WO2013066868A1 - Student retention method and system - Google Patents

Abstract

A method, device and computer program product for collecting survey data to provide an institution into individual and campus-wide student trends, characteristics and matches. Combining this data with the institution's existing application data is used to connect incoming and existing students through social networking sites to fellow students, clubs, organizations, and campus resources available at an institution (e.g., student connections and reporting tool).

Description

[0001] This application claims benefit of priority under 35 U.S.C. § 119(e) to the filing date of U.S. Provisional Application No, 61/553,645, as filed on October 31, 2011, which is incorporated herein bv reference in its entirety.

BACKGROUND

[0002] Today, higher education degrees (Post high school certificates, Associates and Bachelors Degrees) have become the accepted minimal education to gain access to higher paying jobs. This requirement of advanced education has created a higher demand upon institutions to provide degreed graduates. As institutions have rushed to provide these graduates they have increased enrollment, and in some cases lowered entry requirements. The result of this expansion over the past decade has been an increase in the number of students who leave the institution in the first year (First Year Retention) which has reached a low of 69% nationwide resulting in reduced graduation rates. A third area of concern to higher education is the enrollment yield of an educational institution, which is the percentage of students that are accepted at an institution and then register for classes. Current enrollment yield figures indicate that approximately 40% of the students accepted, by an institution, actually show up for classes. The costs of the three key areas of enrollment yield, first year retention and graduation rates have reached an all time high. Current methods to recruit and retain students through graduation have involved the collection of data from student on satisfaction and personal data after they have arrived on campus. This generally takes place 6 to 8 weeks after classes have started with results arriving back to the institution from four to six weeks after the survey data has been collected, It provides an "autopsy" of sorts for those students who leave at the end of the first semester and at the end of the first year, Typically the data is on one or two of the aspects of the student experience, institutional fit, social interests and likes and dislikes.

SUMMARY OF THE INVENTION

[0003] To address the above issues, embodiments of the present invention are directed to improve enrollment yield, student retention and higher graduation rates in higher education institutions. According to one embodiment, a process collects and analyzes data on a college or university's student population delivering a model that solidifies the relationship among the student population and the institution's administration. According to an embodiment, a software engine creates a proactive approach to improving campus interaction using technology developed in the areas of psychology and machine learning. The focus of this process is on improving enrollment yield and student retention thus allowing the institution to better manage the "Costs" and "Risks" associated with these areas (Risk Management). Tool sets have been developed to assist higher education institutions to define, predict and manage risks associated with enrolling and retaining their students. These "Risk Management" tools provide significant return on investment to the institutions beginning in the first year of implementation and increasing through the first four year cycle.

[0004] Additionally, embodiments of the present invention relate to collection and collation of data prior to registration of a user. Engagement upon acceptance significantly improves enrollment yield. Data collected over time will offer insight into who is likely to enroll and who is not and creates insight into where to spend recruiting dollars, Engagement with accepted students allows a pre-arrival on campus connection. This connection will allow for much more rapid adjustment to campus and college because it connects the incoming individual with persons with similar interest, clubs and organizations giving them the introduction and connection needed for easy adjustment to campus. Embodiments of the invention include data collection, modeling, and measuring algorithms that are used on a unique set of information used proactivelv. This early data collection and analysis allows institutions to use personality, fit, social fit and preferences, and academic requirements to assist, the student in early engagement with the institution. This process also allows institutions to include the data collected from each applicant in the analysis process.

[0005] In addition, this process connects incoming accepted students to other incoming classmates, activities and individuals on campus with similar interests and hobbies. The incoming students are also connected to clubs, organizations and activities by matching them with the areas of interest, they define. This early engagement acclimates newly enrolled students and creates a sense of belonging with the institution, Academic requests made through the system will assist with the newly accepted student to find resources before they actually enroll, This prevents many students from waiting too late in the first semester to get the assistance they may need to thrive academically.

[0006] Embodiments include collecting multiple data points, personality, institutional fit, academic needs and requirements, social interests and clubs / organizations/academic support all in one database. The institution is allowed to add the collected application information to the database. The inclusion of all these aspects of the student allows the specially designed data process engine and the algorithms designed to provide the institutions with the capability to correlate data to determine the following (1) which of the applicants are most likely to register for classes, (2) which are most like to be retained in the first year, and (3) which are most likely to stay through graduation, in addition to the identification process of these areas, the present disclosure also assists in improving the actual yield of accepted students to the number that register for classes. The two main reasons for student attrition includes: 1) lack of social engagement with other students & social organizations, and 2) the inability to connect academically.

