The invention disclosed herein provides systems and methods for selecting at least one educational institution form a plurality of educational institutions.

The present invention is a system and method that generates a Table of Contents (TOC) customized to the user knowledge about the concept(s) in the user query and the specific context and preferences of the user. The invention identifies search concepts within the search queries, receives search results, and splits the search results into one or more result segments. In a preferred embodiment, a correlation strength between concepts in one or more of the result segments and the user search query, along with reference to the user knowledge, context, and/or preferences determine which result segments are selected in sequenced to form the TOC.

A computer implemented analytical platform for improving the quality of education, the computer implemented analytical platform comprises a data aggregation module configured to collect and aggregate data from one or more data source. The computer implemented analytical platform includes a statistical analysis module for removing the interrelation among one or more variables. The results are passed to a dimensionality reduction module to select one or more variables from a given set of variables. After a selection is made on the number of dimensions/variables to be included for analysis, the data is passed to a feature engineering module, which calculates the importance of each feature/variable and the weight associated with each variable/dimension. A geospatial analytics module determines the gaps in coverage of schools. Subsequently, the data is passed to an analytical engine implementing machine learning algorithms, which are trained using a training and test dataset, the test dataset comprising one or more variables selected by the feature engineering module to optimize the set goals. The machine learning model is tested on the test dataset. An artificial intelligence module is used for prediction of factors for set objectives and a recommendation module is used for prediction of the outcomes based on the set goals.

A blockchain configuration may provide a simple and secure infrastructure for students to identify subject matter experts as tutors and career mentors, as well as earn scholarship funds in the form of microtransactions of digital currency. One example method may comprise one or more of transmitting a query to a network of nodes to respond in exchange for a microtransaction reward of digital currency; receiving a plurality of responses from the network of nodes; determining one or more best responses from among the plurality of responses; transmitting the reward to the one or more nodes that provided the one or more best responses; combining data related to the query, responses, best answers, and microtransactions into a block of data; and recording the block of data on a blockchain. The method may also include validating the query and plurality of responses in exchange for a microtransaction according to a blockchain proof-of-work configuration.

Techniques for training and evaluating machine-learning models for providing student guidance are described herein. In some embodiments, a network service generates a set of clusters that group a plurality of students by similarity. The network service trains a machine-learning model based on variances in outcomes and actions leading to the outcomes for students that belong to a same cluster in the set of clusters. The network service evaluates the machine-learning model for a student that has been mapped to the same cluster to identify at least one action that the student has not performed that is predictive of an optimal outcome for other students that belong to the same cluster. Responsive to evaluating the machine-learning model, the network service presents, through an interface, a recommendation that the student perform the at least one action.

A method for travel planning which includes a customized application and results in efficient customized grouping and coordination of selected locations and destinations based on a combination of user-selected criteria; radius searching; and real-time, simultaneous, multi-source data gathering, analysis, and derivation executed by and presented on a computer or smart device for user preference. At least one embodiment focuses on travel planning for visiting colleges and universities prior to making decisions on where to apply to or where to enroll.

A method of developing an incubator program includes establishing an accelerator organization having tier 1 members and tier 2 members. A suite of EDA tools is licensed or purchased by the organization. The tier 1 members are charged a first fee. The tier 2 members are charged a second smaller fee. The tier 2 members obtain full access to the EDA tools. Tier 2 intellectual property rights are developed through the use of the EDA tools by the tier 2 members. The tier 1 members are provided a first right to offer to acquire or license the tier 2 intellectual property rights from the tier 2 members for a predetermined period of time. The tier 2 members are required not offer to assign or license tier 2 intellectual property to anyone other than a tier 1 member prior to a tier 1 member's exercise of its first right to offer.

The method comprises: retrieving, from a database, a plurality of optimal study paths selected by a plurality of students, wherein each of the plurality of optimal study paths is a combination of courses and their order during a plurality of study terms; determining an estimated attendance for each of a plurality of courses designated in the plurality of optimal study paths; assigning class hours to each of the plurality of courses based on the estimated attendance; optimizing the assignment of class hours of the plurality of courses, wherein the optimization maximizes a number students registered to their respective study paths; and generating an optimal course catalog based on the optimized assignment of class hours.

Systems, methods, and computer program products for determining an application status of an applicant for an educational program may include receiving cohort performance data comprising first data entries for participants that have respectively achieved outcomes for the educational program and applicant performance data comprising second data entries for the applicant, calculating adjusted cohort performance data based on the cohort performance data and first data characteristics, providing a predictor model based on the adjusted cohort performance data and the outcomes, sequentially changing predictive parameters of the first data characteristics to create second data characteristics and creating an adjusted predictor model based on the second data characteristics and the outcomes, calculating adjusted applicant performance data based on the applicant performance data and the second data characteristics, and calculating a probability of success for the applicant in the educational program based on the adjusted applicant performance data and the adjusted predictor model.

One embodiment of the present invention relates to an integrated scholarship management system and a scholarship operation method using same, the technical problem to be solved being to enable the batch processing online of work involving various and complicated processes such as searching for scholarship information, submitting a scholarship application, reviewing and evaluating, selecting a scholarship student, paying a scholarship, reporting tax, etc.