Keyword: learning performance

ABSTRACT: This study investigates artificial intelligence (AI) psychological empowerment in education, examining how AI tools enhance students’ sense of competence, autonomy, and engagement beyond the effects of material empowerment (e.g., task performance
improvements). Using a quasi-experimental design, we compared Chinese domestic students in China and Chinese international students in Australia to assess whether AI psychological empowerment is both tangible and more impactful than material empowerment. We highlight several nuanced ways AI fosters personal growth and self-perception. Our findings reveal that, while AI material empowerment is beneficial, psychological empowerment has a stronger influence on motivation and self-perception, particularly for international students compared to local students, despite both groups completing the same English writing task. These results suggest that AI’s role in education extends beyond traditional material support, offering transformative psychological empowerment that enhances students’ confidence in academic contexts. This empowerment reasonably translates into greater personal adaptability and, ultimately, personal growth. The study contributes to the growing literature on AI in education, providing insights for scholars, educators, and policymakers seeking to leverage AI for holistic student development. Notably, generative AI (GAI) emerges as a critical tool for cultural and linguistic adaptation, particularly for immigrant students navigating foreign academic systems. Furthermore, the psychological empowerment effects of GAI appear to be context-dependent, with stronger impacts observed in students facing greater cultural or linguistic barriers. These findings emphasize AI’s potential to foster personal growth and resilience across diverse learning contexts. Finally, we recommend that educational policies and practices be tailored to leverage GAI for immigrant populations, paving the way for more equitable educational opportunities.

ABSTRACT: Theoretical foundations in recent years emphasize that a significant number of students globally continue to exhibit a lack of commitment and motivation in school activities, leading to diminished proficiency levels in specific areas of study. The magnitude of this phenomenon, coupled with its evident social implications, suggests that we are facing restlessness and a growing demand for urgent answers and results. In the educational context, the sociocognitive perspective conceives the construct of self-regulation for learning as the management and mastery of a set of factors that emerge as crucial elements for high-quality learning and, predictably, academic success. To achieve this successful learning, it is crucial to manage and control variables such as volitional control strategies (VCS), planning of academic time management, and procrastination (PR). The purpose of this study is to demonstrate, through the technique of structural equation modeling, that these variables impact students’ self-regulation and predict academic performance. A sample of 565 students (Mage = 12.97) from the 3rd cycle of basic education (7th, 8th, and 9th grades) participated, responding to a set of validated scales for the Portuguese context. The results indicated that students who employ more VCS and plan academic time management more effectively demonstrate higher levels of self-regulation for learning. However, those exhibiting higher levels of PR in school activities show a lower propensity to self-regulate their learning. Deepening the understanding of the elements that influence the learning process is crucial to promoting the quality of education and the development of autonomous, self-regulated, and competent students. A student who values school tasks, adopts self-regulatory strategies in their learning process, and manages their time dedicated to school activities appropriately and insightfully will undoubtedly be moving toward academic excellence.