Generative AI in Educational Practices: Emerging Topics, Use Cases, and Socio-Algorithmic Vulnerabilities
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Deadline for manuscript submissions: closed (15 December 2024) | Viewed by 324
Special Issue Editors
Interests: artificial intelligence; complex systems; computer supported cooperative work; human-AI interaction; hybrid intelligent systems; scientometrics; social computing; science and technology studies
Special Issues, Collections and Topics in MDPI journals
Interests: collaborative learning; computational thinking; computer supported cooperative work; human-computer interaction; optimization; reinforcement learning
Special Issues, Collections and Topics in MDPI journals
Interests: computer supported cooperative work; crowdsourcing; digital nomadism; human-computer interaction; social computing; social media
Special Issues, Collections and Topics in MDPI journals
Interests: data mining; machine learning; cognitive computing; explainable artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; data mining; deep learning; educational technology; learning analytics; machine learning; neural networks
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
As we navigate the shifting, fast-paced, and evolving landscape of education technology, the sudden and extensive adoption of generative AI models has opened endless possibilities to establish a completely novel set of educational, socio-algorithmic experiences where students can use intelligent systems to create learning plans or receive answers to their queries in a personalized manner. On the other hand, instructors and teachers can now use AI-based systems to assess student performance based on advanced learning analytics and prepare classroom teaching materials using multimodal instructional media to foster learners’ critical thinking and problem-solving abilities. However, academic institutions and policymakers are also concerned about the vulnerabilities and challenges that arise from the use of large language models (LLMs) and other AI-powered generative tools (e.g., image rendering and synthesis) in the sense that their socially embedded bias and unethical usage can cause harm to academic integrity by allowing students to misrepresent AI-generated assignments as their own work.
For this Special Issue, we invite high-quality submissions that will contribute to a better understanding of the theoretical foundations, research gaps, and potential areas of intervention regarding the practical uses of generative AI in educational settings. Topics and themes of interest include but are not limited to the following:
- Advanced learning analytics integrated into AI-based educational tools aimed at augmenting teaching and learning practices;
- Algorithmic bias and its threats to students from vulnerable groups (e.g., discrimination);
- Interactive machine teaching systems and adaptive learning applications supporting personalized socio-algorithmic experiences;
- Game-based learning in AI-enabled virtual educational settings;
- Immersive virtual environments and extended reality (XR) applications with generative capabilities;
- Formative assessment practices and guidelines in AI-driven tutoring platforms;
- Strategies to manage and mitigate the epistemic risks of generative AI in education and learning;
- Systematic literature reviews and quantitative studies depicting the research conducted in the intersectional space of generative AI and education;
- Multidimensional taxonomies for learner–, instructor–, and teacher–AI interaction.
Dr. António Correia
Dr. Benjamim Fonseca
Prof. Dr. Daniel Schneider
Dr. Mirka Saarela
Prof. Dr. Tommi Kärkkäinen
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- education
- generative AI
- human–AI interaction
- learning
- socio-algorithmic vulnerabilities
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