This paper describes the creation, optimization, and assessment of a
question-answering (QA) model for a personalized learning assistant that uses
BERT transformers customized for the Arabic language. The model was
particularly finetuned on science textbooks in Palestinian curriculum. Our
approach uses BERT's brilliant capabilities to automatically produce correct
answers to questions in the field of science education. The model's ability to
understand and extract pertinent information is improved by finetuning it using
11th and 12th grade biology book in Palestinian curriculum. This increases the
model's efficacy in producing enlightening responses. Exact match (EM) and F1
score metrics are used to assess the model's performance; the results show an
EM score of 20% and an F1 score of 51%. These findings show that the model can
comprehend and react to questions in the context of Palestinian science book.
The results demonstrate the potential of BERT-based QA models to support
learning and understanding Arabic students questions.

本文描述了一种为个性化学习助手创建、优化和评估的问答模型，该模型使用针对阿拉伯语的 BERT transformer 进行了定制。该模型通过在巴勒斯坦课程中的科学教科书中进行优化，能够自动产生正确的科学教育问题的答案，并通过 BERT 技术的精确匹配和 F1 得分评估了模型的性能。结果显示，该模型能够理解并回答与巴勒斯坦科学教材相关的问题，展示了 BERT 问答模型在支持阿拉伯语学生的学习和理解方面的潜力。