DOI: 10.5061/dryad.bvq83bkgd
title: Dataset with determinants or factors influencing graduate economics student preparation and success in an online environment

description: The data relates to the paper that analyses the determinants or factors
 that best explain student research skills and success in the honours
 research report module during the COVID-19 pandemic in 2021. The data used
 have been gathered through an online survey created on the Qualtrics
 software package. The research questions were developed from demographic
 factors and subject knowledge including assignments to supervisor
 influence and other factors in terms of experience or belonging that
 played a role (see anonymous link
 at https://unisa.qualtrics.com/jfe/form/SV_86OZZOdyA5sBurY. An
 SMS was sent to all students of the 2021 module group to make them aware
 of the survey. They were under no obligation to complete it and all
 information was regarded as anonymous. We received 39 responses. The raw
 data from the survey was processed through the SPSS statistical, software
 package. The data file contains the demographics, frequencies,
 descriptives, and open questions processed.    
    The study reported in this paper employed the mixed
 methods approach comprising a quantitative and qualitative analysis. The
 quantitative and econometric analysis of the dependent variable, namely,
 the final marks for the research report and the independent variables that
 explain it. The results show significance in terms of the assignments and
 existing knowledge marks in terms of their bachelor’s average mark. We
 extended the analysis to a qualitative and quantitative survey, which
 indicated that the mean statistical feedback was above average and
 therefore strongly agreed/agreed except for library use by the student.
 Students, therefore, need more guidance in terms of library use and the
 open questions showed a need for a research methods course in the future.
 Furthermore, supervision tends to be a significant determinant in all
 cases. It is also here where supervisors can use social media instruments
 such as WhatsApp and Facebook to inform students further. This study
 contributes as the first to investigate the preparation and research
 skills of students for master's and doctoral studies during the
 COVID-19 pandemic in an online environment.
description: ## Description of the data and file structure This data note refers to the
 paper that analyses the determinants or factors that best explain student
 research skills and success in the honours research report module during
 the COVID-19 pandemic in 2021.  The data used have been gathered through
 an online survey created on the Qualtrics software package.  The research
 questions were developed from demographic factors and subject knowledge
 including assignments to supervisor influence and other factors in terms
 of experience or belonging that played a role. An SMS was sent to all
 students of the 2021 module group to make them aware of the survey.  They
 were under no obligation to complete it and all information was regarded
 as anonymous.  We received 39 responses.  The raw data from the survey was
 processed through the SPSS statistical, software package.  The data file
 contains the demographics, frequencies, descriptives, and open questions
 processed. The Excel file of data provided has a few sheets included. The
 first sheet provides the sample profile, answers for questions 1 - 7, and
 statistics on the demographics and internet access of respondents. The
 second sheet provides the frequencies and answer distribution (agree,
 disagree) of questions 8 - 29 where questions on the supervisor influence
 and the study material are included. The descriptives are included for the
 latter questions in the third sheet. The fourth sheet provides
 correlations between the same questions provided. The last sheet provides
 statistics on the open questions provided. ## Sharing/Access information
 The data is shared and access granted through Dryad. ## Code/Software Some
 code was used to describe the descriptive data.