Contribution: In a context where hands-on courses are biased toward specific technologies, a novel creativity-provoking instructional approach for networking undergraduate courses is successfully applied following action research principles and active and creative learning techniques. Background: Extensive engineering-oriented networking courses have been proposed with a strong focus on specific protocol solutions. At the same time, the amount and complexity of techniques is notably increasing with the advent of the Future Internet. As a result, the curricula looses focus on the fundamentals of networking algorithms. Intended Outcomes: We address algorithmic learning in networking for computer sciences, where students are expected to 1) create; 2) develop; 3) analyze; and 4) compare algorithms and processes regardless of protocol-specific technologies. At least 70% of the students are expected to meet this goal while enhancing their engagement and motivation in a time-constrained course schedule. Application Design: To achieve 1) and 2), we instrument an active experimental strategy, while objectives 3) and 4) are tackled with creative learning techniques, both applied in an action research framework. The approach is supported by state-of-the-art networking application interfaces and simulators. Furthermore, a blended and game learning component favors the engagement via comparison and competition of students’ project metrics. Findings: The experiment is carried out by professors of the Computer Science Bachelor’s degree taught in FAMAF. Results show that the applied methodology met the intended outcomes, and improved by 7% in a two-year cycle. Furthermore, the approach was very well received based on student’s feedback.

中文翻译：

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在未来互联网的背景下修订计算机科学网络动手课程

贡献： 在动手课程偏向于特定技术的情况下，遵循动作研究原理以及积极创新的学习技术，成功地采用了一种新颖的，激发创造力的网络课程来教授创新的教学方法。 背景：已经提出了广泛的面向工程的网络课程，重点是特定协议解决方案。同时，随着未来互联网的出现，技术的数量和复杂性显着增加。结果，该课程失去了对网络算法基础知识的关注。预期结果：我们致力于计算机科学网络中的算法学习，要求学生1）创造；2）发展；3）分析；和4）比较算法和过程，而不管特定于协议的技术如何。预计至少有70％的学生能够达到这一目标，同时在时间紧迫的课程表中提高他们的参与度和动力。应用设计：为实现1）和2），我们设计了一种积极的实验策略，而目标3）和4）则通过创造性的学习技巧来解决，这两种技巧都应用于行动研究框架中。最新的网络应用程序界面和模拟器支持该方法。此外，混合和游戏学习组件通过比较和竞争学生的项目指标来促进参与。发现：该实验由FAMAF教授的计算机科学学士学位的教授进行。结果表明，所应用的方法达到了预期的结果，并且在两年的周期中提高了7％。此外，根据学生的反馈，该方法非常受欢迎。