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Development of Artificial Intelligence and Computational Thinking: Future Directions, Opportunities,...
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Development of Artificial Intelligence and Computational Thinking: Future Directions, Opportunities, and Challenges

A special issue of AI (ISSN 2673-2688).

Deadline for manuscript submissions: 31 July 2025 | Viewed by 3701

Special Issue Editors

Dr. Georgios Lampropoulos

E-Mail Website
Guest Editor
Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece
Interests: learning technologies; extended reality; artificial intelligence; computational thinking; learning analytics; gamification; serious games; educational robotics
Dr. Stamatios Papadakis

E-Mail Website
Guest Editor
Department of Preschool Education, Faculty of Education, University of Crete, 741 00 Crete, Greece
Interests: technology-enhanced learning; game-based learning; educational robotics; computational thinking; coding; STEM; machine learning; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The advent of Artificial Intelligence (AI) has revolutionized numerous aspects of society, from industry to healthcare, education, and beyond. Given this transformative power, our upcoming Special Issue focuses on the “Development of Artificial Intelligence and Computational Thinking: Future Directions, Opportunities, and Challenges”.

In this Special Issue, we aim to explore the intricate interplay between AI and computational thinking, delving into their ongoing development and envisioning their future trajectories. As AI continues to be integrated into various domains, understanding computational thinking becomes paramount, serving as the cornerstone for effectively harnessing AI potential while navigating its complexities.

The scope of this Special Issue encompasses a broad array of topics, including but not limited to the following:

Foundations of AI and Computational Thinking: We welcome contributions that elucidate the foundational principles underpinning AI and computational thinking. Exploring fundamental concepts, such as algorithms, data structures, problem-solving strategies, and machine learning frameworks, lays the groundwork for advancing these disciplines.

Applications of AI in Diverse Domains: AI applications exist in various domains from healthcare to finance, transportation, agriculture, and beyond. Manuscripts exploring innovative AI solutions in various sectors and their societal impact and ethical considerations are highly encouraged.

Educational Perspectives on Computational Thinking: As AI increasingly becomes integral to modern education, fostering computational thinking skills among students becomes imperative. Submissions addressing pedagogical approaches, curriculum development, and educational technologies aimed at nurturing computational thinking abilities are highly sought-after.

Ethical and Societal Implications of AI: While AI offers immense promises, it raises ethical dilemmas and societal concerns. We invite contributions that delve into issues, such as bias in AI systems, data privacy, algorithmic accountability, and the societal implications of automation and job displacement.

Future Directions and Challenges: Anticipating the future trajectory of AI and computational thinking is crucial for policymakers, researchers, and practitioners alike. Manuscripts offering insights into emerging trends, potential challenges, and avenues for future research and development are of great interest.

We aim to foster interdisciplinary dialogue and collaboration among researchers, practitioners, educators, and policymakers through this Special Issue. By collectively exploring the development of AI and computational thinking, we endeavor to chart a course towards a future in which these technologies empower individuals, enrich societies, and drive innovation across the globe.

Submission Guidelines:

Authors are invited to submit original research articles, reviews, case studies, or perspective papers relevant to the Special Issue theme. All submissions will undergo rigorous peer review to ensure academic rigor and quality. Manuscripts should adhere to the journal’s formatting guidelines and be submitted through the online submission system.

We look forward to receiving your contributions and engaging in thought-provoking discussions on the development of Artificial Intelligence and computational thinking.

Dr. Georgios Lampropoulos
Dr. Stamatios Papadakis
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. AI is an international peer-reviewed open access quarterly 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

  • Artificial Intelligence (AI)
  • computational thinking
  • machine learning
  • data science
  • algorithms
  • educational technology
  • ethical AI
  • automation
  • problem solving
  • future trends
  • digital literacy
  • algorithmic bias
  • educational innovation
  • society and technology
  • innovation in education

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Published Papers (1 paper)

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24 pages, 5034 KiB  
Perspective
AI Detection of Human Understanding in a Gen-AI Tutor
by Earl Woodruff
AI 2024, 5(2), 898-921; https://doi.org/10.3390/ai5020045 - 18 Jun 2024
Viewed by 2855
Abstract
Subjective understanding is a complex process that involves the interplay of feelings and cognition. This paper explores how computers can monitor a user’s sympathetic and parasympathetic nervous system activity in real-time to detect the nature of the understanding the user is experiencing as [...] Read more.
Subjective understanding is a complex process that involves the interplay of feelings and cognition. This paper explores how computers can monitor a user’s sympathetic and parasympathetic nervous system activity in real-time to detect the nature of the understanding the user is experiencing as they engage with study materials. By leveraging advancements in facial expression analysis, transdermal optical imaging, and voice analysis, I demonstrate how one can identify the physiological feelings that indicate a user’s mental state and level of understanding. The mental state model, which views understandings as composed of assembled beliefs, values, emotions, and feelings, provides a framework for understanding the multifaceted nature of the emotion–cognition relationship. As learners progress through the phases of nascent understanding, misunderstanding, confusion, emergent understanding, and deep understanding, they experience a range of cognitive processes, emotions, and physiological responses that can be detected and analyzed by AI-driven assessments. Based on the above approach, I further propose the development of Abel Tutor. This AI-driven system uses real-time monitoring of physiological feelings to provide individualized, adaptive tutoring support designed to guide learners toward deep understanding. By identifying the feelings associated with each phase of understanding, Abel Tutor can offer targeted interventions, such as clarifying explanations, guiding questions, or additional resources, to help students navigate the challenges they encounter and promote engagement. The ability to detect and respond to a student’s emotional state in real-time can revolutionize the learning experience, creating emotionally resonant learning environments that adapt to individual needs and optimize educational outcomes. As we continue to explore the potential of AI-driven assessments of subjective understanding, it is crucial to ensure that these technologies are grounded in sound pedagogical principles and ethical considerations, ultimately empowering learners and facilitating the attainment of deep understanding and lifelong learning for advantaged and disadvantaged students. Full article
(This article belongs to the Special Issue Development of Artificial Intelligence and Computational Thinking: Future Directions, Opportunities, and Challenges)
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