This mixed research aims to analysis and design the Web Game On Descriptive Statistics (WGODS) through the ADDIE model, data science and machine learning. The sample consists of 61 students from a university in Mexico. WGODS is a technological tool (quiz game) that presents various questions and answers about statistics (quantitative and qualitative data). The results of the linear regression (machine learning) indicate that the content and aesthetics of WGODS have a positive influence on the educational process. The ADDIE model allows the organization of WGODS considering the needs of the students. Also, data science identifies 4 predictive models on the use of WGODS in the field of statistics through the decision tree technique. Finally, teachers can transform the organization and development of school activities through the ADDIE model and technology. In particular, WGODS improves the educational process on the quantitative and qualitative data through a pleasant, attractive, simple, easy and useful web interface.

This mixed research aims at the planning, construction and implementation of a web application to facilitate the educational process on the Normal Distribution through the technological, pedagogical and content knowledge of the Technological Pedagogical Content Knowledge (TPACK) model. This study proposes the use of the PHP programming language (technological knowledge), the topics of Normal Distribution (content knowledge) and computer simulation (pedagogical knowledge) to create the Web Application on the Educational Process of Statistics (WAEPS). The sample consists of 61 students who took the subject Statistical Instrumentation for Business during the 2018 school year. The results of the linear regression (machine learning with 50% and 70% of training) indicate that the WAEPS facilitates the educational process on statistics. In fact, the WAEPS promotes the active role in the student, develops mathematical skills and facilitates the assimilation of knowledge about the calculation of upper and lower limits in the Normal Distribution by means of data simulation, interactivity and navigation. Even students consider that this web application is innovative and useful for the educational field. In addition, data science (decision tree technique) identifies various predictive models on the impact of the WAEPS in the educational process. Finally, the TPACK model is an ideal frame of reference to innovate the teaching-learning process through technological, pedagogical and content knowledge.

Esta investigación cuantitativa tiene como objetivo analizar la incorporación del aula invertida en el proceso de enseñanza-aprendizaje sobre las matemáticas. La muestra está conformada por 88 estudiantes de la Facultad de Negocios que cursaron la asignatura Matemáticas básicas para los negocios durante el ciclo escolar 2016. Este estudio analiza el impacto del aula invertida para la compresión, habilidad, aplicación y utilidad de las derivadas. Por medio de la regresión, estas variables son utilizadas para la construcción de cuatro modelos de pronóstico relacionados con las calificaciones del examen parcial. Los resultados obtenidos permiten señalar que el aula invertida representa una estrategia didáctica innovadora, creativa e idónea para facilitar la asimilación y aplicación del conocimiento en el área de las matemáticas.

The objective of this quantitative research is to analyze the impact of the flipped classroom in the educational process on computer science considering data science and machine learning. This study proposes the consultation of YouTube videos (before class), collaborative work through MySQL software (during class) and individual work through MySQL software (after class) in the database subject. The results of machine learning (linear regression) indicate that school activities before, during and after the class positively influence the assimilation of knowledge and development of skills on the administration of the database. Likewise, data science identifies 6 predictive models on the use of the flipped classroom in the educational process by means of the decision tree technique. Finally, the flipped classroom improves the teaching-learning conditions through the performance of creative and active activities.

This mixed research analyzes the use of the Collaborative Wall to improve the teaching-learning conditions in the Bachelor of Visual Arts considering data science and machine learning (linear regression). The sample is made up of 46 students who took the Geometric Representation Systems course at the National Autonomous University of Mexico (UNAM) during the 2019 school year. The Collaborative Wall is a web application that facilitates the organization and dissemination of ideas through the use of images and text. In the classroom, the students formed teams and used mobile devices to access this web application. The results of machine learning indicate that the organization of ideas in the Collaborative Wall positively influences the participation of students, motivation and learning process. Data science identifies 3 predictive models about the use of this web application in the educational field. Also, the Collaborative Wall facilitates the learning process in the classroom through the comparison and discussion of information. Finally, technological advances allow organizing creative activities that favor the active role of students.