Teaching Challenges in COVID-19 Scenery: Teams Platform-Based Student Satisfaction Approach

• Published in: Sustainability 2020-09, Vol.12 (18), p.7514
• Main Authors: Rodriguez-Segura, Leticia, Zamora-Antuñano, Marco Antonio, Rodriguez-Resendiz, Juvenal, Paredes-García, Wilfrido J., Altamirano-Corro, José Antonio, Cruz-Pérez, Miguel Ángel
• Format: Article
• Language: English
• ISSN: 2071-1050; 2071-1050
• DOI: 10.3390/su12187514

At the onset of the crisis caused by COVID-19, the Mexican education system chose to join the global context and suspend face-to-face classes for all educational levels. For the continuity of educational processes, a transition from a traditional educational model (face-to-face) to emergency remote teaching (ERT) was made through virtual learning platforms and learning management system (LMS) schemes. Universidad del Valle de Mexico (UVM), in a collaboration agreement with Microsoft Co., chose to use Teams to continue its educational process. In this work, we intend to identify the factors that can be taken into account regarding the level of student satisfaction in the teaching–learning process in ERT using Teams, and validate the established educational strategy. Statistical analysis was carried out to analyze the academic environment for these scenario changes while considering knowledge assessment, and competencies achievement. A combined sampling method was applied with convenience and statistical analysis. The main results established significant percentages, where more than 60% of the students surveyed were manifested in the use of the teams and the organization of the class sessions by the teachers, and the activities developed. Using the Cronbach’s Alpha coefficient, the reliability of the data collection instruments was determined. The correlations of each of the survey questions were calculated to determine the relationship between themselves and the total answers, giving results similar to those obtained through data science tools. Taking advantage of the situation, data science tools were applied to compare the results with obtained values from RapidMiner software in the correlation of factors in of 0.440, 0.384, 0.246, 0.048 and 0.384.