This quantitative research analyzes the impact of the Web Application for the Educational Process on Compound Interest (WAEPCI) considering the machine learning and data science. The sample is composed of 46 students who studied the Financial Mathematics course in a Mexican university during the 2017 school year. WAEPCI presents the calculation of the Compound Interest and Compound Amount over a period of four years through the data simulation. The results of the machine learning (linear regression) indicate that WAEPCI positively influences the assimilation of knowledge and development of mathematical skills on the Compound Interest and Compound Amount. Data science establishes 4 predictive models on the use of WAEPCI in the educational process by means of the decision tree technique. The construction of web applications facilitates the active role of students, improves the assimilation of knowledge and allows the development of skills. Finally, WAEPCI improves the teaching-learning conditions on Financial Mathematics through the data simulation.

中文翻译：

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Web应用在教育过程中对考虑数据科学的复合兴趣的影响

这项定量研究分析了考虑到机器学习和数据科学的Web Process for Education过程对复利（WAEPCI）的影响。该样本由46名学生组成，他们在2017学年期间在墨西哥大学学习了金融数学课程。WAEPCI通过数据模拟显示了为期四年的复利和复利计算。机器学习的结果（线性回归）表明，WAEPCI对复利和复利积极地影响了知识的吸收和数学技能的发展。数据科学通过决策树技术建立了在教育过程中使用WAEPCI的4种预测模型。网络应用程序的构建有助于学生发挥积极作用，改善知识的吸收并促进技能的发展。最后，WAEPCI通过数据模拟改善了金融数学的教学条件。