University Faculty Views on Computer Code and Data Submission Requirements
This study looks at how faculty, primarily in the sciences and social sciences, view computer code and data submission requirements from journal publishers, repositories, funding sources, peer review and other sources. The study gives detailed data on the percentage of faculty that submit code, how much they submit, and whether they think submission requirements are too stringent or not stringent enough.
Just a few of this 52-page report’s many findings are that:
More than 38% of faculty at research universities in the sample generated such code or instruction sets.
The key variable in code submissions with journal articles was personal age. The younger the scholar, the higher percentage of code that was actually submitted with an article.
A plurality of 44.54% of scholars felt that no changes were needed in the data submission requirements of peer review, journal publishers, funding sources, repositories and other sources occasionally requiring code or data from scholars.
Data in the report was derived from a survey drawing 339 responses from faculty from 100 colleges and universities in the USA; it was conducted from November 2023 to February 2024.
Data is broken out by variables related to the institutional affiliation of the survey participants (enrollment size, public/private status) as well as personal characteristics such as age, gender and academic field.
- Table 1.1 In your scholarly research, do you generate computer code, AI instruction
- sets, or other information designed to guide computerized analytics?
- Table 1.2 In your scholarly research, do you generate computer code, AI instruction
- sets, or other information designed to guide computerized analytics? Broken out by
- enrollment
- Table 1.3 In your scholarly research, do you generate computer code, AI instruction
- sets, or other information designed to guide computerized analytics? Broken out by
- type of college or Carnegie Class
- Table 1.4 In your scholarly research, do you generate computer code, AI instruction
- sets, or other information designed to guide computerized analytics? Broken out by
- public or private college
- Table 1.5 In your scholarly research, do you generate computer code, AI instruction
- sets, or other information designed to guide computerized analytics? Broken out by
- age of respondent
- Table 1.6 In your scholarly research, do you generate computer code, AI instruction
- sets, or other information designed to guide computerized analytics? Broken out by
- political views
- Table 1.7 In your scholarly research, do you generate computer code, AI instruction
- sets, or other information designed to guide computerized analytics? Broken out by
- tenure status
- Table 1.8 In your scholarly research, do you generate computer code, AI instruction
- sets, or other information designed to guide computerized analytics? Broken out by
- gender of respondent
- Table 1.9 In your scholarly research. do you generate computer code, AI instruction
- sets, or other information designed to guide computerized analytics? Broken out by
- race or ethnicity
- Table 1.10 In your scholarly research, do you generate computer code, AI instruction
- sets, or other information designed to guide computerized analytics? Broken out by
- academic field
- Table 1.11 In your scholarly research, do you generate computer code, AI instruction
- sets, or other information designed to guide computerized analytics? Broken out by
- years at present institution
Research Assistance
Download our eBook: How to Succeed Using Market Research
Learn how to effectively navigate the market research process to help guide your organization on the journey to success.
Download eBook