Computers in Human Behavior Artificial Humans, Год журнала: 2025, Номер unknown, С. 100157 - 100157
Опубликована: Май 1, 2025
Язык: Английский
Applied Sciences, Год журнала: 2022, Номер 12(22), С. 11457 - 11457
Опубликована: Ноя. 11, 2022
In recent years, gesture recognition and speech recognition, as important input methods in Human–Computer Interaction (HCI), have been widely used the field of virtual reality. particular, with rapid development deep learning, artificial intelligence, other computer technologies, achieved breakthrough research progress. The search platform this work is mainly Google Academic literature database Web Science. According to keywords related HCI such “intelligent HCI”, “speech recognition”, “gesture “natural language processing”, nearly 1000 studies were selected. Then, 500 selected 100 finally content after five years (2019–2022) year screening. First, current situation intelligent system analyzed, realization interaction voice summarized, advantages brought by learning are for research. core concepts introduced progress analyzed. Furthermore, representative applications described. Finally, direction natural processing investigated. results show that combination deeply applied emotion robot direction. A wide variety proposed fields verified experiments. Compared interactive without high accuracy was achieved. Human–Machine Interfaces (HMIs) support, context plays an role improving user interfaces. Whether it search, mobile communication, or children’s combined can maintain better robustness. convolutional neural networks long short-term memory greatly improve precision action recognition. Therefore, future, application will involve more industries greater prospects expected.
Язык: Английский
Процитировано
77
Computers in Human Behavior, Год журнала: 2024, Номер 162, С. 108416 - 108416
Опубликована: Авг. 28, 2024
Язык: Английский
Процитировано
20
Frontiers in Robotics and AI, Год журнала: 2021, Номер 8
Опубликована: Ноя. 19, 2021
The evolving field of human-robot interaction (HRI) necessitates that we better understand how social robots operate and interact with humans. This scoping review provides an overview about 300 research works focusing on the use NAO robot from 2010 to 2020. study presents one most extensive inclusive pieces evidence deployment humanoid its global reach. Unlike reviews, provide both qualitative quantitative results regarding is being used what has been achieved so far. We analyzed a wide range theoretical, empirical, technical contributions multidimensional insights, such as general trends in terms application, capabilities, input output modalities communication, experiments featured (e.g. number roles participants, design, length interaction). Lastly, derive some gaps current state-of-the-art suggestions for design next generation robots.
Язык: Английский
Процитировано
64
AI & Society, Год журнала: 2022, Номер 39(3), С. 1127 - 1140
Опубликована: Сен. 10, 2022
Язык: Английский
Процитировано
43
Information, Год журнала: 2025, Номер 16(1), С. 29 - 29
Опубликована: Янв. 7, 2025
In contrast to other learning technologies, social robots are and affective entities that defined by their physical presence, anthropomorphic characteristics, advanced social, emotional, cognitive skills. Social intelligent tutoring systems can improve students’ learning, affective, outcomes when used as tutors or peer learners offering personalized learning. As the field of use in education is rapidly advancing, this study aims provide a review regarding integration through analysis existing literature present state art identify future research directions. Additionally, main characteristics properties benefits they bring discussed. Specifically, examines 361 documents derived from Scopus Web Science databases. To analyze documents, Bibliometrix, VOSviewer, topic modeling Latent Dirichlet Allocation (LDA), content used. An basic (e.g., publication frequency, citation count, authors, sources, countries, affiliations, etc.) more in-depth focusing on identifying most prominent topics themes well thematic evolution were carried out. Finally, analysis, current limitations challenges revealed emerging directions highlighted.
Язык: Английский
Процитировано
1
npj Science of Learning, Год журнала: 2025, Номер 10(1)
Опубликована: Янв. 8, 2025
Abstract Rising interest in artificial intelligence education reinforces the demand for evidence-based implementation. This study investigates how tutor agents’ physical embodiment and anthropomorphism (student-reported sociability, animacy, agency, disturbance) relate to affective (on-task enjoyment) cognitive (task performance) learning within an intelligent tutoring system (ITS). Data from 56 students ( M = 17.75 years, SD 2.63 years; 30.4% female), working with emotionally-adaptive version of ITS “Betty’s Brain”, were analyzed. The ITS’ agents either depicted as on-screen robots (condition A) or both avatars B). Physical presence agent was not significantly related task performance anthropomorphism, but higher initial on-task enjoyment. Student-reported disturbance negatively enjoyment, student-reported sociability performance. While may increase students’ perception certain characteristics hinder learning, providing implications designing social education.
