Performing a remediation based on a Bayesian multilevel model prediction

A method, comprising the steps of:

• tracking, by a website, online activities of a plurality of students operating a plurality of student client devices and taking a plurality of online courses, wherein the online activities comprise the plurality of students performing online assignments and online assessments on the plurality of student client devices;
• encoding and storing the online activities of the plurality of students in one or more databases;
• extracting, by one or more servers, courseware-level data derived from the tracked online activities of the plurality of students operating the plurality of client devices and taking the plurality of online courses;
• extracting, by the one or more servers, student-level data for the plurality of students operating the plurality of student client devices from i) the online activities of the plurality of students and ii) registration information entered by the plurality of students encoded and stored in the one or more databases;
• retrieving, by the one or more servers, institution-level data for a plurality of educational institutions from the one or more databases;
• receiving, by the website, a request from a student operating a student client device for an analysis of an online course in the plurality of online courses;
• weighting, by the one or more servers, data for the online course in the courseware-level data;
• generating a prediction from a Bayesian multi-level model comprises a courseware level, a student level and an institution level, wherein the Bayesian multi-level model uses the courseware-level data, the student-level data and the institutional-level data to generate the prediction;
• determining a targeted remediation linked in the one or more databases to the prediction;
• providing access by the website to a webpage, for the student client device, with the targeted remediation based on the prediction;
• and
• performing by the webpage the targeted remediation on the student while the student is operating the student client device.

A method, comprising the steps of:

• tracking, by a website, online activities of a plurality of students operating a plurality of student client devices and taking a plurality of online courses, wherein the online activities comprise the plurality of students performing online assignments and online assessments on the plurality of student client devices;
• encoding and storing the online activities of the plurality of students in one or more databases;
• extracting, by one or more servers, courseware-level data derived from the tracked online activities of the plurality of students operating the plurality of student client devices and taking the plurality of online courses;
• extracting, by the one or more servers, student-level data for the plurality of students from i) the online activities of the plurality of students operating the plurality of student client devices or ii) registration information entered by the plurality of students, encoded and stored in the one or more databases;
• retrieve, by the one or more servers, institution-level data for a plurality of educational institutions from the one or more databases;
• generating, by the one or more servers, teacher-level data for a plurality of teachers teaching the plurality of online courses;
• receiving, by the website, a request from a teacher operating a teacher client device for an analysis of an online course;
• weighting, by the one or more servers, data for the online course in the courseware-level data;
• generating, by the one or more servers, a prediction from a Bayesian multi-level model comprising a courseware level, a student level and an institution level, wherein the Bayesian multi-level model uses the courseware-level data, the student-level data, the institutional-level data and teacher-level data to generate the prediction;
• determining, by the one or more servers, a targeted remediation linked in the one or more databases to the prediction;
• providing access by the website to a webpage for the teacher client device with the targeted remediation based on the prediction;
• and
• performing by the webpage the targeted remediation on the teacher while the teacher is using the teacher client device.