Comparative study of technology with student's perceptions in Indian and Hungarian universities for real-time: Preliminary results

Abstract

The present study was conducted to explore both the differential and inferential analysis of technology applications and benefits in two country university students. In-depth statistical analysis with parametric and non-parametric tests was performed on primary samples collected from Indian and Hungarian universities. We assumed six null hypotheses and their corresponding alternative hypotheses in line three major objectives of our study. The first two null hypotheses were tested with the Student T-test, and the rest of the four hypotheses were tested with Correspondence Analysis (CA) advance dimension reduction approach. Supporting with results of Cramer's V (CV) inclusive Fisher's Exact (FE) and Chi2 tests, an in-depth analysis was also performed. The result of the T-test proved that country variable not impacted by Technology Use due to insignificant p value (p > 0.05). But, Technology Benefit affected two-country students with significant p value (p < 0.05). Surprisingly, the Mann-Whitney U test explored the effect of Technology Benefit and Use on Indian and Hungarian students (p < 0.05). The CA method explored a significant association of Technology Use with Indian and Hungarian student's responses (p < 0.05) yielded two dimensions. On the one hand, it did not find a significant association of Technology Benefit with Indian students (p < 0.05). Still, on the other hand, it explored a significant association of Technology Benefit with Hungarian student's opinions (p > 0.05). The paper's findings are evident in higher technology awareness and association among Hungarian students than Indian students. We also proposed a real-time conceptual design to estimate the differential and inferential analysis using a web application to avoid the conventional method. Our proposed models might be helpful not only for two countries but also for inter-continent institutions to work in a collaborative project to measure; exchange student's and educators' perceptions about the technology. Based on the results, we also proposed a futuristic real-time technology impact identification for a university to integrate with extant "Election," a class response system.