Learning computer programming is a challenging process. Among the current approaches for overcoming this challenge, visual programming languages (VPLs), such as Scratch, have shown very promising results for beginners. Interestingly, some higher education institutions have started to use VPLs to introduce basic programming concepts, mainly in CS1 courses. However, an important issue regarding Scratchs usage in higher education environments is that students may feel unmotivated being confronted by programming exercises that do not fulfill their individual expectations. To try and overcome this barrier, we propose CARAMBA, a Scratch extension including an exercise recommender system. Based on features, such as taste and complexity , CARAMBA is able to personalize student learning with Scratch by suitably suggesting exercises for students. An in-depth evaluation was conducted about the effects of our proposal on both the learning of basic concepts of CS1 and the overall performance of students. We adopted an equivalent pretest-posttest design with 88 college students at an Ecuadorian university. Results confirm that recommending exercises in Scratch had a positive effect on students programming learning abilities in terms of pass rates. In totality, the pass rate achieved by our proposal was over 52%, which is 8% higher than the rate achieved during a previous experience using only Scratch (without recommendation) and 21% higher than the historical results of traditional teaching (without Scratch). Furthermore, we analyzed the degree of exploitation of CARAMBA by students to portray two facts: students actually used CARAMBA and there was a significant, positive correlation between the utilization of CARAMBA and the scores obtained by the students.

中文翻译：

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推荐系统和从头开始：增强计算机编程学习的综合方法

学习计算机编程是一个充满挑战的过程。在克服这一挑战的当前方法中，诸如Scratch之类的可视化编程语言（VPL）对初学者显示了非常有希望的结果。有趣的是，一些高等教育机构已经开始使用VPL来引入基本的编程概念，主要是在CS1课程中。但是，有关在高等教育环境中使用Scratchs的一个重要问题是，学生可能会感到不自觉地受到编程练习的挑战，而这些编程练习并没有达到他们的个人期望。为了克服这一障碍，我们建议使用CARAMBA，这是Scratch扩展程序，其中包括运动推荐系统。基于功能，例如味道 和 复杂 ，CARAMBA可以通过适当地建议学生练习来使Scratch个性化学生的学习。对我们的建议对CS1基本概念的学习和学生整体表现的影响进行了深入评估。我们采用了与厄瓜多尔大学的88名大学生相同的测验前测验后设计。结果证实，推荐通过Scratch进行的练习对学生通过及格率的编程学习能力产生积极影响。总体而言，我们的建议所获得的通过率超过52％，比仅使用Scratch的先前体验（不推荐）获得的通过率高8％，比传统教学的历史结果（不包含Scratch）获得的通过率高21％ 。此外，