International Journal of New Developments in Education, 2024, 6(11); doi: 10.25236/IJNDE.2024.061116.
Tiantian Yu
Beijing Academy of Social Science, Beijing, China
This paper examines the pivotal role of large language models (LLMs) in academic writing and explores their implications for students and educators alike. By tracing the progression from early statistical methods to the current sophisticated deep learning models based on Transformer architectures, LLMs have showcased their capability in a wide array of natural language processing tasks. Prominent examples of such models include the GPT series, PaLM, LLaMA, and T5, each characterized by unique features and applications. The study further investigates the influence of LLMs on higher education, employing theoretical perspectives such as dialectical materialism, neoliberalism, and constructivism. It argues for the creation of an evaluation framework to support the prudent integration of LLMs into educational practices and suggests conducting empirical research to refine this guidance. In conclusion, the paper asserts that LLMs hold significant promise in advancing educational goals.
Large Language Model, Dissertation Writing, Philosophical Orientation
Tiantian Yu. Language Models as Dissertation Assistants: Academic Misconduct or Efficiency Upgrades?. International Journal of New Developments in Education (2024), Vol. 6, Issue 11: 96-101. https://doi.org/10.25236/IJNDE.2024.061116.
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