Data Quality Procedures in Survey Research: An Analysis and Framework for Doctoral Program Curricula
Saved in:
| Title: | Data Quality Procedures in Survey Research: An Analysis and Framework for Doctoral Program Curricula |
|---|---|
| Language: | English |
| Authors: | Burleson, James, Bott, Gregory J., Carter, Michelle, Sarabadani, Jalal |
| Source: | Journal of Information Systems Education. 2023 34(4):418-429. |
| Availability: | Journal of Information Systems Education. e-mail: editor@jise.org; Web site: http://www.jise.org |
| Peer Reviewed: | Y |
| Page Count: | 14 |
| Publication Date: | 2023 |
| Document Type: | Journal Articles Reports - Research Information Analyses |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Doctoral Programs, Curriculum Evaluation, Curriculum Development, Surveys, Research, Research Methodology, Data Collection, Data Interpretation, Best Practices, Validity, Doctoral Students, Student Research, Research Skills, Information Skills |
| ISSN: | 1055-3096 2574-3872 |
| Abstract: | To ensure validity in survey research, it is imperative that we properly educate doctoral students on best practices in data quality procedures. A 14-year analysis of 679 studies in the AIS "Basket of 8" journals noted undercommunication in the most pertinent procedures, consistent across journals and time. Given recent calls for improvements in data transparency, scholars must be educated on the importance and methods for ensuring data quality. Thus, to guide the education of doctoral students, we present a "5-C Framework'' of data quality procedures derived from a wide-ranging literature review. Additionally, we describe a set of guidelines regarding enacting and communicating data quality procedures in survey research. |
| Abstractor: | As Provided |
| Entry Date: | 2023 |
| Access URL: | https://jise.org/Volume34/n4/JISE2023v34n4pp418-429.pdf |
| Accession Number: | EJ1402339 |
| Database: | ERIC |
| Abstract: | To ensure validity in survey research, it is imperative that we properly educate doctoral students on best practices in data quality procedures. A 14-year analysis of 679 studies in the AIS "Basket of 8" journals noted undercommunication in the most pertinent procedures, consistent across journals and time. Given recent calls for improvements in data transparency, scholars must be educated on the importance and methods for ensuring data quality. Thus, to guide the education of doctoral students, we present a "5-C Framework'' of data quality procedures derived from a wide-ranging literature review. Additionally, we describe a set of guidelines regarding enacting and communicating data quality procedures in survey research. |
|---|---|
| ISSN: | 1055-3096 2574-3872 |
