Method for matching students with teachers to achieve optimal student outcomes

A computer implemented method for identifying the optimal teachers for a student, the method comprising:

• using a processor of a server computer, the server computer communicatively connected to one or more data electronic interfaces, receiving input data from a plurality of different sources where the input data consists of teacher historical data, teacher biographical data, student historical data, student learning style data, or student biographical data;
• cleansing, validating and storing the input data;
• distributing a first query in real time to retrieve instruction sets from an analysis algorithms datastore;
• spawning the quantity and type of compute nodes as specified in the instruction sets;
• creating automatically a plurality of machine learning models and analysis engines on the compute nodes with the input data per the instruction sets comprising:
• creating prospective new machine learning models and analysis engines using the processor of the server computer, the server computer communicatively connected to a modeler client electronic interface for a modeler to request creating the prospective new machine learning model or analysis engine, the modeler request specifying one or more configuration files, dummy test data sets, source code or object code or executable code, machine learning models, machine learning algorithms, or instruction sets;
• parsing, validating, and storing the data contained in the modeler request by the modeler client electronic interface;
• spawning automatically the quantity and the type of compute nodes based on the configuration file;
• creating automatically the prospective machine learning model or analysis engine based on the configuration files and the instruction sets;
• testing automatically the prospective new machine learning model or analysis engine using the dummy test data sets;
• causing in response to the modeler request from the modeler client electronic interface a rendering or a listing of the results or the errors from the creation and the testing of the prospective machine learning model or analysis engine;
• testing automatically the plurality of machine learning models and analysis engines and storing accuracy and performance results;
• determining automatically from the accuracy and performance results which of the plurality of machine learning models and analysis engines is most accurate and promoting the most accurate to become the winning machine learning model or analysis engine;
• using the processor of the server computer, the server computer communicatively connected to one or more client electronic interfaces for the student to request matches for one or more of the optimal teachers, the student request specifying one or more subject areas, the student biographical data, or the student learning style data;
• distributing a second query in real time based on the student request from the client electronic interfaces to the winning machine learning model or analysis engine and receiving a result set of the optimal teachers in response to the second query;
• causing in real time in response to the student request from the client electronic interface rendering of an interactive display of the optimal teachers.