Enhancing Educational Outcomes Through Exploring the Optimized Options Artificial Intelligence and Deep Learning
Artificial Intelligence (AI) has the potential to herald a new dawn of instructional and operational excellence in the higher education domain, thereby reshaping the dimensions of teaching and learning and administrative efficiency. This paper explores great potential for AI in the customization of...
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Published in | 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) pp. 929 - 934 |
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Main Authors | , , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
14.05.2024
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Subjects | |
Online Access | Get full text |
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Summary: | Artificial Intelligence (AI) has the potential to herald a new dawn of instructional and operational excellence in the higher education domain, thereby reshaping the dimensions of teaching and learning and administrative efficiency. This paper explores great potential for AI in the customization of learning experiences to optimize each learner's engagement, hence better academic performance. It also investigates the potential for AI to help in streamlining most of the administrative processes, which would lead to less work pressure on the faculty and staff, thus freeing up additional time for them to focus on core educational objectives. Specifically, the paper addresses key ethical issues that AI brings with it in relation to data privacy, algorithmic bias, and digital divide, which are fundamental barriers to an equitable and fair use of these technologies. This would form part of a mixed-methods research design that would synthesize such qualitative perspectives from expert interviews with data gleaned from the most recent example of educational interventions around AI. This provides a broad picture of the effectiveness of AI and challenges that may lie at the level of higher education. The range of artificial intelligence applications from current to likely use reviews is adaptive learning systems, automated grading tools, and predictive analytics for student support services. |
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DOI: | 10.1109/ICACITE60783.2024.10616772 |