Discrete mathematics and probability theory contain foundational material for computer scientists. Despite their importance, instructors often worry that students will find these courses to be too abstract and seemingly disconnected from their future careers. For this research project, we introduced homework questions throughout our introductory theory courses based on real world applications of the course content. Areas of application included a court case, code correctness, and machine learning ethics. We surveyed students at the beginning and end of the term on their attitudes toward the relevance of the course material. Our results, surprisingly, indicate that a small minority of students (less than 7%) expected the material to be irrelevant to them at the start of the term, and a similarly small number believed that at the end of the term. Our surveys and qualitative feedback also indicate students enjoyed having the problems and wanted them to continue being offered in future iterations of the courses.

翻译：离散数学与概率论为计算机科学家提供了基础性知识。尽管这些课程至关重要，教师常担忧学生会觉得其过于抽象，且似乎与未来职业生涯脱节。在本研究项目中，我们围绕课程内容的现实应用，在导论性理论课程中引入了课后问题。应用领域包括法庭案例、代码正确性以及机器学习伦理。我们在学期初和学期末分别调查了学生对课程材料相关性的态度。出乎意料的是，结果显示，学期初仅有极少数学生（不足7%）认为这些材料与自己无关，学期末持同样看法的学生比例同样微小。我们的调查与定性反馈还表明，学生乐于解答这些问题，并希望后续课程中继续保留此类设计。