Drop out Factors in Data Literacy and Research Data Management Survey: Experiences from Lithuania and Finland
Author(s) -
Jurgita Rudžionienė,
Vincas Grigas,
Heidi Enwald,
Terttu Kortelainen
Publication year - 2018
Publication title -
information and media
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.128
H-Index - 1
ISSN - 2783-6207
DOI - 10.15388/im.2018.82.8
Subject(s) - survey research , survey data collection , descriptive statistics , survey methodology , web survey , ibm , lithuanian , data collection , questionnaire , research data , psychology , statistics , computer science , library science , applied psychology , mathematics , world wide web , linguistics , materials science , philosophy , subject (documents) , nanotechnology
[full article, abstract in English; abstract in Lithuanian] The purpose of this paper is to develop an understanding of factors that affect the respondents to drop out of an already started survey on research data management. We decided to take a questionnaire on data management survey at Vilnius University and Oulu University implemented in 2017 as a case study. The data for the analysis was collected using the questionnaire, which was used in multinational research for Data Literacy and Research Data Management, performed by a group of researchers in more than ten countries, initiated by Serap Kurbanoglu and Joumana Boustany. This paper describes the analysis of 1 185 survey samples, of which 515 were unfinished and 670 finished in both universities. For the analysis of the data, we used Framework for Web Survey Participation created by Andy Peytchev (2009). The collected data was analyzed using IBM SPSS Statistics ver. 19 with descriptive and inferential statistical tests. The most significant factors on deciding not to finish the survey were the length of the survey, the scientific field, experience, age and the topic of the survey. No statistically significant difference was measured between those who finished the survey and unfinished evaluating the data by gender and job position. An important factor in not finishing the survey was the design of the survey.
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