In the near future, the presence of advanced generative technologies, including ChatGPT and other services that use large language models (LLM), has the potential to greatly impact the field of education and the role of teachers within it. In particular, chatbots can perform four roles: interlocutor, content provider, teaching assistant and evaluator [1].
A notable characteristic of large language models (LLM) is their capacity for further training, wherein the initial model can be adapted and refined to cater to a specific subject area. Specifically, large language models (LLM) can undergo additional training using the written works of specific authors, enabling the creation of a “digital counterpart” of real historical figures.
The application of LLM holds significant potential in assisting both students and teachers in their textual work. For students, LLM can serve as a reviewer when working on creative assignments, offering guidance by identifying obvious and serious mistakes. Likewise, teachers can use LLM to conduct preliminary assessments of students' work and identify areas that require further educational attention [2]. This may be particularly useful when evaluating creative essays, a genre of literature known for its concise format and flexible style of presentation. Although essays have a changeable structure, they generally include an introduction, thesis statement, argumentation, and conclusion.
This research aims to investigate the implementation of LLM as a personal assistant in this context. In order to train LLM on specific data and create a “digital counterpart,” several tasks need to be accomplished:
- Gathering and preprocessing a dataset.
- Establishing evaluation criteria and annotating the dataset accordingly.
- Identifying educational shortcomings in LLM.
- Collecting and constructing a training set based on the “question-answer” principle for further training of the large language model.
The primary research focuses include the criteria for annotation required for subsequent training and potential limitations of LLM for educational purposes.