Resembling ChatGPT-Generated Science Topics with Human-Written Text-books (A case study)

Abstract

The affordances of Generative Pre-Trainer Transformer (ChatGPT) in learning and teaching have gained increasing traction. Its release and rapid diffusion have caught the attention of educators worldwide. No doubt that ChatGPT and similar generative AI models have attracted hundreds of millions of users and have become part of the public discourse. Rapid developments in generative AI technologies have led to an increased interest in their capabilities and applications. Relevant Literature demonstrates valuable support of this technique(s) for drafting manuscripts, summarizing articles, translating languages, and refining text structures or wording. likewise, these technologies have the ability to mimic human-like conversations with users, such as providing information and assistance, offering emotional support. The most frequently used of these technologies is ChatGPT.

This study is evaluating effectiveness and differences between learners’ comprehension (concepts acquirement) by generative AI (ChatGPT) and human-generated texts in educational contexts. By determining learner’s comprehension level, the study identifies key distinctions between the two types of content. Results showed a statistically significant difference at the significance level (α ≤ 0.05) between the means of the experimental and control groups in the post-testing in favor of the experimental group. Overall, findings indicated constructive impact of this technology on students’ comprehension (acquisition of scientific concepts).