Advances in Human-Centered Artificial Intelligence

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 4810

Special Issue Editors

Department of Computer Science, University of the Philippines Diliman, Quezon 3113, Philippines
Interests: software engineering; artificial intelligence; software services; HCI
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Human-centered artificial intelligence concentrates on algorithms that are part of broader "user-based" software and evolves by user intervention and collaboration. Software systems that constantly evolve as a result of user input and offer a positive interaction between human users and machines are referred to as human-centered artificial intelligence. As such, this field can exceed the limits of existing artificial intelligence solutions to reduce the disparity between computers and users by generating machine intelligence with the aim of comprehending natural speech, sentiment, and behaviour.

As mentioned above, by fusing powerful user experiences with integrated artificial intelligence services that users demand, human-centered artificial intelligence, as a compelling idea, empowers people to perceive, understand, produce, and interact in distinctive ways.

With precise guidelines for creating effective solutions that enhance, magnify, enable, and enrich individuals rather than replacing them, the HCAI approach addresses the barrier between ethics and practice. This change in perspective might pave the way for a future that is safer, clearer, and simpler to control. An HCAI strategy will lessen the likelihood of unchecked technology, allay concerns about machine-driven layoffs, and lessen dangers to security and privacy. Future developments that are centered on people will also uphold human values, honor human dignity, and foster strong respect for the human abilities that lead to innovative breakthroughs and innovations.

Toward this direction, this Special Issue is soliciting original research papers as well as review articles and short communications in specific relevant areas. Pertaining to the field of human-centered artificial intelligence, the topics of interest/application include, but are not limited to, the following:

  • Conversational agents and smart assistants
  • Technological advancements in healthcare
  • Autonomous systems
  • Support for people with disabilities
  • Personalized tutoring systems
  • Efficient green energy
  • Effective cybersecurity
  • User-centered and intelligent systems

Dr. Christos Troussas
Dr. Akrivi Krouska
Dr. Phivos Mylonas
Dr. Katerina Kabassi
Dr. Jaime Caro
Prof. Dr. Cleo Sgouropoulou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • human-centered artificial intelligence
  • enhanced user experience
  • human–artificial-intelligence interaction

Published Papers (1 paper)

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Research

18 pages, 278 KiB  
Article
Higher Education Students’ Task Motivation in the Generative Artificial Intelligence Context: The Case of ChatGPT
by Mohammad Hmoud, Hadeel Swaity, Nardin Hamad, Omar Karram and Wajeeh Daher
Information 2024, 15(1), 33; https://doi.org/10.3390/info15010033 - 08 Jan 2024
Cited by 1 | Viewed by 4173
Abstract
Artificial intelligence has been attracting the attention of educational researchers recently, especially ChatGPT as a generative artificial intelligence tool. The context of generative artificial intelligence could impact different aspects of students’ learning, such as the motivational aspect. The present research intended to investigate [...] Read more.
Artificial intelligence has been attracting the attention of educational researchers recently, especially ChatGPT as a generative artificial intelligence tool. The context of generative artificial intelligence could impact different aspects of students’ learning, such as the motivational aspect. The present research intended to investigate the characteristics of students’ task motivation in the artificial intelligence context, specifically in the ChatGPT context. The researchers interviewed 15 students about their experiences with ChatGPT to collect data. The researchers used inductive and deductive content analysis to investigate students’ motivation when learning with ChatGPT. To arrive at the categories and sub-categories of students’ motivation, the researchers used the MAXQDA 2022. Five main categories emerged: task enjoyment, reported effort, result assessment, perceived relevance, and interaction. Each category comprised at least two sub-categories, and each sub-category was further organized into codes. The results indicated more positive characteristics of motivation than negative ones. The previous results could be due to the conversational or social aspect of the chatbot, enabling relationships with humans and enabling the maintenance of good quality conversations with them. We conclude that a generative AI could be utilized in educational settings to promote students’ motivation to learn and thus raise their learning achievement. Full article
(This article belongs to the Special Issue Advances in Human-Centered Artificial Intelligence)
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