The rapid growth of online learning, especially following the COVID-19 pandemic, has highlighted the crucial role of feedback in ensuring effective English language learning in virtual environments. This study aims to identify and assess the most effective feedback strategies used in online English learning through a Systematic Literature Review (SLR). Using PRISMA 2020 standards, a total of 40 peer-reviewed articles published between 2020 and 2025 were analyzed from the Scopus database. The primary research instrument was a structured SLR protocol, specifically developed and adapted by the authors to ensure consistency in data selection, screening, and thematic synthesis. The outcomes were indicated that formative feedback strategies, artificial intelligence (AI)-based personalization, and integration in instructional design, such as ADDIE and UDL models, were the most effective approaches in improving learners' emotional engagement, intrinsic motivation, and language acquisition. The study also reveals that a hybrid approach combining automated technology and human intervention is more effective in bridging affective and social needs in online language learning. The findings make theoretical contributions to the development of feedback literacy and digital learning design, while offering practical implications for teachers, instructional designers, and policy makers in developing responsive, reflective, and sustainable online learning systems. Study limitations include the lack of a longitudinal approach and the exclusion of non-college contexts, as well as the predominance of survey-based articles from specific regions. Therefore, future research is recommended to employ a blended, cross-cultural, and learner-centered approach.
Hardi et al. (Mon,) studied this question.