This study aims to analyze the suitability of fourth-grade teaching modules at SDN 39 Pontianak Utara with the principles of Deep Learning. The study employed a descriptive qualitative approach. Data were obtained through documentation of 15 teaching modules consisting of three IPAS modules, three Indonesian Language modules, three Mathematics modules, three Pancasila Education modules, and three Fine Arts modules. Data analysis was conducted thematically through data reduction, data presentation, and conclusion drawing and verification. The analysis focused on four aspects, namely identification, learning design, learning experience, and learning assessment. The findings indicate that the teaching modules have incorporated several elements of Deep Learning. In the identification aspect, the modules contain initial assessments, graduate profile dimensions, and identification of students' initial knowledge, interests, and learning needs. In the learning design aspect, the modules include learning objectives, active pedagogical practices, learning environments, and digital technology utilization, although learning partnerships remain relatively limited. In the learning experience aspect, all modules provide activities involving understanding, applying, and reflecting. Meanwhile, the assessment aspect includes diagnostic, formative, and summative assessments. However, the implementation of Deep Learning is not yet optimal because the relationships among learning components, contextual learning, reflection, and the use of assessment results as feedback still need strengthening. Therefore, teaching modules need to be developed more coherently so that learning becomes meaningful, contextual, active, and reflective.