University students' self-assessment of data literacy: A validation study

Area of Science:

• Educational Psychology
• Data Science Education

Background:

• Data literacy is crucial for professionals, leading to its integration into higher education curricula.
• Understanding factors influencing student data literacy is vital for curriculum development and benchmarking.
• The structure of data literacy among four-year institution students remains underexplored.

Purpose of the Study:

• To validate the Data Literacy Self-Efficacy Scale (DLSES) for use with students in four-year institutions.
• To identify the underlying components and structure of data literacy self-efficacy.
• To provide a reliable instrument for measuring data literacy proficiency.

Main Methods:

• Validated the DLSES with 1,816 students from two four-year institutions.
• Employed exploratory and confirmatory factor analyses to determine scale construct.
• Conducted item analysis to ensure validity of scale items.

Main Results:

• Exploratory factor analysis revealed eight distinct factors with 29 items.
• Confirmatory factor analysis demonstrated a strong model fit (CFI=0.994, TLI=0.994, RMSEA=0.053, SRMR=0.044).
• The refined 29-item DLSES proved to be a reliable and valid measure of data literacy self-efficacy.

Conclusions:

• The 29-item DLSES is a validated and reliable tool for assessing data literacy self-efficacy in higher education students.
• The scale can inform curriculum development and guide educators in designing targeted interventions.
• Findings contribute to a better understanding of data literacy components and structure in academic settings.