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 is primarily used for accessing reliable, multi-source information and verifying rules, whereas GPT is favored for summarizing content, providing explanations, paraphrasing, and drafting responses for English test tasks. Since neither tool independently satisfies all aspects of English language test preparation, students expressed a clear preference for an integrated approach. In response, this study proposes a prototype chatbot embedded within a search interface, combining GPTs interactive capabilities with Googles credibility to enhance test preparation and reduce cognitive load.

翻译：随着人工智能日益融入教育领域，备考英语测试的大学生频繁在Google等传统搜索引擎与大型语言模型之间切换以辅助问题解决。本研究探讨了学生对这两种工具的认知，特别是在可用性、效率及其如何融入英语备考实践方面。采用混合方法设计，我们收集了来自不同学术领域140名大学生的问卷调查数据，并对20名参与者进行了深度访谈。通过方差分析和卡方检验等定量分析方法，评估了学生在感知效率、满意度和整体工具偏好方面的差异。定性研究结果显示，学生会根据任务需求在GPT与Google之间进行策略性切换：Google主要用于获取可靠的多源信息和验证规则，而GPT更受青睐于内容总结、提供解释、文本改写以及为英语测试任务草拟回答。由于两种工具均无法独立满足英语备考的所有需求，学生明确表现出对整合式方法的偏好。为此，本研究提出一种内嵌于搜索界面的原型聊天机器人，通过融合GPT的交互能力与Google的可信度，以优化备考过程并降低认知负荷。