A method that includes receiving, from educational institutions, a rule set for each educational institution; receiving, from merchants, user data and usage data for a plurality of users; wherein each user is associated with an educational institution; wherein each educational institution is associated with a branding theme that comprises any one or more of: a name of the educational institution, a name of a mascot of the educational institution, and a color theme associated with the educational institution; calculating, for each user and based on the user data for the user, usage data for the user, and the rule set for the educational institution that is associated with the user, a reward point balance; and displaying, for each user and using the branding theme associated with the educational institution associated with the user, an available reward points balance on a graphical user interface that is associated with the user.

Method, apparatus, and a computer-readable storage device for determining similarities. A plurality of sets having social network service members as entities is constructed by associating each of the social network service members with each of a predetermined selection of professional outcomes by school of graduation of the member. One of the plurality of sets is selected. A similarity algorithm calculates the similarity score of at least some of the plurality of sets in the plurality of sets to the selected one of the plurality of sets, and presents for rendering the k sets in the plurality of sets with the highest similarity scores. The similarity algorithm used may be a cosine similarity algorithm using the sets as vectors.

Methods disclosed for lead generation relate to matching prospective applicants with educational institutions. Prospective applicants provide personal information and educational background information which are used to find matching educational institutions. Methods include enhancing connections between education institutions and prospective applicants by setting up mutually agree appointments. Systems and apparatuses are also disclosed to implement the disclosed methods.

In some examples, an electronic classroom desk includes a desktop comprising a display device, and a processor to authenticate a student at the electronic classroom desk based on received authentication information of the student, and responsive to authenticating the student: cause display, on the display device, of class material selected based on a criterion relating to which class the student is currently attending, and cause display, on the display device, of student-specific information that corresponds individually to the student, without regard to the criterion.

Aspects of the present disclosure generally relates to a method including receiving user data and identifying at least a domain target for the at least a domain as a function of the domain-specific data. Also, the method may include generating a plurality of candidate schedules. Further, the method may include selecting an optimal user schedule from the plurality of candidate schedules. Moreover, the method may include presenting, at a remote device, the optimal user schedule to a user, and tracking, by the computing device, a user's progress with regard to the optimal user schedule.

A system for recommending colleges for students to apply for admission, the system comprises a memory configured to store computer executable instructions and one or more processors configured to execute the instructions to obtain student profile data of a student. Further, obtain college data for each college from a list of colleges. The one or more processors are further configured to determine a college signature for each college of the list of colleges based on the respective college data, using a trained machine learning module. Further, generate a score of admission for each college of the list of colleges for the student, based on a comparison between the student profile data and the respective college signature and generate a list of recommended colleges from the list of colleges for the student using the score of admission corresponding to each college of the list of colleges.

Various methods and systems for automatically recommending academic programs for an applicant are disclosed herein. The systems and methods disclosed herein can involve receiving initial applicant data, applying a historical applicant data model to define an applicant profile for the applicant, applying an employment outlook data model to each initial academic program included in the initial applicant data to generate an employment success score, determining whether the employment success score for each academic program is below a threshold and in response to determining that the employment success score for an initial academic program is below the threshold, applying an employment recommendation data model to recommend employment types and applying an institution success data model to each recommended employment type to identify academic institutions offering relevant academic programs, and identifying at least one of the one or more relevant academic programs and initial academic programs as program recommendations.

A method and system for providing curriculum management services. In an operation, a user may access curriculum management system from a computer terminal. A user may send information and/or commands to a processing module. A user may enter or update information stored in one or more databases. A user may select or be assigned one or more objectives from an objective dataset. An objective module may access one or more databases containing information from one or more objective datasets. Given an objective from an objective set, processing module may request a course dataset from a course module. Information regarding a user's pathways may be sent to a display module for viewing by the user.

A system and/or method can be provided for improving applicant diversity by giving institutions selectable and adjustable application windows, thereby providing a number of benefits including an enriched learning environment. A similar system or method may be used to manage the availability of application windows in general to ensure that a diversity of applicant groups have an opportunity to apply.

A system and/or method can be provided for optimizing data-sharing in a multi-institutional application system using, where appropriate, semi-blind data-viewing in a semi-cooperative context. A method for evaluating agent quality, individual student success probability, and sharing these evaluations among a plurality of applicants to a plurality of academic programs while retaining the confidentiality of individual applicants is shown. Multiple parameters both immediate and historic are used to evaluate agent quality and individual student success probability.