STUDENTS’ PERCEPTIONS OF DEEPSEEK IN PAKISTANI HIGHER EDUCATION INSTITUTIONS: THE ROLE OF DEMOGRAPHIC CHARACTERISTICS IN ACCESS, ATTITUDES, AND ACADEMIC CONCERNS
Keywords:
DeepSeek, artificial intelligence, higher education, student perceptions, demographic differences, Pakistan.Abstract
Purpose– This study investigates students’ perceptions of DeepSeek in Pakistani higher education institutions, focusing on accessibility, attitudes, and academic concerns, as well as the role of demographic characteristics in shaping these perceptions.
Design/methodology/approach– A quantitative cross-sectional survey research design was employed. Data were collected from 1,072 university students in Pakistan through a structured questionnaire. The data were analyzed using descriptive statistics, independent samples t-tests, and one-way analysis of variance (ANOVA) using SPSS to examine differences across demographic groups.
Findings– The results indicate that students generally demonstrate moderate to positive perceptions of DeepSeek in terms of accessibility, attitude, and academic concerns. The findings further reveal that gender, age, and university category do not significantly influence students’ perceptions. However, significant differences were observed across faculties and semesters, indicating that academic discipline and level of study play a more influential role in shaping students’ engagement with AI-based tools. Students from science and health-related disciplines reported more positive perceptions compared to those from arts and management fields, while middle and higher-semester students showed relatively stronger engagement than early-semester students.
Originality/value–This study highlights that while demographic characteristics have limited influence, academic context significantly shapes students’ perceptions of AI tools such as DeepSeek. The findings contribute to the growing body of literature on artificial intelligence in higher education and provide practical implications for policymakers, educators, and institutional leaders regarding the effective, ethical, and discipline-specific integration of AI technologies in academic environments.
