@inproceedings{sayeedi-etal-2025-rethinking,
    title = "Rethinking Search: A Study of University Students' Perspectives on Using {LLM}s and Traditional Search Engines in Academic Problem Solving",
    author = "Sayeedi, Md. Faiyaz Abdullah  and
      Haque, Md. Sadman  and
      Razzaque, Zobaer Ibn  and
      Robin, Robiul Awoul  and
      Nawshin, Sabila",
    editor = "Blodgett, Su Lin  and
      Curry, Amanda Cercas  and
      Dev, Sunipa  and
      Li, Siyan  and
      Madaio, Michael  and
      Wang, Jack  and
      Wu, Sherry Tongshuang  and
      Xiao, Ziang  and
      Yang, Diyi",
    booktitle = "Proceedings of the Fourth Workshop on Bridging Human-Computer Interaction and Natural Language Processing (HCI+NLP)",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.hcinlp-1.5/",
    doi = "10.18653/v1/2025.hcinlp-1.5",
    pages = "48--59",
    ISBN = "979-8-89176-353-1",
    abstract = "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."
}