Aug 2026· Journal of Global Social Transformation· Vol 2, pp. 188-204· 0 citations· 33 references
TL;DR
The study revealed that the higher the reported level of AI use, the better students’ learning and psychological well-being, and significant differences were also found among the low-, moderate-, and high-AI use groups.
Abstract
Artificial intelligence (AI) is rapidly transforming higher education by reshaping how students access information, engage with academic content, and manage learning activities, while its broader implications for students’ psychological well-being remain an important area of inquiry. This study examined the influence of artificial intelligence on student learning and psychological well-being, with particular emphasis on understanding the educational and human dimensions of AI-supported learning. A quantitative, cross-sectional study was carried out with a sample comprised of 423 students from higher education institutions in Punjab and Sindh. Data on the study variables were collected using a structured research instrument, designed on the basis of the study’s objectives and adopted from the literature, and distributed via Google Forms. The completed research instruments were downloaded to Microsoft Excel, and the data were analyzed using IBM SPSS Statistics. To study the differences between the groups and the study variables, the following statistical methods were applied: descriptive statistics, the independent-samples t-test, analysis of variance (ANOVA) and Tukey HSD post-hoc tests, multiple linear regression, and Cronbach’s alpha and Pearson correlation. The study findings indicated that artificial intelligence (AI) positively and significantly correlated with student learning and psychological well-being. Regression analysis indicated that AI positively and significantly predicted both student learning and psychological well-being. The study also revealed that the higher the reported level of AI use, the better students’ learning and psychological well-being. Moreover, significant differences were also found among the low-, moderate-, and high-AI use groups. The study is a pioneer in addressing the possible positive impacts of ethical AI on learning, well-being, and responsible digital practices, providing a foundation for human-centered AI in higher education.
Artificial Intelligence (AI) is increasingly transforming higher education by providing students with personalized learning support, rapid access to information, and assistance with academic tasks, while simultaneously creating new academic and psychological demands. The present study examined Artificial Intelligence-Supported Education, student stress, and academic performance, with particular emphasis on the moderating role of coping self-efficacy among university students in Punjab and Sindh, Pakistan. A quantitative, cross-sectional research design was used, and data were collected from 423 university students through a structured, adopted questionnaire administered online using Google Forms. The questionnaire measured Artificial Intelligence-Supported Education, student stress, academic performance, and coping self-efficacy using established measurement scales. The collected responses were initially organized in Microsoft Excel and subsequently analyzed using IBM SPSS Statistics. Descriptive statistics, Cronbach’s alpha reliability analysis, Pearson correlation, regression analysis, and moderation analysis were conducted to examine the proposed relationships among the study variables. The findings demonstrated that Artificial Intelligence-Supported Education was significantly associated with student stress and positively predicted academic performance. The moderation findings further showed that coping self-efficacy significantly influenced these relationships by weakening the association between AI-supported education and student stress while strengthening the positive association between AI-supported education and academic performance. The study is significant because it provides an integrated understanding of the educational and psychological consequences of AI-supported learning and highlights the importance of students’ coping resources in determining how they respond to AI-enabled educational environments. The findings suggest that higher education institutions should combine AI integration with responsible-use guidance, psychological support, and coping-skills development to maximize educational benefits while reducing potential student stress.
Unknown authors· Journal of Global Social Tra...· 0 citations
Artificial Intelligence (AI) has become an increasingly important component of higher education, influencing teaching, learning, academic support, and institutional practices. AI-powered tools such as adaptive learning systems, intelligent tutoring systems, virtual assistants, and learning analytics are reshaping students’ academic experiences by improving access to information, supporting self-paced learning, and enhancing engagement. At the same time, the growing use of AI in higher education has raised concerns relating to privacy, ethical use, digital fatigue, and the quality of human interaction in learning environments. Against this background, the present study examines undergraduate students’ perceptions of AI tools and their influence on student well-being and daily academic work in degree colleges of Rajouri District, Jammu and Kashmir.
The study adopted a quantitative approach using a descriptive survey design. Primary data were collected from 387 undergraduate students selected through stratified random sampling from degree colleges in Rajouri District. A structured questionnaire consisting of 25 statements measured on a five-point Likert scale was used to assess five dimensions: mental and emotional well-being, social interaction, academic engagement and performance, ethical concerns and privacy, and inclusivity and accessibility. Data were coded in Microsoft Excel and analyzed in SPSS Version 26 using descriptive statistics such as minimum, maximum, mean, and standard deviation.
