Underlining what matters in higher ed and ed tech: news, vendor updates, and commentary from across the field, in one place.https://theunderline.netlify.app/source/iheduc/https://doi.org/10.1016/j.iheduc.2026.101118https://doi.org/10.1016/j.iheduc.2026.101118Wed, 07 Oct 2026 12:00:00 GMTZiyi Kuang and Xiaoxue LengResearchhttps://doi.org/10.1016/j.iheduc.2026.101115https://doi.org/10.1016/j.iheduc.2026.101115Wed, 16 Sep 2026 12:00:00 GMTYong Qin et al.Researchhttps://doi.org/10.1016/j.iheduc.2026.101116https://doi.org/10.1016/j.iheduc.2026.101116Mon, 14 Sep 2026 12:00:00 GMTDewi Juliah Ratnaningsih et al.Researchhttps://doi.org/10.1016/j.iheduc.2026.101106https://doi.org/10.1016/j.iheduc.2026.101106Tue, 25 Aug 2026 12:00:00 GMTJingjing Zhang et al.Researchhttps://doi.org/10.1016/j.iheduc.2026.101105https://doi.org/10.1016/j.iheduc.2026.101105This study investigates how specific prompting behaviors influence the academic performance of engineering students using ChatGPT. A total of 128 fourth-year students across four engineering programs participated in weekly sessions involving rotating task types: case analysis, engineering design, multi-step…Fri, 24 Jul 2026 12:00:00 GMTLauren Genith Isaza Domínguez et al.Researchhttps://doi.org/10.1016/j.iheduc.2026.101103https://doi.org/10.1016/j.iheduc.2026.101103With the growing prevalence of AI-assisted learning, there has been little research that investigated the intricate impacts of AI use on students' learning. In response to this research gap, this paper based on the Self-efficacy Theory, respectively analyzes the double-edged sword effect of AI use on college students'…Wed, 22 Jul 2026 12:00:00 GMTDu Jingwen and Wang JunResearchhttps://doi.org/10.1016/j.iheduc.2026.101104https://doi.org/10.1016/j.iheduc.2026.101104Tue, 21 Jul 2026 12:00:00 GMTQianru Lyu et al.Research