  In recent years, the rapid development of artificial intelligence technology,
especially the emergence of large language models (LLMs) such as ChatGPT, has
presented significant prospects for application in the field of education. LLMs
possess the capability to interpret knowledge, answer questions, and consider
context, thus providing support for dialogic teaching to students. Therefore,
an examination of the capacity of LLMs to effectively fulfill instructional
roles, thereby facilitating student learning akin to human educators within
dialogic teaching scenarios, is an exceptionally valuable research topic. This
research recruited 34 undergraduate students as participants, who were randomly
divided into two groups. The experimental group engaged in dialogic teaching
using ChatGPT, while the control group interacted with human teachers. Both
groups learned the histogram equalization unit in the information-related
course "Digital Image Processing". The research findings show comparable scores
between the two groups on the retention test. However, students who engaged in
dialogue with ChatGPT exhibited lower performance on the transfer test.
Electroencephalography data revealed that students who interacted with ChatGPT
exhibited higher levels of cognitive activity, suggesting that ChatGPT could
help students establish a knowledge foundation and stimulate cognitive
activity. However, its strengths on promoting students. knowledge application
and creativity were insignificant. Based upon the research findings, it is
evident that ChatGPT cannot fully excel in fulfilling teaching tasks in the
dialogue teaching in information related courses. Combining ChatGPT with
traditional human teachers might be a more ideal approach. The synergistic use
of both can provide students with more comprehensive learning support, thus
contributing to enhancing the quality of teaching.
