This invention is about providing a repository of study materials generated by academics who match educational criteria.

An apparatus for evaluating a skill of a user according to an embodiment of the present application including: a transferable feature extraction unit configured to receive problem response information and test score information of a reference domain from a user terminal and extract at least one transferable feature from the problem response information or the test score information; a basic model training unit configured to train a basic model for predicting a test score of a user from the transferable feature and feature information that is usable in common for comparison of skills of a plurality of users in the reference domain and a target domain in which skill evaluation of the user is desired; and a model transfer performing unit configured to transfer the basic model to a skill evaluation model for predicting a test score in the target domain.

An online educational system includes a load balancing reverse proxy server adapted to receive requests from a plurality of student clients and institution clients; a platform coupled to the server, the platform comprising supporting services including tuition and fee payment management, identity and role management, student application status management services; an analytical data warehouse and databases coupled to the platform; a data warehouse coupled to the analytical data warehouse; and a machine learning network coupled to the data warehouse to generate educational recommendations to help students learn.

A method of determining rank of an institution or a student. The method of determining rank of an institution comprises receiving rank information relating to academic performance of the institution; identifying social media data associated with the institution, the social media data comprising text and video data; and analysing sentiment associated with the social media data the analysis including categorising relevance of the social media data. The method also comprises receiving endorsement data; determining strength of the endorsement data; and generating an output rank of the institution, the output rank being generated based on the rank information, the determined relevance of the social media, and the determined strength of the endorsement data.

Operations include aggregating, analyzing, and displaying information about prospects for an educational institution. The system may aggregate prospect information by traversing, for example, lower education databases, social networking websites, or testing organization databases. The system may evaluate prospects which are potential applicants to generate recommendations for contact by a recruiter. Alternatively, or additionally, the system may evaluate prospects which have applied for admission to the institution to generate recommendations for acceptance by an admission officer. The system may recommend a prospect based on the prospect's potential for success in the institution. Success may correspond to metrics such as a likelihood of graduating from the educational institution or a likelihood of obtaining employment subsequent to graduating from the institution. Prospects sharing attributes with previously successful students may be selected for recommendation. Prospects which do not share attributes with previously successful students may not be selected for recommendation.

A computer-implemented method, computer program product and computing system for obtaining a provider evaluation model from each of a plurality of providers, resulting in a plurality of provider evaluation models; generating a dynamic evaluation model based, at least in part, upon the plurality of provider evaluation models; receiving a request for an evaluation response; requesting applicant information based, at least in part, upon the dynamic evaluation model, thus defining dynamic applicant information; and revising the dynamic evaluation model to eliminate one or more non-compatible providers based, at least in part, upon a hypertree-based compatibility structure.

A computer-implemented method, computer program product and computing system for obtaining a provider evaluation model from each of a plurality of providers, resulting in a plurality of provider evaluation models; generating a dynamic evaluation model based, at least in part, upon the plurality of provider evaluation models; receiving a request for an evaluation response; requesting applicant information based, at least in part, upon the dynamic evaluation model, thus defining dynamic applicant information; and revising the dynamic evaluation model to eliminate one or more non-compatible providers based, at least in part, upon an overlap operator.

A computer-implemented method, computer program product and computing system for obtaining a provider evaluation model from each of a plurality of providers, resulting in a plurality of provider evaluation models; generating a dynamic evaluation model based, at least in part, upon the plurality of provider evaluation models; receiving a request for an evaluation response; requesting applicant information based, at least in part, upon the dynamic evaluation model, thus defining dynamic applicant information; and providing at least a portion of the dynamic applicant information to each of the plurality of providers for the purpose of generating the evaluation response.

A computer-implemented method, computer program product and computing system for obtaining a provider evaluation model from each of a plurality of providers, resulting in a plurality of provider evaluation models; generating a dynamic evaluation model based, at least in part, upon the plurality of provider evaluation models; receiving a request for an evaluation response; requesting applicant information based, at least in part, upon the dynamic evaluation model, thus defining dynamic applicant information; and revising the dynamic evaluation model to eliminate one or more non-compatible providers based, at least in part, upon a prefix operator.

A computer-implemented method, computer program product and computing system for defining dynamic applicant information based, at least in part, upon a dynamic evaluation model; and processing the dynamic applicant information to generate one or more provider specific information sets for one or more providers, wherein the one or more provider specific information sets are based, at least in part, upon one or more provider evaluation models.