The revelation of the preferences and choices of students is critical for understanding which areas of the discipline they aim. Especially for final‐year undergraduate students, job prospects are an important concern. In this study, the graduation project choices of the final‐year undergraduate students in the department of computer engineering were investigated in light of their impact on both the industry and academia. A total of 1,693 course grades of 94 final‐year undergraduate students were retrieved from the Student Information System. These course grades were utilized as the features of the employed machine learning algorithms alongside the features that were deduced from them. In addition, the popularities of the graduation project topics on both GitHub and IEEE were investigated to reveal their impact on the industry and academia. To this end, we proposed an experimental study, using 14 machine learning techniques, that predicts the topics of the graduation projects that the final‐year undergraduate students chose. According to the experimental results, the accuracy of the proposed model was calculated to be as high as 100 % when it was utilized with the Bayes Net, Kleene Star, or J48 algorithm. This experimental result confirms the efficiency of the proposed model. Finally, the insights gained from the data are discussed to shed light on the reasons for the choices of the graduation projects as well as their relationships with the courses.

中文翻译：

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计算机工程专业学生专业偏好与选择分析

揭示学生的偏好和选择对于了解他们的目标学科领域至关重要。特别是对于大四的本科生来说，就业前景是一个重要的问题。本研究从对工业界和学术界的影响对计算机工程系本科最后一年学生的毕业项目选择进行了调查。从学生信息系统中检索到 94 名本科毕业学生的 1,693 个课程成绩。这些课程成绩被用作所用机器学习算法的特征以及从中推导出的特征。此外，还对毕业项目主题在 GitHub 和 IEEE 上的流行度进行了调查，以揭示其对行业和学术界的影响。为此，我们提出了一项实验研究，使用 14 种机器学习技术，预测本科最后一年学生选择的毕业项目的主题。根据实验结果，该模型与贝叶斯网络、Kleene Star 或 J48 算法一起使用时计算出的准确率高达 100%。该实验结果证实了所提出模型的有效性。最后，讨论了从数据中获得的见解，以阐明选择毕业项目的原因及其与课程的关系。当与贝叶斯网络、Kleene Star 或 J48 算法一起使用时，所提出模型的准确度被计算为高达 100%。该实验结果证实了所提出模型的有效性。最后，讨论了从数据中获得的见解，以阐明选择毕业项目的原因及其与课程的关系。当与贝叶斯网络、Kleene Star 或 J48 算法一起使用时，所提出模型的准确度被计算为高达 100%。该实验结果证实了所提出模型的有效性。最后，讨论了从数据中获得的见解，以阐明选择毕业项目的原因及其与课程的关系。