This exploratory research investigates the interactions between information overload, self-efficacy, and student usage of AI tools in the pursuit of (and selection process for) studying overseas by Indian students. The theoretical foundations of this research are drawn from cognitive load theory (Sweller, 1988) and social cognitive theory (Bandura, 1986). Data were collected from a total of 70 prospective international students who were (or were not) utilising AI tools during their selection process for admission to university for the 2026 academic year in the United States. The results indicate moderate to high levels of information overload (Mean = 3.87; Standard Deviation =0.92) for students surveyed and that there is a negative correlation between students' information overload and their self-efficacy to make decisions (r = -0.48, p < .001). The students surveyed who utilised AI-powered recommendation tools as part of their decision-making process have statistically lower levels (Mean= 3.62, vs Mean=4.35; p<.001; d=to0.85) of information overload than those who did not use AI-powered tools and have statistically higher levels (Mean=3.89VsMean=3.21;p<0;d=to0.92)of self-efficacy compared to their non-user counterparts These findings indicate that the use of AI personalized tools may reduce the amount of information overload experienced by students during their decision-making process regarding complex educational choices while the sample size and self-selection of students limit generalization results This research contributes to understanding how emerging technologies influence international student mobility and related influences on decision making for students during digital recruitment.
Nithin Achuthan (Wed,) studied this question.