The findings reveal that students generally perceive AI as beneficial for reducing academic stress, improving confidence, supporting workload management, and enhancing learning efficiency. Academic engagement and inclusivity emerged as especially strong dimensions, with students reporting that AI tools save time, support self-paced learning, and should be made equally accessible to all learners. However, the study also found that AI tools are not perceived as significantly improving peer interaction, teamwork, or collaborative learning, and many students expressed concern about privacy, ethical use, and mental fatigue associated with prolonged AI use. The paper concludes that AI has considerable potential to enrich higher education, but its educational value depends on balanced, ethical, and inclusive implementation supported by institutional transparency and human guidance.
M. Devi, Darakhshan Anjum· International Journal For Mu...· 0 citations
Artificial intelligence (AI) has transformed higher education by introducing intelligent learning environments that support personalized instruction, adaptive learning, automated assessment, and enhanced student engagement. While AI-supported education offers substantial academic benefits, its implications for students' mental health and psychological well-being remain insufficiently explored. Therefore, this study examined the relationship between AI-supported education and student mental health, This research aimed to identify artificial intelligence-supported education systems and teaching models and the effect that AI-assisted education has on students' psychological well-being and mental state. It focused on health in the field of higher education, balancing the innovations and psychological health of students. A quantitative, cross-sectional study was used. The primary data used were collected by means of a structured questionnaire. The targeted population for this study included both undergraduate and postgraduate students enrolled at public and private universities in Punjab and Sindh, Pakistan, including Bahauddin Zakariya University, The Women University Multan, University of the Punjab, Government College University Faisalabad, Islamia University of Bahawalpur, University of Sindh Jamshoro, Mehran University of Engineering and Technology, NED University of Engineering and Technology Karachi, Foundation university medical college, and the University of Karachi. The specific sample used for this study was convenience sampling. Google Forms were distributed to university mailing lists and academic social media platforms, collecting data from 457 participants. The data were screened using Microsoft Excel. The data were analyzed using IBM SPSS Statistics Version 27. Descriptive statistics and inferential statistics including Cronbach's Alpha, Pearson’s correlation, multiple linear regression, Independent Samples t-test, and One-Way ANOVA were employed for this study. The results showed that AI-supported education positively affected student mental health and psychological well-being, showing distinct demographic patterns for respondents. The results of this study build on established research to show that, when critically applied in the field of higher education, AI innovation may support the enhancement of not only teaching and learning but also the psychological well-being of students. Based on the results, recommendations are made for educators, higher education administrators, and policy makers, as well as instructional designers and education technology entrepreneurs, to aid the development of ethical, student-centered, and psychological support frameworks for the use of AI Learning technologies within the field of higher education.
Batool Butt, Nimra Jamil, Mahira Mirza et al.· Journal of Global Social Tra...· 2 citations
The rapid advancement of artificial intelligence (AI) has transformed higher education by introducing intelligent learning technologies that enhance teaching, learning, and academic management. Despite these advancements, concerns have emerged regarding their potential influence on students' psychological well-being and mental health. Thus, the objective of this research was to analyze the implications of artificial intelligence-based education and the role of digital innovation on students' mental health in the context of higher education. The study adopted a quantitative cross-sectional research design. A survey was the only research instrument. The study population was comprised of under and post-graduate students who attended the public and private sector universities of Punjab and Sindh, Pakistan. The universities were Bahauddin Zakariya University, The Islamia University of Bahawalpur, University of the Punjab, Government College University Faisalabad, University of Sindh, Shah Abdul Latif University, and University of Karachi. A sample of 467 participants was surveyed. The sample was selected using the convenience sampling method. The researcher collected the data using an online survey created in Google Forms. The survey was distributed via university email groups, WhatsApp groups, and other academic online platforms. The researcher downloaded the responses, and data were screened and transferred to IBM SPSS Statistics for analysis. The researcher applied descriptive statistics to analyze participants' demographic data, and used Cronbach's alpha to evaluate scale reliability. To study the relationship of artificial intelligence-based education and the mental health of students, the researcher applied Pearson correlation analysis, and for the role of digital innovation, the researcher employed multiple regressions. The researcher employed an independent samples t-test and a one-way analysis of variance (ANOVA) to assess the impact of demographic variables on students' mental health. The results showed that student psychological well-being improved with Artificial intelligence-enhanced education integrated with digital innovation. Furthermore, developing more engaging, personalized, and supportive learning environments improved student psychological well-being. Implementing Artificial Intelligence ethically and human-centered in psychologically supportive educational practices helped balance innovative technologies with student mental health. The results add to current understanding of Artificial Intelligence in higher education and provide insights for educators, university administrators, and policymakers, as well as educational technologies, to create more sustained digital transformations for greater student psychological well-being.
