substantially more complicated endeavor when the interaction target is not just a technological system or application, but an entire intelligent environment and the systems contained therein. Motivated by the imminent need to assess, measure and quantify user experience in intelligent environments, this paper presents a methodological and conceptual framework that provides concrete guidance for UX research, design and evaluation, explaining which UX parameter should be measured, how, and when. An evaluation of the framework indicated that it can be valuable for researchers and practitioners, assisting them in planning, carrying out, and analyzing UX studies in a comprehensive and thorough manner, thus enhancing their understanding and improving the experiences they design for intelligent environments.

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Section: Related Workmentioning

confidence: 99%

User Experience Evaluation in Intelligent Environments: A Comprehensive Framework

et al. 2021

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“…Although the majority of people wouldn't give intelligent agents a second thought for the work they perform to make their lives simpler, their use has grown significantly over the past years. In the UK and throughout the world, intelligent agents are used in every industry area [1]. There are two primary sections that include the most prevalent and extensively utilized agents.…”

Section: Introductionmentioning

confidence: 99%

Agent Based Intelligent System for Enhanced Teamwork Performance

Betrand,

Ekwealor,

Onukwugha

et al. 2024

IJDST

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It is impossible to overstate the necessity of a strategic and practical approach in the workplace in order to maximize productivity these days. Teamwork is one of the best ways to adapt to the changes that have occurred in today's environment throughout time. In every industry, the optimum performance arrangement for realizing visions, carrying out plans, and accomplishing objectives is teamwork. It is also one of the most crucial components of systems for continuous improvement since it makes information exchange, issue resolution, and the growth of employee accountability easier. Teams function as a grouping of people with complementary talents who work together rather than against one another. They are held accountable for their strategic methods and use them to achieve a shared objective. The Supervised Learning technique was used in this work to simulate team performance utilizing an intelligent coaching agent. Through the use of an automated performance assessment and weighted scores for each task, this study was able to create a system that will remove biases from performance evaluation. As soon as a worker does the task, they will obtain a score. The purpose of this study was to demonstrate an event-based performance approach by developing and utilizing an intelligent coaching agent in a supervised learning team training framework. The goal was successfully met, and the result shows positive impacts on the team's performance.

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