Dataset on the questionnaire-based survey of higher-education student preference on distance education classes during the COVID-19 pandemic.
The data set contains data collected by an online questionnaire. The questionnaire inquired about design students’ preferences regarding distance education formats (distance, in-person, or a combination of both). It was conducted with students (n=279) from a bachelor’s degree in design at a University in Portugal during the first COVID-19 lockdown period. The questionnaire explored the issue by inquiring students about four types of classes (project, drawing, theoretical-practical, and theoretical) and comparing the students’ enrolment years. The survey collected data online using an anonymized questionnaire. This questionnaire was available via an online link sent to the students by email (including first, second, and third-year students) enrolled in the course during the Covid-19 lockdown period (including the 2019-20 and 2020-21 academic years). The survey included 279 participants from 794 students; the sample represents 35% of the total. The average age of the participants was 22,2. The results show that design students prefer in-person formats, and preference for in-person educational formats increases for project-based and drawing types of classes; furthermore, preference for in-person educational formats is higher in second and third-year students than in first-year ones. The results have serious implications for design education: the typical design educational setting may require specific formats for distance education to offer students a satisfactory pedagogical experience. The dataset is available as a Microsoft Excel file (.xlsx) and a .CSV file, which most data upload interfaces should support. The questionnaire’s questions are available as a .PDF file. The data can be used to understand higher-education student preferences regarding distance educational formats.
Steps to reproduce
(1) designing the questionnaire, (2) conduct a pilot test, (3) dissemination of the questionnaire, (4) data gathering, (5) export data to Microsoft Excel (6) check for duplicates or any other inconsistencies, (7) export data to SPSS.