Predictive role of artificial, moral and spiritual intelligence in academic achievement among PhD scholars in Punjab, Pakistan

Abstract

This study examined how Artificial Intelligence (AI), Moral Intelligence (MI) and Spiritual Intelligence (SI) predict the academic achievement of PhD scholars. A total of 923 participants were selected through stratified random sampling. This method ensured representation from different universities and academic disciplines. A quantitative research design was used. Data were collected through a structured questionnaire. Academic achievement was measured through the participants’ current CGPA. The reliability of the questionnaire was tested using Cronbach’s Alpha. Descriptive statistics, Pearson correlation and multiple regression were used for data analysis in SPSS. The results showed that the participants had high levels of AI (M =3.75, SD = 0.65), MI (M = 4.02, SD = 0.60) and SI (M = 4.11, SD = 0.38). The mean academic achievement was 3.26 (SD = 0.70). Pearson correlation showed significant positive relationships among the study variables. Multiple regression results showed that the overall model was significant, F (3,919) = 34.319, P < .001. The model explained 10.1 % of the variance in academic achievement (R² = .101). AI, MI and SI were significant positive predictors of academic achievement. The study concludes that developing technological, moral and spiritual abilities together can support academic achievement among PhD scholars. Higher education should encourage the responsible use of AI along with moral and spiritual development.