2025/10/20 by Md. Faiyaz Abdullah Sayeedi, Sayeedi, Md. Faiyaz Abdullah, Md. Enamul Haque +7
Computer Science · Medicine · #AI in Service Interactions #Artificial Intelligence in Healthcare and Education #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Information Retrieval and Search Behavior
paper · pdf · doi:10.48550/arxiv.2510.17726
openalex publication_date 2025/10/20 · openalex created_date 2025/10/22 · openalex updated_date 2026/07/28
With the increasing integration of Artificial Intelligence (AI) in academic problem solving, university students frequently alternate between traditional search engines like Google and large language models (LLMs) for information retrieval. This study explores students' perceptions of both tools, emphasizing usability, efficiency, and their integration into academic workflows. Employing a mixed-methods approach, we surveyed 109 students from diverse disciplines and conducted in-depth interviews with 12 participants. Quantitative analyses, including ANOVA and chi-square tests, were used to assess differences in efficiency, satisfaction, and tool preference. Qualitative insights revealed that students commonly switch between GPT and Google: using Google for credible, multi-source information and GPT for summarization, explanation, and drafting. While neither tool proved sufficient on its own, there was a strong demand for a hybrid solution. In response, we developed a prototype, a chatbot embedded within the search interface, that combines GPT's conversational capabilities with Google's reliability to enhance academic research and reduce cognitive load.