AI and Data Literacy: A Disciplinary Divide
DOI:
https://doi.org/10.55737/trt/v-vi.313Keywords:
AI Literacy, Data Literacy, Higher Education, Gender, Academic DisciplineAbstract
Artificial intelligence (AI), data literacy now influences the study, work, and social life. However, little is known about the distribution of such capabilities within disciplines in developing-country contexts in universities. It was a cross-sectional study that involved 317 undergraduates of the University of Sargodha on self-judged proficiency, objective knowledge, and perceptions and exposure. Internal consistency was high in the questionnaire (Cronbachs =.90). Students expressed moderate confidence and strong interest in further learning. They had a weaker knowledge of the world. The self-assessed proficiency in female students was higher than in male students, t (315) = -3.231, p = .001, d = 0.37. The analysis provided did not show gender difference in objective knowledge and perceptions and exposure. The means of Science students were a little higher than Social Science students in each of the three measures, but none of the differences was statistically significant. Results do not indicate a definite disciplinary split. Instead they demonstrate a mutual desire towards more profound conceptual and critical study. A shared AI and data literacy base should be offered by universities, and related to the issues, skills, and ethical challenges of disciplines.
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