ChatGPT’s Opinion-Based Real-Time Student Age-Group Differentiation Application

This paper developed a real-time online application to explore the differences in students’ perspectives on the educational benefits of Chat-GPT. The primary samples were analyzed after thoroughly validating the assumptions of One-Way ANOVA and Tukey’s Honestly Significant Difference (HSD). Users can view statistical findings along with the hypothesis status within the application. Additionally, Cohen’s d effect size was calculated for the observed differences. The One-Way ANOVA and Tukey’s HSD tests revealed significant differences between the age groups of 26-30 and those under 18, as well as between 26-30 and 2225. Cohen’s d indicated an effect size of 1.07 for the significant difference between the 22-25 and 26-30 age groups, and 0.93 for the difference between the $\lt 18$ and 26-30 age groups. The Tukey’s HSD test also showed substantial differences between the age groups 18-21 and 26-30, as well as 22-25 and 26-30. No other comparisons showed significant differences. More specifically, the higher mean scores for the 26-30 age group imply that maybe because of their maturity and experience, older students may find more educational advantages from Chat-GPT.