This study is aimed at providing solutions to problems in the field of science and technology education, as well as approaches to improve its effectiveness. This study’s specific goal was to ascertain how inquiry-based learning, when aided by instructional technology, raises student success and fosters their capacity for scientific inquiry. In this paper, we investigate a technology-supported intervention that facilitates students to actively generate and solve questions in a cycle of science inquiry in a primary (elementary) school. Through utilizing a question generation technology platform with a guided pedagogical framework, the teachers purposefully leveraged on students’ generated questioning to design and implement a process of creating and presenting their inquiries. The questioning-driven dialogic exchanges took place in the classroom setting, as well as during online interactions outside of the class. Our empirical study, as demonstrated by quantitative and qualitative analysis, connotes a positive causal effect of students’ generated questioning to their cognitive performances, and their noteworthy differences of attitudes towards science between the experimental and control groups. The results uphold the value of fostering students to generate questions for their inquiries and learning. We also highlight the importance of teachers’ awareness of pedagogical design and enactment, enabled by technology, in order to adapt to the profiles of students’ generated questioning for fostering productive cognitive performances.

As artificial intelligence (AI) becomes increasingly embedded in education and society, cultivating critical AI literacy has become a key objective of sustainable higher education, enabling learners to engage with AI responsibly, critically, and throughout lifelong learning. However, empirical evidence on how innovative pedagogical approaches foster critical AI literacy remains limited. This quasi-experimental study evaluated a critical thinking-oriented flipped instructional model in an AI general education course. Following data screening, the final analytic sample consisted of 82 undergraduate students (53 in the Experimental Group and 29 in the Control Group). Closely aligned pretest and posttest forms assessed critical AI literacy across knowledge, skill, and attitude dimensions. Between-group gain-score comparisons showed that the Experimental Group demonstrated greater improvement in overall critical AI literacy than the Control Group (Cohen’s d = 1.12, 95% CI [0.63, 1.60]). Greater gains were also observed for knowledge (d = 0.54), skill (d = 0.84), and attitude (d = 1.21), with the standardized between-group difference descriptively largest for attitude. These findings suggest that the critical thinking-oriented flipped instructional model is a promising approach for cultivating critical AI literacy in higher education and may have broader implications for sustainable higher education.