Abstract: 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.

Abstract: An event recommendation system recommends events for a candidate attendee. The system recommends an event based on characteristics of the candidate attendee and characteristics of prior attendees that attended a prior occurrence of the event. A prior attendee may have a positive or negative experience with the prior occurrence of the event. A positive experience may be defined, for example, as enjoying the event, completing the event, or performing well in the event. A negative experience may be defined, for example, as not enjoying the event, not completing the event, or not performing well in the event. An event is recommended to a candidate attendee if the candidate attendee has similar characteristics to a prior attendee that had a positive experience. An event is not recommended to a candidate attendee if the candidate attendee has similar characteristics as a prior attendee that had a negative experience.

Abstract: Operations include recommending and presenting academic programs for students. An academic program recommendation model generates recommendations based on a target student's specific characteristics. An academic program is recommended to the target student if the target student's characteristics match the characteristics of other students that have successfully completed the academic program. An academic program is not recommended to the target student if the target student's characteristics match the characteristics of other students that have failed to complete the academic program after some threshold period of time. The system presents an interface for comparing multiple academic programs that have been evaluated in view of a target student's specific characteristics. The interface concurrently lists each of a set of academic programs with a corresponding likelihood of success determined for the target student.

Abstract: An event recommendation system recommends events for a candidate attendee. The system recommends an event based on characteristics of the candidate attendee and characteristics of prior attendees that attended a prior occurrence of the event. A prior attendee may have a positive or negative experience with the prior occurrence of the event. A positive experience may be defined, for example, as enjoying the event, completing the event, or performing well in the event. A negative experience may be defined, for example, as not enjoying the event, not completing the event, or not performing well in the event. An event is recommended to a candidate attendee if the candidate attendee has similar characteristics to a prior attendee that had a positive experience. An event is not recommended to a candidate attendee if the candidate attendee has similar characteristics as a prior attendee that had a negative experience.

Abstract: Operations include identifying students at risk of dropping out or transferring from an academic institution. A student risk analyzer determines a risk score for a student, which may be used to determine whether the student is at-risk. The risk score may be based on a combination of factors. As an example, the risk score may be based on a similarity between (a) attributes of the student and (b) attributes of students that have previously dropped out or transferred to other institutions. A student retention interface displays risk information for students in aggregate form or individual form. The interface may display student information in a student-population view comprising aggregate student information. The interface may display a risk-category view comprising a subset of students. The interface may display an individual-profile view comprising detailed information about a particular student. The interface may allow for drill-down navigation between the views.

Abstract: An event management system generates and displays an event schedule for an attendee. An initial order of the event schedule is based on (a) events already completed by the attendee, (b) events to be completed by the attendee to meet an event completion target, and (c) a set of ordering rules associated with the set of events to be completed by the attendee. The event management system may include an interface for modifying the event schedule in accordance with the set of ordering rules. The interface may include an initial set of events, in an initial order with respect to a timeline. The event management system may receive user input including a proposed modification to the initial order of the events. The event management system may or may not permit the proposed modification based on the set of ordering rules.

Abstract: In an embodiment, a first level of confidence corresponding to a first data set presented in a pre-populated form is computed. A visualization suggesting a need for user review in association with the first data set is displayed when the first level of confidence is determined to not meet a first threshold value. In addition, a second level of confidence corresponding to a second data set presented in the pre-populated form is computed. No visualization is presented when the second level of confidence is determined to meet the second threshold value. In an embodiment, an impact associated with an academic course modification is determined and identified according to a user selection from a displayed set of scheduled courses. The impact may include a financial impact, a graduation timeline impact, or a workload impact associated with the modification.

Abstract: In an embodiment, a first level of confidence corresponding to a first data set presented in a pre-populated form is computed. A visualization suggesting a need for user review in association with the first data set is displayed when the first level of confidence is determined to not meet a first threshold value. In addition, a second level of confidence corresponding to a second data set presented in the pre-populated form is computed. No visualization is presented when the second level of confidence is determined to meet the second threshold value. In an embodiment, an impact associated with an academic course modification is determined and identified according to a user selection from a displayed set of scheduled courses. The impact may include a financial impact, a graduation timeline impact, or a workload impact associated with the modification.

Abstract: Operations include recommending and presenting academic programs for students. An academic program recommendation model generates recommendations based on a target student's specific characteristics. An academic program is recommended to the target student if the target student's characteristics match the characteristics of other students that have successfully completed the academic program. An academic program is not recommended to the target student if the target student's characteristics match the characteristics of other students that have failed to complete the academic program after some threshold period of time. The system presents an interface for comparing multiple academic programs that have been evaluated in view of a target student's specific characteristics. The interface concurrently lists each of a set of academic programs with a corresponding likelihood of success determined for the target student.

Abstract: Operations include recommending and presenting career recommendations for students. The system makes a career recommendation based on a recommendation score computed based on student data and employee data. The employee data may be obtained from a variety of sources such as alumni surveys, job recruiting databases, and job market statistics. The system may recommend an employment position for a student, based on an academic program in which the student is enrolled. The system may recommend an academic program for a student, based on a target employment position. The system may present an interface for comparing multiple recommended academic programs or employment positions. The interface may display detailed information about one or more academic programs and/or employment positions.

Abstract: Operations include identifying students at risk of dropping out or transferring from an academic institution. A student risk analyzer determines a risk score for a student, which may be used to determine whether the student is at-risk. The risk score may be based on a combination of factors. As an example, the risk score may be based on a similarity between (a) attributes of the student and (b) attributes of students that have previously dropped out or transferred to other institutions. A student retention interface displays risk information for students in aggregate form or individual form. The interface may display student information in a student-population view comprising aggregate student information. The interface may display a risk-category view comprising a subset of students. The interface may display an individual-profile view comprising detailed information about a particular student. The interface may allow for drill-down navigation between the views.

Abstract: 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.

Abstract: An event recommendation system recommends events for a candidate attendee. The system recommends an event based on characteristics of the candidate attendee and characteristics of prior attendees that attended a prior occurrence of the event. A prior attendee may have a positive or negative experience with the prior occurrence of the event. A positive experience may be defined, for example, as enjoying the event, completing the event, or performing well in the event. A negative experience may be defined, for example, as not enjoying the event, not completing the event, or not performing well in the event. An event is recommended to a candidate attendee if the candidate attendee has similar characteristics to a prior attendee that had a positive experience. An event is not recommended to a candidate attendee if the candidate attendee has similar characteristics as a prior attendee that had a negative experience.

Abstract: An event management system generates and displays an event schedule for an attendee. An initial order of the event schedule is based on (a) events already completed by the attendee, (b) events to be completed by the attendee to meet an event completion target, and (c) a set of ordering rules associated with the set of events to be completed by the attendee. The event management system may include an interface for modifying the event schedule in accordance with the set of ordering rules. The interface may include an initial set of events, in an initial order with respect to a timeline. The event management system may receive user input including a proposed modification to the initial order of the events. The event management system may or may not permit the proposed modification based on the set of ordering rules.