The Acoustic Environment and University Students' Satisfaction with the Online Education Method during the COVID-19 Lockdown

Int J Environ Res Public Health. 2022 Dec 30;20(1):709. doi: 10.3390/ijerph20010709.

Abstract

The acoustic environment has been pointed out as a possible distractor during student activities in the online academic modality; however, it has not been specifically studied, nor has it been studied in relation to parameters frequently used in academic-quality evaluations. The objective of this study is to characterize the acoustic environment and relate it to students' satisfaction with the online learning modality. For that, three artificial neural networks were calculated, using as target variables the students' satisfaction and the noise interference with autonomous and synchronous activities, using acoustic variables as predictors. The data were obtained during the COVID-19 lockdown, through an online survey addressed to the students of the Universidad de Las Américas (Quito, Ecuador). Results show that the noise interference with comprehensive reading or with making exams and that the frequency of noises, which made the students lose track of the lesson, were relevant factors for students' satisfaction. The perceived loudness also had a remarkable influence on engaging in autonomous and synchronous activities. The performance of the models on students' satisfaction and on the noise interference with autonomous and synchronous activities was satisfactory given that it was built only with acoustic variables, with correlation coefficients of 0.567, 0.853, and 0.865, respectively.

Keywords: indoor acoustic environment; indoor soundscapes; online education; students’ satisfaction.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19* / epidemiology
  • Communicable Disease Control
  • Education, Distance*
  • Humans
  • Personal Satisfaction
  • Students
  • Universities

Grants and funding

This research was funded by the Universidad de Las Américas (UDLA) and was developed under the research project SOA.VPR.20.03.Covid-Amend (VII Call for research projects of the UDLA).