[0007] Aspects of the present disclosure provides the following approach: (1) connect and survey students immediately upon acceptance, (2) immediately upon completion of the survey connect the accepted student to all other incoming students and current students at the institution based upon social and personality matches, providing academic assistance and information immediately at that time, (3) use a scientifically based matching algorithm to select potential roommates and allow multiple reselections if requested, (4) correlate application data automatically using the retention engine to provide a total view of the student to the institution, (5) allow the students to interact with all their matches on a common computing platform to match them with students with similar athletic, social, academic interests as well as with the school activities and functions, (6) provide the institution the ability to analyze the data on individuals, the entire school or sub populations to determine the clusters of individual that best fit within the organization, providing analysis on all students that leave the institution and identify possible characteristics that identify the most likely to succeed (by clusters) at the institution.

BRIEF DESCRIPTION OF THE DRAWINGS [0008] Aspects of the present invention are further described in the detailed description which follows in reference to the noted plurality of drawings by way of non- limiting examples of embodiments of the present invention in which like reference numerals represent similar parts throughout the several views of the drawings and wherein:

[0009] Figure 1 is a block diagram of a method and system for student retention according to the present disclosure according to an embodiment

[0010] Figure 2 is another block diagram of the core model of the method and system for student retention according to the present disclosure according to another embodiment

[0011] Figure 3 is a flowchart of the system for student retention according to the present disclosure according to an embodimen

[0012] Figures 4-5 are block diagrams of systems for student retention according to some embodiments.

[0013] Figures 6-9 are flowcharts of methods for student retention according to some embodiments.

[0014] Figure 10A is an exemplary graphical representation of student empirical data resulting from the system according to the present disclosure according to an embodiment

[001S] Figure 10B is an exemplary graphical representation of student empirical data resulting from the system according to the present disclosure according to another embodiment [0016] Figures 11-21 are exemplary graphical representations for student retention and assistance according to various embodiments,

DETAILED DESCRIPTION

[0017] As will be discussed in more depth below., one embodiment of the present disclosure includes a two part solution to student retention: (1) a dashboard tool providing data-driven insight to the administration (hereinafter "administrative reporting") and (2) a student social media portal using social networking sites [e.g., Facebook®) to match students to fellow students and to of-interest organizations and resources (hereinafter "student connections and reporting").

[0018] Embodiments of the present invention provides surveys to collect information on personality, institutional fit, social and academic characteristics and roommate matching to provide the administration with empirical insight into individual and campus wide student trends, characteristics and matches. Combining this data with the institution's existing application data enables the most powerful analytical tools available (e.g., administrative reporting tool). This data is also used to connect incoming and existing students through social networking sites to fellow students, clubs, organizations, and campus resources available at an institution (e.g., student connections and reporting tool).

[0019] As previously mentioned, some aspects the present invention takes a proactive approach to student retention problem with its risk management solution, focusing on the individual student immediately upon acceptance, creating a connection with the institution. This connection includes individual student-to-student connections, student-to-clubs/organizations connections, student-to-academic resources and a scientific roommate matching capability.

[0020] The data is processed by a tool referred to herein as a "scoring & analysis engine" which delivers the content to the risk management system, The scoring & analysis engine is a software product and is designed to aid in the early engagement of students and the quantitative analysis of the data collected in the initial survey and data input from the individual student applications.

[0021] Significant results expected from the use of the risk management solution include an increased enrollment yield and improved retention, and higher graduation rates, each of which is discussed below.

[0022] For increased enrollment yield, results expected include: (1) immediate connectivity of the student to student (incoming class) and incoming student to current students creates an immediate connection with people with the same interests; (2) improved integration of transfer students as they now have a method to connect to their new institution; (3) improved outreach of clubs and organizations to new and current students who indicated an interest in their organization; (4) immediate access to academic resources prior to arriving on campus; and (5) an ability to analyze data on those students that accepted but did not register.

[0023] For improved retention, the results relate to: (1) an ability to correlate data on the existing student body creating a clusters identifying best fit benchmarks (Figure 10A and 10B); (2) using the obtained data to assist with the lowest retention groups (minority groups, academically challenged, first generation college students): (3) an ability to analyze data on those students that registered but left the institution by timeframe (first 6 weeks, first semester, 1^st year, other time frames), indicate the level of engagement of individuals, and correlate clustered groups based upon data entered by institution, and (4) connecting students to other students and campus clubs and resources prior to typical formation of any problems.

