Abstract: Academic emotions significantly impact academic performance, with positive academic emotions effectively promoting the learning process. Recently, many outstanding studies have emerged in the field of academic emotion recognition. A systematic review and analysis of these studies are crucial for advancing research in this domain. Firstly, the definition of academic emotions is comprehensively summarized from four aspects: emotion classification, generation mechanisms, measurement methods, and annotation strategies. Secondly, commonly used academic emotion databases and their corresponding evaluation metrics are analyzed and summarized. Then, unimodal and multimodal academic emotion recognition methods are thoroughly examined, along with their advantages and limitations. Furthermore, the application status and effectiveness of academic emotion recognition in real educational scenarios are reviewed. Finally, the challenges faced in academic emotion recognition and future development trends are discussed. A comprehensive analysis suggests that future research in this field should focus on establishing standardized emotion classification frameworks and shared academic emotion databases. Additionally, the exploration and practical application of academic emotion recognition methods still require significant improvement.