Version Rev0

Dataset for Paper "Towards Increased Diversity in STEM Education: Five archetypes Derived through a Data-Driven Approach Examining a Computer Science Student Cohort

Anonymous;Anonymous

Description

Dataset for Paper "Towards Increased Diversity in STEM Education: Five archetypes Derived through a Data-Driven Approach Examining a Computer Science Student Cohort" - Rev #0 This is the dataset for the paper titled "Towards Increased Diversity in STEM Education: Five archetypes Derived through a Data-Driven Approach Examining a Computer Science Student Cohort". In case of questions, feel free to contact the authors, anonymised, ORCID: https://orcid.org/*anonymised*, current affiliation and email: anonymised ## Survey 2019 ##
The raw survey data for the initial 2019 survey is available in the file survey2019_anon.csv. Note that the data is anonymised as free-text comments have been removed. Explanations on the variables and their levels are given in the files variables_survey2019.csv and values_survey2019.csv.
The questionnaire for the 2019 survey is contained in survey2019_instrument.pdf. ## Survey 2020 ##
The raw survey data for the 2020 survey is available in the file rdata_anon_survey2020.csv. Additional scripts are supplied to reproduce the exploratory factor analysis. The main entry is the file EFA.R, which imports the data. The file contains some comments on the process.
The questionnaire for the 2020 survey is contained in survey2020_instrument.pdf.

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.4

FAIR Score

77%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

License

Creative Commons Attribution 4.0 International

Open Access

Assigned Domain

Subfield

Computer Science Applications

Field

Computer Science

Domain

Physical Sciences

Confidence Score

89%

Source

Open Alex

Keywords

Computer ScienceEducationDiversitySTEMStudent interaction

Normalization Factors

FT

57.69

CTw

1.00

MTw

1.00