AI-Driven Frameworks for Human–Computer Interaction

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: 15 June 2026 | Viewed by 537

Special Issue Editor


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Guest Editor

Special Issue Information

Dear Colleagues,

Artificial intelligence (AI) is reshaping the future of human–computer interactions (HCIs) by enabling systems that understand, learn from and adapt to human behavior. As AI becomes increasingly embedded in our daily lives, new frameworks are emerging that combine intelligent computation with user-centered design principles to create more natural, responsive and personalized interaction experiences. The integration of AI-driven models into HCIs has the potential to revolutionize communication, accessibility, education and creative expression.

The Special Issue “AI-Driven Frameworks for Human-Computer Interaction” in Electronics explores the frontier where AI meets HCIs. We aim to gather innovative contributions that investigate algorithms, architectures, frameworks and experimental methods enhancing human–AI collaboration. This Special Issue welcomes studies that address both theoretical and practical aspects of intelligent interaction systems, emphasizing explainability, trust and ethical design.

General Description

The objective of this Special Issue is to advance the understanding of how AI technologies can be leveraged to create intelligent, adaptive and context-aware interaction systems that improve human experience. Submissions may include original research articles, surveys or application studies presenting novel methodologies, frameworks and tools that bridge AI techniques and HCI principles. We encourage interdisciplinary perspectives combining artificial intelligence, cognitive science, data analytics and educational research.

Potential Topics

Topics of interest include, but are not limited to:

  • Machine learning and deep learning for adaptive and intelligent interfaces
  • Multimodal interaction (visual-, auditory-, haptic-, gesture- or speech-based systems)
  • Affective computing and emotion-aware systems
  • Conversational AI and intelligent virtual assistants
  • Human–robot interactions and embodied AI frameworks
  • Cognitive modeling and user intent prediction
  • Trust, transparency and ethics in AI-driven HCI
  • Real-time perception and decision-making in interactive environments
  • Generative AI for interface and interaction design
  • Creation of prompt engineering techniques within AI-driven systems
  • Frameworks that integrate prompt engineering into educational processes
  • Prompt Engineering as a Reflective Pedagogical Practice
  • AI and Prompt Engineering in Education
  • AI-based assistive and accessibility technologies
  • Evaluation methods for intelligent and adaptive user interfaces

By combining insights from AI, HCIs and education, this Special Issue aims to foster discussion and innovation toward next-generation systems that are not only intelligent but also meaningful, inclusive and human-centered.

We look forward to your valuable contributions to this Special Issue.

Dr. George Kokkonis
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 250 words) can be sent to the Editorial Office for assessment.

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. Electronics 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

  • AI
  • HCI
  • intelligent virtual assistants
  • prompt engineering
  • AI-driven HCI
  • human–robot interactions

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Published Papers (1 paper)

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Research

33 pages, 2088 KB  
Article
Reconceptualizing Prompt Engineering as Reflective Professional Practice: A Framework for Teacher Development
by Ioannis Dourvas, George Kokkonis and Sotirios Kontogiannis
Electronics 2026, 15(5), 930; https://doi.org/10.3390/electronics15050930 - 25 Feb 2026
Viewed by 287
Abstract
The rapid integration of generative AI in education often frames teachers as technology users who primarily need technical training. Existing prompt engineering frameworks offer technical guidance but have limited grounding in theories of teacher professional development or reflective practice. This misses a key [...] Read more.
The rapid integration of generative AI in education often frames teachers as technology users who primarily need technical training. Existing prompt engineering frameworks offer technical guidance but have limited grounding in theories of teacher professional development or reflective practice. This misses a key feature of prompt engineering: prompting can externalize pedagogical thinking, making AI interaction a process of knowledge externalization. Through systematic conceptual analysis, this paper proposes a reconceptualization of prompt engineering from a technical competency to a reflective professional practice. The methodology integrates three theoretical traditions: Schön’s reflective practice theory (for externalizing tacit knowledge), Wiggins and McTighe’s backward design (for structuring instructional decisions), and Celik’s AI-TPACK framework (as integrated knowledge base). This synthesis suggests that effective prompting can be understood as an act of pedagogical externalization requiring integrated professional knowledge. The paper develops a seven-strategy framework (RPE framework) as an analytic lens for examining prompt engineering sophistication. This theoretical framework offers theory-derived hypotheses that require future empirical validation rather than presenting verified outcomes. Ultimately, the RPE framework offers a conceptual basis for potentially shifting the focus from technical training to teacher professional development by repositioning educators as AI-assisted instructional designers rather than mere AI users. Full article
(This article belongs to the Special Issue AI-Driven Frameworks for Human–Computer Interaction)
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