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Applied Sciences
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Human-Computer Interaction: Challenges, Opportunities and Emerging Developments, 2nd Edition
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Human-Computer Interaction: Challenges, Opportunities and Emerging Developments, 2nd Edition

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 September 2025 | Viewed by 2782

Special Issue Editor

Dr. Paweł Weichbroth

E-Mail Website
Guest Editor
Department of Software Engineering, Gdansk University of Technology, Gdansk, Poland
Interests: AI; machine learning; information systems; software quality; mobile computing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Human-computer interaction (HCI) is a multidisciplinary field of research focusing on the design of computer technology and, more specifically, the interaction between humans (users) and computers. Nowadays, HCI is still the subject of considerable interest, gaining the attention of both researchers and practitioners.

The emergence of new technological advancements, including Artificial Intelligence, Extended Reality Mobile Computing, Virtual/Augmented Reality, and the Internet of Things (IoT), have imposed new requirements with respect to the design of information systems (ISs) on the one hand, as well having introduced significant opportunities for ISs to leverage user experiences, on the other.

This Special Issue is dedicated to disseminating high-quality, original research papers, covering the following topics (though not limited to them):

  • Human-computer interaction theory.
  • Multimodal interaction.
  • Natural language interaction.
  • Intelligent user interfaces.
  • User-centered design.
  • Usability and user experience.
  • Cognitive systems.
  • Machine learning methods for user interface design and customization.
  • Mobile computing.
  • Mobile applications design and development.
  • Virtual reality.
  • Augmented reality.
  • Interaction and humans in the Internet of Things.

Dr. Paweł Weichbroth
Guest Editor

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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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–computer interaction
  • usability
  • user experience
  • intelligent user interfaces
  • mobile computing
  • virtual reality
  • augmented reality

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Related Special Issue

Published Papers (2 papers)

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Research

15 pages, 3317 KiB  
Article
Classification of Properties in Human-like Dialogue Systems Using Generative AI to Adapt to Individual Preferences
by Kaori Abe, Changqin Quan, Sheng Cao and Zhiwei Luo
Appl. Sci. 2025, 15(7), 3466; https://doi.org/10.3390/app15073466 - 21 Mar 2025
Viewed by 302
Abstract
As the linguistic capabilities of AI-based dialogue systems improve, their human-likeness is increasing, and their behavior no longer receives a universal evaluation. To better adapt to users, the consideration of individual preferences is required. In this study, the relationships between the properties of [...] Read more.
As the linguistic capabilities of AI-based dialogue systems improve, their human-likeness is increasing, and their behavior no longer receives a universal evaluation. To better adapt to users, the consideration of individual preferences is required. In this study, the relationships between the properties of a human-like dialogue system and dialogue evaluations were investigated using hierarchical cluster analysis for individual subjects. The dialogue system driven by generative AI communicated with subjects in natural language via voice-based communication and featured a facial expression function. Subjective evaluations of the system and dialogues were conducted through a questionnaire. Based on the analysis results, the system properties were classified into two types: generally and individually relational to a positive evaluation of the dialogue. The former included inspiration, a sense of security, and collaboration, while the latter included a sense of distance, personality, and seriousness. Equipping the former properties is expected to improve dialogues for most users. The latter properties should be adjusted to individuals since they are evaluated based on individual preferences. A design approach in accordance with individuality could be useful for making human-like dialogue systems more comfortable for users. Full article
(This article belongs to the Special Issue Human-Computer Interaction: Challenges, Opportunities and Emerging Developments, 2nd Edition)
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37 pages, 1529 KiB  
Article
Differences in User Perception of Artificial Intelligence-Driven Chatbots and Traditional Tools in Qualitative Data Analysis
by Boštjan Šumak, Maja Pušnik, Ines Kožuh, Andrej Šorgo and Saša Brdnik
Appl. Sci. 2025, 15(2), 631; https://doi.org/10.3390/app15020631 - 10 Jan 2025
Viewed by 2143
Abstract
Qualitative data analysis (QDA) tools are essential for extracting insights from complex datasets. This study investigates researchers’ perceptions of the usability, user experience (UX), mental workload, trust, task complexity, and emotional impact of three tools: Taguette 1.4.1 (a traditional QDA tool), ChatGPT (GPT-4, [...] Read more.
Qualitative data analysis (QDA) tools are essential for extracting insights from complex datasets. This study investigates researchers’ perceptions of the usability, user experience (UX), mental workload, trust, task complexity, and emotional impact of three tools: Taguette 1.4.1 (a traditional QDA tool), ChatGPT (GPT-4, December 2023 version), and Gemini (formerly Google Bard, December 2023 version). Participants (N = 85), Master’s students from the Faculty of Electrical Engineering and Computer Science with prior experience in UX evaluations and familiarity with AI-based chatbots, performed sentiment analysis and data annotation tasks using these tools, enabling a comparative evaluation. The results show that AI tools were associated with lower cognitive effort and more positive emotional responses compared to Taguette, which caused higher frustration and workload, especially during cognitively demanding tasks. Among the tools, ChatGPT achieved the highest usability score (SUS = 79.03) and was rated positively for emotional engagement. Trust levels varied, with Taguette preferred for task accuracy and ChatGPT rated highest in user confidence. Despite these differences, all tools performed consistently in identifying qualitative patterns. These findings suggest that AI-driven tools can enhance researchers’ experiences in QDA while emphasizing the need to align tool selection with specific tasks and user preferences. Full article
(This article belongs to the Special Issue Human-Computer Interaction: Challenges, Opportunities and Emerging Developments, 2nd Edition)
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