以下是适用于英语论文答辩的结束语通用模板及关键要点，结合多个学术资源整理而成，供参考时根据具体研究内容调整：
模板一：结构化总结型
适用场景：适用于需全面回顾研究内容、强调逻辑性的答辩。
1. 重申研究目的与结论
"In conclusion, this study focused on [研究主题], aiming to [研究目的]. The findings demonstrate that [核心结论], which aligns with the initial hypothesis proposed in the introduction."
引用示例：网页1与网页13均以重述论文标题和核心论点作为收尾。
2. 总结研究贡献
"The significance of this research lies in [贡献1: 理论/实践意义], [贡献2: 领域创新点]. For example, [具体案例或数据] highlights its potential application in [相关领域]."
技巧：网页69建议通过实例强化结论的可信度。
3. 致谢与邀请提问
"I sincerely thank my supervisor, Prof. [姓名], for their guidance, and the committee for your attention. I welcome any questions or suggestions to further improve this work."
礼仪提示：网页18指出，结尾需礼貌邀请提问，如“Thank you for your attention. Please ask questions.”
模板二：问题导向型
适用场景：针对研究中存在不足或未来方向的答辩。
1. 反思研究局限
"Despite the findings, this study has limitations. For instance, [局限1: 样本量/方法], [局限2: 数据范围]. Future research could explore [改进建议]."
模板参考：网页15提到需主动说明不足，如“limitation of time and energy”。
2. 强调研究价值
"Nevertheless, this work provides a foundation for [后续研究主题]. By addressing [关键问题], it encourages deeper discussions on [相关议题]."
学术规范：网页29建议使用“suggests”“indicates”等词汇增强逻辑性。
3. 致谢与收尾
"I am grateful to all participants and mentors. Your insights are invaluable. Thank you, and I look forward to your feedback."
模板三：致谢与情感表达型
适用场景：适用于强调研究过程中个人成长或团队合作的答辩。
1. 个人成长与感悟
"This journey has taught me the importance of [研究中的关键技能/认识]. The challenges in [具体环节] deepened my understanding of [领域]."
情感表达：网页43的致谢部分强调导师与同伴的支持。
2. 团队致谢
"My deepest gratitude goes to Prof. [姓名] for their patience, and my colleagues for [具体帮助]. Special thanks to my family for their unwavering support."
句型参考：网页61提供致谢模板，如“I would like to thank... for their love and faith”。
3. 展望与邀请提问
"I believe this research is just the beginning. Let us continue exploring [领域]. Thank you, and I am ready for your questions."
关键注意事项
1. 语言风格：避免冗长，使用主动语态（如“This study demonstrates...”而非“It was demonstrated that...”）。
2. 时间控制：结束语建议控制在2-3分钟内，占答辩总时长的10%-15%。
3. PPT配合：如使用PPT，结尾页可列出1-2个核心结论或致谢词（参考网页36的答辩结构）。
如需更多细分领域模板（如语言学、工程学等），可结合具体研究方向调整上述框架，并参考网页69的结论写作逻辑。
