Innovation in the teaching-learning process of global climate change through the collaborative wall

• Main Authors: Ricardo-Adán Salas-Rueda, Gustavo De-La-Cruz-Martínez, Clara Alvarado-Zamorano, Estefanía Prieto-Larios
• Format: Article
• Language: English
• Published: LUMA Centre Finland 2021-05-01
• Series: LUMAT
• Subjects: Collaborative wall; learning; data science; machine learning; global climate change
• Online Access: https://journals.helsinki.fi/lumat/article/view/1471

The aim of this mixed research is to analyze the students' perception about the use of the collaborative wall in the educational process of global climate change considering data science. The collaborative wall is a web application that allows the active participation of students and discussion of ideas in the classroom. During the face-to-face sessions, the students use mobile devices to share the information and images of the courses through the collaborative wall. The sample is made up of 74 students from the National Preparatory School No. 7 “Ezequiel A. Chávez” who took the Biology IV course during the 2019 school year. The results of machine learning (linear regression) indicate that the organization of ideas and dissemination of information in the collaborative wall positively influence the learning process of global climate change, motivation and interest of the students. Data science identifies 6 predictive models about the use of the collaborative wall in the field of Biology through the decision tree technique. In fact, the use of the collaborative wall in the Biology IV course facilitated the assimilation of knowledge about the global climate change and improved the active participation of the students in the classroom. Finally, the collaborative wall allows the creation of new educational spaces where students acquire the main role during the learning process.