This Special Issue brings together contributions that share a simple yet powerful idea: if we do not measure, we do not know; and if we do not know, we should be cautious about claiming "innovation." The manuscripts included here address impact measurement from multiple angles-classroom practices, institutional programs, university services, and internal policies-using diverse methodological approaches and, above all, maintaining a clear orientation toward continuous improvement. Broadly, three main strands emerge.A first strand focuses on technological innovation and pedagogical design, presenting studies that evaluate concrete interventions. For example, one paper examines the use of immersive virtual reality laboratory practices to strengthen learning and academic performance (Ramírez Gallegos et al., 2025), showing that technology's potential depends heavily on training and on the instructional design of the intervention. Complementing this, another study explores the integration of 3D printing technology (Monroy-Peláez et al., 2025) into challenge-based learning experiences in engineering, assessing its effects on the quality of proposed solutions and on students' attitudes toward problemsolving. In addition, a mixed-methods study on VaKE-guided online discussion forums (Xu et al., 2025) analyzes changes in critical thinking styles, student engagement, information-seeking behaviors, understanding of social issues, and cognitive flexibility-highlighting the importance of careful instructional facilitation. In parallel, a systematic review on digital competence in the COVID-19 context (Zhao et al., 2025) synthesizes trends and persistent gaps and argues for strengthening professional development to sustain improvements in achievement and educational quality.A second central strand addresses student trajectories, academic success, and employability. Evidence is presented on the formative value of professional internships from students' own perspectives (Gutiérrez-Pulido it is the cornerstone on which educational innovation rests, because it allows us to evaluate-through evidence-what works, what does not, and why. This Special Issue invites the field to move beyond simply trying "new things" and toward building a grounded understanding of what worked, for whom, under what conditions, at what cost-or, alternatively, why it did not work. Evidence will not always confirm what we hoped to hear, but it enables informed decisions and supports the consistent use of teaching approaches that genuinely improve learning outcomes.
Rincón-Flores et al. (Thu,) studied this question.