Educational innovation in virtual environments: a systematic review of methodological strategies post-covid-19 (2020–2025)

This study provides a systematic and detailed review of educational innovation in virtual learning environments, emphasizing the use of active methodologies during the post-COVID-19 period (2020–2025). Employing a mixed-methods approach, the research combines a qualitative documentary review guided by PRISMA 2020 with empirical data collection through surveys and semi-structured interviews involving students and university instructors in Ecuador. Searches were conducted in major databases, including Scopus, Web of Science, ERIC, SciELO, Redalyc, and Google Scholar, to locate empirical and theoretical studies related to higher education, virtual teaching, and active learning strategies. Findings show that gamification, flipped classrooms, project-based learning, and collaborative learning effectively enhance student motivation, engagement, autonomy, and academic achievement. Key challenges remain, such as the digital divide, limited teacher training, insufficient institutional support, and sustainability concerns for implementing innovative pedagogies. Comparisons of student and teacher perspectives reveal alignment regarding the benefits of active methodologies but differences in perceived obstacles: students emphasize technical and access difficulties, whereas instructors focus on professional development and institutional support gaps. The study concludes that context-sensitive integration of active methodologies in hybrid learning environments can substantially improve higher education quality in Ecuador, provided strong institutional policies, ongoing professional development, and inclusive digital infrastructures are implemented. Implications for curriculum design, policy-making, and future research are also discussed, highlighting the need for longitudinal and comparative studies that include both student and teacher perspectives to develop sustainable, culturally appropriate hybrid learning models.