[0024] To implement this concept, embodiments of the present invention may include what is referred to herein as a "student connections and reporting" module (for use by the accepted applicant and current students) and an "administrative reporting" module (for use by the institution's faculty and administration).

[0025] Embodiments of the present invention further includes sophisticated data collection, modeling, and measuring algorithms that are used on data sets, as delivered in the "student connections and reporting" and "administrative reporting" modules, (prior to a student's registration at an institution). This early data collection and analysis allows institutions to use personality, institutional fit, social fit and (personal and social) preferences, and academic requirements to assist the student in early engagement, with the institution. This process also allows institutions to include the data collected from each applicant in the analysis process. Not in the previous art provided or anywhere else in practice or in the literature are all these facets and factors collected and used in a consolidated database to measure and provide input for institutions to understand their student body, their needs, and the insight to analyze lost students. The timing of this data collection is also important as the collection by an institution of this data has not been done prior to the arrival of the student on campus for registration.

[0026] In addition, this process connects incoming accepted students to other incoming classmates, activities and individuals on campus with similar interests and hobbies. The incoming students are also connected to clubs, organizations and activities by matching them with the areas of interest they define. This early engagement acclimates newly accepted students and creates a sense of belonging with the institution well before they arrive on campus for class registration. Academic requests made through the system will assist with the newly accepted student to find resources before they actually enroll. This prevents many students from waiting too late in the first semester to get the assistance they may need to thrive academically,

[0027] Ail of these processes are implemented using the process described herein in the form of personality, institutional fit, social and academic matching of individuals to institutions. The present disclosure discusses: (1) the overall process of including personality, institutional fit, social, academic characteristics and traits, and roommate match in one complete solution designed specifically for the higher education environment (colleges, universities, community colleges, technical schools, and on-line educational institutions) providing benchmark solutions with a multiple clustered approach to improve reliability and measurement (individual process, standard questions plus specific questions designed for the individual institution, measurement and comparison scales specific to the institution); (2) roommate matching algorithms and the process that has been developed using proprietary personality, fit, and social data for the match; (3) methodology of quantifying, comparing, and presenting the data for analysis of the retention problem (dashboard format and presentation); (4) the "scoring & analysis engine" and its processes - which includes the process, personality, institutional fit, social, academic and roommate match surveys, the scientific algorithms used to analyze this data (scoring & analysis engine), the reporting process (wherein a "dashboard" used to display/present reports and is used to apply the database engine to provide retention programs for future incoming classes); (6) an overall solution delivered by the risk management system that assists colleges, universities, community colleges and technical schools and on-line schools to successfully integrate new incoming students, and transfer students to become adjusted to the institutions' environment, both socially and academically. To create a method to identify early problems and assist those students in adjusting more smoothly to the environment.

0028] The administrative reporting dashboard provides usable data and interactive reports throughout the enrollment process and student life cycle to create a data revolution on campus. The software provides the analytical and reporting capabilities available for understanding students and determining the reasons for student success and retention. The present disclosure provides a true risk management tool to address the retention of students while providing a lower cost structure.

[0029] The dashboard provides interactive reports and database mining and query capabilities on ail available data, both current and historic: (personality, institutional fit, social and academic values). The following highlights some of the data that may be provided by the present disclosure: (1) survey completion of accepted and enrolled students; (2) social engagement statistics (through "student connections & reporting" usage); (3) application and demographic data with drilldowns to individual students; (4) financial and academic assistance requests; (5) retention reports on characteristics of students leaving and being retained at critical points within the student life cycle; (6) aggregate personality and fit characteristics to understand the characteristics of the student body and provide targeted early intervention where needed; (7) targeted resource allocation through interactive reports on the most popular clubs/organizations on campus and the interests of incoming and existing students; (8) advanced student search features to find students with specified characteristics; (9) track aggregate characteristics of students who leave and are retained in real time; and (10) individual student profiles with personality and fit characteristics, social and academic interests, and the ability to record and review meeting notes with each students.

