As data and artificial intelligence (AI) technologies have emerged, educational robot system can be aided by edge-cloud platform service which provides low delay service from edge server and powerful performance service from cloud server. As an edge cloud infrastructure realizing the edge cloud-aided smart agriculture system, intelligent edge computing (IEC) is a well-defined foundation. Among the reference points defined for IEC, reference points between terminal entity (TE) and edge networking entity (ENE) can be used for the interaction between agricultural entities, such as sensors and actuators used for educational robot service, and an edge server. By use of the reference points, entities can report the education-related data including configuration and measurement data to an edge server. Then the edge server can analyze and generate the optimal operation model for the smart educational robot service on the basis of the analysis result. For deep analysis requiring high computation power, the analysis and generation can be performed by the cloud. The edge server, then, sends the generated optimal models to terminal entities. To support the above operations, a method to interact on the defined reference points. Rec. ITU-T Q.5001 defines signalling messages for network functions and intelligent data processing. However, in addition to the defined signalling messages, it is needed to support an API. In addition, service-specific API will be helpful to support service-specific functions. This draft Recommendation defines data management interfaces for intelligent edge computing-based educational robot system.