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EDSCI 2024 : How Artificial Intelligence Can Enhance Education: Current Practices and Challenges | |||||||||
Link: https://www.mdpi.com/journal/education/special_issues/JQG7ACJ6MF | |||||||||
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Call For Papers | |||||||||
Special Issue Information
Dear Colleagues, Artificial intelligence (AI) is transforming various aspects of education, from curriculum design to assessment and feedback. AI offers the potential to enhance the quality and effectiveness of teaching and learning by providing personalized and adaptive learning experiences, streamlining administrative tasks, and supporting early intervention and remediation. However, AI also poses significant challenges and risks, such as data privacy and security, algorithmic bias and fairness, and ethical and social implications. Striking a balance between harnessing the benefits of AI for enhanced education and addressing the associated risks is crucial in ensuring a responsible and equitable integration of these technologies (Delello et al., 2024). The use of AI and its effects on teaching and learning have not been fully investigated. In fact, according to the 2023 Teaching and Learning Horizon Report, the absence of best practices on how to incorporate AI is an obstacle for its widespread use (Pelletier et al., 2023). Leveraging insights and approaches from diverse fields, this Special Issue aims to shed additional light on the utilization of AI to support learning and consider how educators can responsibly integrate such technologies. Original research articles, case studies, and reviews are invited. The scope of the submission should focus on the use of artificial intelligence (AI) to support learning environments and may include (but is not limited to) items such as the following: Conversational AI (chatbots, virtual agents, ChatGPT); Intelligent tutoring and personalized learning; Immersive learning environments (gaming, simulations); The use of data analytics and AI for decision making; Improved accessibility opportunities; Equity, inclusion, and differentiation of learning; Academic integrity (cheating, plagiarism, and policy development); Ethics, data privacy, and the potential for bias; Testing, grading, and assessment; AI literacy, overreliance, and student motivation; Preparing the future workforce. We look forward to receiving your contributions. |
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