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University Faculty Views on Computer Code and Data Submission Requirements

Publisher Primary Research Group
Published Feb 27, 2024
Length 52 Pages
SKU # PF19285332

Description

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 of Contents

52 Pages
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

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