Abstract
Using information technology tools for academic help-seeking among college
students has become a popular trend. In the evolutionary process between
Generation Artificial Intelligence (GenAI) and traditional search engines, when
students face academic challenges, do they tend to prefer Google, or are they
more inclined to utilize ChatGPT? And what are the key factors influencing
learners' preference to use ChatGPT for academic help-seeking? These relevant
questions merit attention. The study employed a mixed-methods research design
to investigate Taiwanese university students' online academic help-seeking
preferences. The results indicated that students tend to prefer using ChatGPT
to seek academic assistance, reflecting the potential popularity of GenAI in
the educational field. Additionally, in comparing seven machine learning
algorithms, the Random Forest and LightGBM algorithms exhibited superior
performance. These two algorithms were employed to evaluate the predictive
capability of 18 potential factors. It was found that GenAI fluency, GenAI
distortions, and age were the core factors influencing how university students
seek academic help. Overall, this study underscores that educators should
prioritize the cultivation of students' critical thinking skills, while
technical personnel should enhance the fluency and reliability of ChatGPT and
Google searches and explore the integration of chat and search functions to
achieve optimal balance.