Язык: Английский
Процитировано
1
Advances in business information systems and analytics book series, Год журнала: 2024, Номер unknown, С. 65 - 93
Опубликована: Янв. 7, 2024
The current digital society has witnessed important developments in robotics and artificial intelligence (AI) research being applied to several spheres of life order address multitude issues. While there are numerous studies on human-robot collaboration low- high-level tasks with a focus robot development, the study, chapter focused organizational issues arising from co-working education particular reference network (REN) for universities as leverage human capital development. identified critical REN tried solve them an pedagogical normalization perspective. described AI-powered instructional application development process that can participate impact AI pedagogic literacy using deep learning, introducing emphasis expansion.
Язык: Английский
Процитировано
7
Computers, Год журнала: 2022, Номер 11(12), С. 181 - 181
Опубликована: Дек. 8, 2022
There is a growing interest in using social robots public spaces for indoor and outdoor applications. The threat landscape an important research area being investigated debated by various stakeholders. Objectives: This study aims to identify synthesize empirical on the complete of spaces. Specifically, this paper identifies potential actors, their motives attacks, vulnerabilities, attack vectors, impacts possible scenarios, mitigations these threats. Methods: systematic literature review follows guidelines Kitchenham Charters. search was conducted five digital databases, 1469 studies were retrieved. analyzed 21 that satisfied selection criteria. Results: Main findings reveal four categories: cybersecurity, social, physical, space. Conclusion: completely grasped complexity transdisciplinary problem robot security privacy while accommodating diversity stakeholders’ perspectives. Findings give researchers other stakeholders comprehensive view highlighting current developments new directions field. also proposed taxonomy actors
Язык: Английский
Процитировано
25
Frontiers in Robotics and AI, Год журнала: 2020, Номер 7
Опубликована: Окт. 7, 2020
This research occurred in a special context where Kazakhstan's recent decision to switch from Cyrillic the Latin-based alphabet has resulted challenges connected teaching literacy, addressing rare combination of hypotheses and technical objectives about language learning. Teachers are not necessarily trained teach new alphabet, this could result challenge for children with learning difficulties. Prior studies Human-Robot Interaction (HRI) have proposed use robot handwriting (Hood et al., 2015; Lemaignan 2016). Drawing on Kazakhstani case, our study takes an interdisciplinary approach by bringing together smart solutions robotics, computer vision areas, educational frameworks, language, cognitive that will benefit diverse groups stakeholders. In study, human-robot interaction application is designed help primary school learn both newly-adopted script also its system. The setup involved experiment 62 between ages 7-9 years old, across three conditions: tablet, tablet only, teacher. Based paradigm-learning teaching-the showed improved their knowledge Latin interacting robot. Findings reported gained similar all conditions without gender effect. addition, children's likeability ratings positive mood change scores demonstrate significant benefits favoring over traditional teacher only approaches.
Язык: Английский
Процитировано
36
Опубликована: Май 6, 2021
Visually impaired children (VI) face challenges in collaborative learning classrooms. Robots have the potential to support inclusive classroom experiences by leveraging their physicality, bespoke social behaviors, sensors, and multimodal feedback. However, design of robots for mixed-visual abilities classrooms remains mostly unexplored. This paper presents a four-month-long community-based process where we engaged with school community. We provide insights into barriers experienced how can address them. also report on participatory activity children, highlighting expected roles, attitudes, physical characteristics robots. Findings contextualize within settings as holistic solution that interact anywhere when needed suggest broader view inclusion beyond disability. These include children's personality traits, technology access, mastery subjects. finish providing reflections process.
Язык: Английский
Процитировано
32