Amber Sarwar Hashmi, Amjad Hussain, Aisha Aslam et al.· Journal of Global Social Tra...· 0 citations
Artificial Intelligence (AI)-supported education is increasingly transforming higher education by providing personalized learning, immediate academic assistance, and flexible access to educational resources; however, its psychological implications for students remain an important area of investigation. The present study examined the relationships among Artificial Intelligence-Supported Education, Student Anxiety, Academic Engagement, and Coping Self-Efficacy, with particular emphasis on the moderating role of coping self-efficacy in the relationship between anxiety and academic engagement. A quantitative, cross-sectional research design was employed, and data were collected from 268 university students from higher education institutions in Punjab and Sindh, Pakistan. Data were collected through an adopted structured questionnaire using online Google Forms, and the completed responses were organized in Microsoft Excel and analyzed using IBM SPSS. Descriptive statistics, Cronbach’s alpha reliability analysis, Pearson correlation, multiple linear regression, independent-samples t-test, one-way ANOVA, post-hoc analysis, and moderation analysis were employed. The findings indicated significant relationships among the major study variables, with AI-supported education being positively associated with academic engagement and negatively associated with student anxiety. Student anxiety was negatively associated with academic engagement, whereas coping self-efficacy demonstrated a positive association with academic engagement. The regression findings further indicated that AI-supported education, student anxiety, and coping self-efficacy were significant predictors of academic engagement. The moderation findings demonstrated that coping self-efficacy significantly weakened the negative relationship between student anxiety and academic engagement, highlighting its potential protective role in students’ academic experiences. The study contributes to the emerging literature on AI-supported higher education by demonstrating that the effectiveness of AI-based learning should be considered alongside students’ psychological well-being and coping resources. The findings have practical implications for universities, educators, and policymakers in developing AI-supported learning environments that promote academic engagement while addressing student anxiety and strengthening coping capabilities.
Unknown authors· Journal of Global Social Tra...· 0 citations
Artificial intelligence (AI) is increasingly reshaping higher education, yet the psychological mechanisms that determine when and for whom AI-assisted learning translates into academic success remain insufficiently understood, particularly within developing educational contexts. This study examined the relationship between artificial intelligence-assisted learning and academic achievement among university students, with academic self-efficacy tested as a moderating variable, drawing on Bandura's Social Cognitive Theory. A quantitative, cross-sectional survey design was employed, and data were collected from 477 undergraduate and postgraduate students enrolled in public and private universities across Punjab and Sindh, Pakistan, using a convenience sampling technique. A structured questionnaire comprising validated scales measuring artificial intelligence-assisted learning, academic self-efficacy, and academic achievement was administered via Google Forms, and data were analyzed using IBM SPSS Version 27. Pearson correlation analysis revealed a strong, statistically significant positive relationship between artificial intelligence-assisted learning and academic achievement (r = .684, p < .001). Multiple linear regression confirmed that artificial intelligence-assisted learning significantly predicted academic achievement, accounting for 49.9% of the variance (R² = .499, F(1, 475) = 470.836, p < .001). An independent samples t-test showed that students with high academic self-efficacy achieved significantly higher academic outcomes than those with low academic self-efficacy (t(475) = -14.126, p < .001). Most notably, hierarchical multiple regression analysis demonstrated that academic self-efficacy significantly moderated the relationship between artificial intelligence-assisted learning and academic achievement (ΔR² = .029, ΔF(1, 473) = 12.87, p < .001), with the interaction term emerging as a significant predictor (B = .156, β = .142, p < .001), indicating that the positive effect of artificial intelligence-assisted learning on academic achievement was stronger among students with higher academic self-efficacy. These findings extend Social Cognitive Theory into AI-mediated educational settings and suggest that the effectiveness of AI-assisted learning technologies is conditional upon students' belief in their own academic capabilities. The study offers practical implications for higher education institutions seeking to maximize the benefits of AI-based learning tools by simultaneously strengthening students' academic self-efficacy.
Shumaira Rahim, Ziauddin, Saima Zaman Khalil et al.· Aposta: Revista de Ciencias...· 0 citations
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