Generative AI in Education


Abstract views: 606

Authors

  • Muhammet Emir Kars

DOI:

https://doi.org/10.31039/ljss.2023.6.114

Keywords:

generative AI, education, transformative technology, learning outcomes, student engagement, teacher support, ethical considerations, personalized learning experiences, biased content

Abstract

Recently, the field of artificial intelligence (AI) has advanced significantly, with generative
AI rising to the top of the tech industry's most-discussed subjects list. Education like many
other fields could be transformed by generative AI like ChatGPT, Bard, DALL-E,
Midjourney, and DeepMind, which all have the ability to revolutionize a number of industries
with all the benefits and drawbacks they entail.
The paper begins by providing an overview of generative AI, highlighting its capacity to
generate human-like text, images, and even interactive simulations. It delves into the
underlying principles and techniques that empower generative AI models, focusing on
prominent models like ChatGPT and Midjourney.
To assess the effectiveness of generative AI in educational contexts, the paper examines
studies that have evaluated learning outcomes, student engagement, and teacher support.
These findings provide insights into the efficiency of generative AI as a supplementary
educational tool and its role in fostering innovative teaching practices. The paper also addresses
concerns around the technology being too integrated into education like over dependence and
cheating.
Finally, the paper discusses future possibilities and challenges for the integration of generative
AI in education. It proposes strategies for maximizing the benefits of this technology while
ensuring ethical considerations are met. The paper concludes with a call for further research
and collaboration between AI experts, educators, policymakers, and other stakeholders to
harness the full potential of generative AI in transforming the learning landscape.

References

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Published

2023-09-20

How to Cite

Kars, M. E. (2023). Generative AI in Education. London Journal of Social Sciences, (6), 144–151. https://doi.org/10.31039/ljss.2023.6.114

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Section

Articles