This research examines applying a deep learning approach in teaching Arabic vocabulary (mufradāt) by integrating three main pillars: mindful learning, meaningful learning, and joyful learning. The research explores how these principles can enhance Arabic vocabulary mastery through innovative technology-based strategies. Using the Integrative Literature Review (ILR) method, this study synthesizes relevant literature from indexed journals, academic books, and research reports published between 2020 and 2025. Data was collected from trusted academic databases such as Google Scholar, Crossref, and Scopus. After a rigorous selection process, 12 high-quality literature sources were analyzed to identify key themes, methodologies, and findings. The analysis process involved identifying the theoretical foundation, objectives, methodology, findings, and relevance of deep learning-based mufradāt instruction studies. Key findings from various sources were synthesized to formulate a conceptual instructional model that integrates deep learning principles to enhance the effectiveness of Arabic vocabulary learning. The results show that the deep learning approach improves Arabic vocabulary mastery by encouraging student engagement, contextual understanding, and emotional motivation. Mindful learning enhances focus and retention through reflective practices and multimedia tools. Meaningful learning strengthens long-term memory by connecting new vocabulary with prior knowledge and real-life contexts. Joyful learning increases motivation through gamification, interactive media (such as Duolingo, Kahoot!, and Educandy), and collaborative activities. However, limited technological infrastructure in remote areas can hinder implementation. In conclusion, the deep learning approach supported by mindful, meaningful, and joyful learning strategies offers a transformative framework for teaching Arabic vocabulary. Educators can create engaging, effective, and sustainable learning environments by leveraging technology and student-centered pedagogy.
                        
                        
                        
                        
                            
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