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Quantitative analysis reveals faculty readiness for AI technology varies by age and educational level.
This study investigated AI readiness using a quantitative descriptive design with a sample of 130 faculty members. Data from a self-constructed questionnaire were analyzed using SPSS 27 and SmartPLS 4.0 for statistical treatment. Anchored on grit theory, the results show that the faculty members have a high level of AI readiness in terms of wellbeing and mental health, changing skill requirements, job automation and displacement, and low level of privacy issues. The independent samples t-test conducted to compare the AI readiness of faculty members aged 18 – 44 years and 45 – 64 years showed that younger faculty members were more ready for AI technologies than older faculty members. The Mann-Whitney U-test results and Cohen’s effect size revealed a significant difference in AI readiness for Protestants and non-Protestants, with Protestants having a higher level of readiness than their counterparts. On gender, the females had a higher level of AI readiness than the males. In terms of educational levels, postgraduate degree faculty members had a higher level of AI readiness than those with up to bachelor’s degrees.
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Mahlon Juma (2025) studied this question.
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