Task-centered e-learning environments have gained increasing attention from researchers and instructional designers due to their high capacity for enhancing active and interactive learning. However, the lack of a comprehensive and evidence-based conceptual model has created challenges in the effective design and implementation of these environments. This study aims to develop a conceptual model for task-centered e-learning environments based on the 4C/ID model.The present research includes a systematic review of articles published in reputable databases such as Scopus, ERIC, ScienceDirect, and Google Scholar between 2015 and 2024. After screening, 14 articles that met the research criteria were selected for analysis. The findings indicate that task-centered learning environments improve learners' performance in cognitive, psychomotor, and motivational dimensions.The use of adaptive artificial intelligence for personalized feedback, virtual reality for simulating complex tasks, and learning analytics for understanding cognitive processes play a crucial role in optimizing the educational experience. The 4C/ID model enhances learning effectiveness by providing supportive information, procedural guidance, part-task practice, and a gradual design of learning tasks, effectively managing cognitive load.The proposed framework can increase learning effectiveness, enhance self-efficacy, and facilitate knowledge transfer.