Assessing Undergraduate Student Awareness of Bias in Data Science

This study investigates undergraduate student awareness of potential biases in data science. A survey of 20 undergraduate students assessed their understanding of how bias can manifest in data collection, analysis, and interpretation. The findings reveal a wide range of awareness levels, with 85% of students acknowledging some understanding of the concept but only 45% expressing confidence in their ability to explain it fully. Additionally, 35% of students admitted that their explanation of bias in data science would be mostly guesswork. These results highlight the need for increased educational efforts to ensure students are well-versed in the nuances of bias and its potential impact on data-driven decision-making.

Educational Gaps in Data Science

Biases in Data

Undergraduate Student Data Awareness

Data Collection and Interpretation 

Education

Symposium on Data Science and Statistics (SDSS) 2025