Students' perception about the use of LMS platforms and smartphones during the Covid-19 pandemic

The aim of this quantitative research is to analyze the impact of LMS platforms and smartphones through data science. The participants are 302 students of the National Autonomous University of Mexico who attended the high school (n = 208, 68.87%) and career of Social Work (n = 94, 31.13%) during the 2020 school year. The results of machine learning (linear regression) indicate that LMS platforms and smartphones positively influence the motivation, satisfaction and assimilation of knowledge. Likewise, data science identifies 6 predictive models about the use of these technological tools. Finally, the incorporation of LMS platforms and smartphones in the school activities allows building new educational spaces during the Covid-19 pandemic. © 2022 Fundacao Cesgranrio. All rights reserved.

Students' Perception about the Use of an Educational Web Application During the COVID-19 Pandemic

SARS-CoV-2 virus has caused universities to update their courses in the distance modality. The general aim of this mixed research was to build and analyse the use of a web application for the educational process about the t-test considering data science. In particular, the professor of the Teaching of Mathematics II course needed to update the school activities because of the new educational demands caused by the COVID-19 pandemic. To facilitate the educational process of math, this teacher decided to build a web application that presents the formulas and calculation of the mean, standard deviation and statistical error to understand the use of the t-test. This technological tool allows the personalisation of learning through the simulation of data. The participants were 42 students from a Mexican university. The results of machine learning indicated that the contents of the web application positively influenced the assimilation of knowledge, satisfaction during the learning process, development of mathematical skills and learning in the distance modality. The decision tree technique allows the construction of four (4) predictive models about the use of the web application for the educational process about the t-test. Finally, educators have the opportunity to improve the teaching-learning conditions during the SARS-CoV-2 virus through the design and construction of web applications. © 2022, Commonwealth of Learning. All rights reserved.

Analysis about the use of technology in the Clinical Method course during the Covid-19 pandemic considering data science

Since the appearance of the Covid-19 pandemic, teachers are updating the school activities of the courses with the support of Information and Communication Technologies (ICTs). The aim of this mixed research is to analyze the students' perceptions about the use of technology in the Clinical Method course considering data science (machine learning) through linear regression and decision tree techniques. The participants are 77 students from the Faculty of Psychology who took the Clinical Method course at the National Autonomous University of Mexico during the 2020 school year. The results of the machine learning technique indicate that the use of Zoom, Moodie, audios and Padlet during the educational process about observation and inquiry in Clinical Psychology positively influence the assimilation of knowledge and motivation of the students. Likewise, data science identifies 8 predictive models about the use of these technological tools in the educational process through the decision tree technique. In conclusion, ICTs allow the construction of new educational spaces that facilitate the learning process from anywhere, allow the active participation of the students at any time and satisfy the educational demand during the Covid-19 pandemic.

Students’ Perception About the Incorporation of Technological Tools in the Educational Field During the COVID-19 Pandemic

Currently, teachers are changing the planning and organization of the courses due to the appearance of the SARS-CoV-2 virus. This mixed research analyzes the perception of students about the use of Google Classroom, smartphones, and Google Meet through machine learning and decision tree techniques (data science). The participants are 76 students from the National Preparatory School No. 6 “Antonio Caso” who took the universal literature course in the 2021 school year. The incorporation of Google Classroom allowed that these students reviewed the contents, consulted the multimedia resources, sent the tasks and established a communication from anywhere. Also, smartphones allowed the communication in the virtual classes, search for information on the Internet and review of the school contents at any time. Lastly, these students used Google Meet to answer their questions, understand the school topics and actively participate. The machine learning technique indicates that the use of Google Classroom, smartphones, and Google Meet positively influence the active role of the students during the realization of the school activities. The decision tree technique determines 3 predictive models about the use of these technological tools considering the profile of the students. In conclusion, technological tools such as Google Classroom, smartphones, and Google Meet play a fundamental role to plan, organize and carry out new educational activities and practices in the distance modality. © 2022 by authors;licensee OJCMT by Bastas, CY.

Teachers’ Perception About MOOCs and ICT During the COVID-19 Pandemic

Technological advances such as Massive Open Online Courses (MOOCs) and Information and Communication Technologies (ICT) allow the construction of new spaces where students consult the information at any time, take the online exams and communicate with the participants of the educational process from anywhere. This quantitative research analyzes the perception of the teachers about the organization of the school activities in MOOCs and use of ICT considering machine learning and decision tree techniques (data science). The participants are 122 teachers (58 men and 64 women) from the National Autonomous University of Mexico who took the “Innovation in University Teaching 2020” Diploma. The academic degree of these educators is Bachelor (n = 35, 28.69%), Specialty (n = 4, 3.28%), Master (n = 58, 47.54%) and Doctorate (n = 25, 20.49%). The results of machine learning (linear regressions) indicate that the organization of the school activities in MOOCs positively influences the motivation, participation and learning of the students. Data science identifies 3 predictive models about MOOCs and ICT through the decision tree technique. According to the teachers of the National Autonomous University of Mexico, the organization of the school activities in MOOCs and use of ICT play a fundamental role during the COVID-19 pandemic. The implications of this research promotes that educators use MOOCs and ICT to improve the educational conditions, create new remote school activities and build new virtual learning spaces. In conclusion, universities with the support of technological tools can improve the teaching-learning process and update the course during the COVID-19 pandemic. In particular, MOOCs represent a technological alternative to transform the school activities in the 21st century. © 2022 by the authors.