Search in Transition: A Study of University Students Perspectives on Using LLMs and Traditional Search Engines in English Test Problem Solving for Higher Study
Tarek Rahman, Md Shaharia Hossen, Mark Protik Mondol, and Jannatun Noor Mukta

TL;DR
This study investigates university students' perceptions of using LLMs and traditional search engines for English test preparation, revealing strategic tool use and proposing an integrated chatbot to improve efficiency and reliability.
Contribution
It provides empirical insights into students' tool preferences and introduces a novel integrated chatbot prototype combining LLMs and search engines for enhanced test preparation.
Findings
Students alternate between GPT and Google based on task needs.
Google is used for reliable information and verification.
GPT is preferred for summarization and explanation.
Abstract
As Artificial Intelligence (AI) becomes increasingly integrated into education, university students preparing for English language tests are frequently shifting between traditional search engines like Google and large language models (LLMs) to assist with problem-solving. This study explores students perceptions of these tools, particularly in terms of usability, efficiency, and how they fit into English test preparation practices. Using a mixed-methods design, we collected survey data from 140 university students across various academic fields and conducted in-depth interviews with 20 participants. Quantitative analyses, including ANOVA and chi-square tests, were applied to assess differences in perceived efficiency, satisfaction, and overall tool preference. The qualitative results reveal that students strategically alternate between GPT and Google based on task requirements. Google…
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Taxonomy
TopicsAI in Service Interactions · Artificial Intelligence in Healthcare and Education · Educational Strategies and Epistemologies
