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June 6, 2026Journal of Data Science0 citationsOpen Access

Perceptions and Utilization of GenAI Tools Among Data Science Students and Faculty

AHAbeer M. HasanSMSayed A. Mostafa

Key Points

  • The study explores how students and faculty in data science perceive and use generative AI tools.
  • Survey of 119 student responses and 14 faculty responses
  • Examination of familiarity, usage patterns, benefits, limitations, and instructional support needs
  • Comparison of perceptions across different student subgroups
  • Students predominantly used ChatGPT for coding and writing support, but confidence in interpreting AI outputs was low.
  • Concerns about AI accuracy, reliability, and dependence were common among students.
  • Faculty had a positive view of GenAI but reported limited proficiency and classroom integration.

Abstract

This study investigates perceptions and use of generative artificial intelligence (GenAI) tools among students and faculty in statistics and data science at a historically Black college or university. Survey data from 119 valid student responses and 14 faculty responses were used to examine familiarity, usage patterns, perceived benefits, awareness of limitations, and instructional support needs. Students reported substantial use of GenAI, with ChatGPT as the dominant tool, primarily for coding assistance and writing support. Although student perceptions of AI in data science workflows and careers were generally positive, confidence in interpreting AI-generated outputs was limited, and concerns about accuracy, reliability, and over-reliance were common. Faculty also viewed GenAI favorably, but self-rated proficiency and the frequency of classroom integration remained limited. Comparisons across student subgroups suggested that familiarity with GenAI and awareness of its limitations varied more by academic level than by gender. These findings highlight a gap between AI adoption and AI literacy and underscore the need for structured training, validation practices, and clearer institutional guidance for responsible AI integration in data science education.

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Cite This Study

Hasan et al. (2026) studied this question.

synapsesocial.com/papers/6a23bbeb71a5da9775e77415https://doi.org/10.6339/26-jds1233
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