[0030] For roommate matching, specially designed algorithm are utilized. The

"student connections and reporting system" utilizes an engagement portal designed to combine the individual survey data and the roommate match questions and process them through the scoring and analysis engine to obtain the optimal roommate match. This solution also allows the incoming student to request additional matches from the system.

Below is a chart that indicated the service provided to the student and their benefit.

[0031] Figure 1 is a flowchart of an example of a method for the scoring and analysis engine. As illustrated, scientifically designed surveys are provided to the institutions applicants immediately upon acceptance to the institution. These include questions collecting data on personality, institutional fit, social preferences and interests and academic resources they may want to request. This data has information on personal interests, athletic and social interests. All students are required to complete the institutions application which has data ranging from hoard scores, high school grade point averages, class standings, college academic major and many more items. This data has been incorporated into a relational database to be used as yield rates are identified, retention data is collected and graduation rates are studied.

[0032] Correlations among all data collected and desired or undesirable results are collected and analyzed by the scoring and analysis engine (illustrated in Figure 1). This engine uses algorithms to synthesize the data from the surveys and database and create meaningful relationships and conclusions for the educational institution. These results are presented in two formats, one for administrative (shown in the block labeled "administrative reporting") and another for the student (shown in the block labeled "student connections & reporting"). The administrative reporting module provides dynamic dashboards to present the information in easy to use graphical format employing the analytical and data organization tools of the system. The format provides the capability to view both aggregate and individual date on the students. Also available in this system are the roommate matching algorithms and tools.

[0033] The student connections and reporting module provides early engagement for the accepted applicant connecting them to other students and to the institution, such as fellow students, clubs, organizations, and campus resources. Campus resources are available and can be used prior to arriving at school and after the student is registered and on campus. All the student connectivity is focused through a social network, such as Facebook®.

[0034] Figure 2 is a diagram of an analysis method, referred to herein as the

"POWeR analysis model", This system was developed to provide the scoring and analysis engine with the method to weight responses from accepted applicants in order to compare and match individuals. The system uses the response to survey questions measuring purpose, openness, willpower and resourcefulness that are referred to as process elements. These elements are broken into sub elements as shown in Figure 2. They include committed, challenge seeking, control, creative, adaptable, curious, hard-working, prudent, stable, proactive, confident, and hopeful. Further discussion of these elements individually, and their interaction as a group with the risk management solution follow.

Process Elements Discussion

[0035] Embodiments of the present invention include the process elements to collect and analyze applicant specific information on incoming students to determine the likelihood an individual will succeed at a specific institution. This determination is achieved by using the process elements (Figure 1) to create a unique model for each institution and then match the applicants to this model. The risk management solution is designed to be an iterative process, improving each year by using the results to identify changes in the process element model and adjusting the baseline each year using the data generated by the system.

[0036] The process elements may include collection of data in these areas of personality, institutional fit, academic needs and social activities and clubs. The personality element is defined by the POWeR personality model (Figure 2) and is developed in conjunction with each client to match their student body and their environment. The POWeR model is discussed in more depth below.

[0037] For the institutional fit element, specific questions are developed to define the client institution and are used to determine if the student is a fit to that institution. Being sure that this fit is present prevents the institution from assuming that the student is fully familiar with the unique elements of the institution, including the environment and the facilities they provide. This also provides the ability to determine how satisfied they might be entering the present environment.

[0038] For the academic element, data collected in these areas will add insight into the personal academic strengths and weakness the applicant identifies and will help match resources to those needs. Academic and social interests, areas of need, preferred types of assistance and immediate engagement further the value provided by this element. Study habits and preferred environments for studying will also be used in the roommate match process. For the social element, this element allows the institution to gather pertinent information on the student's activities and interests (social, athletic and other extracurricular activities) to assist in the immediate connection upon acceptance. Incoming prospective students will be connected to all clubs, and social and athletic activities. This data may also be utilized in the roommate matching process.

[0039] Embodiments of the present invention may be implemented at an institution in the following manner, A meeting with the institution occurs, and specialized questions (by Process Element) are developed and added to the Personality, institutional fit, and school clubs, organizations, activities and special interest groups and academic groups. [0040] Meetings are held with each of the organizations identified to develop the necessary data to create the student connections and reporting pages on the site.

[0041] The institution establishes the necessary policies and procedures to input the data into the system,

[0042] Roommate matching provides contact information to allow individuals to connect and to discuss their personal preferences and determine if they agree to the match.

[0043] Agreement on access is reviewed to enable the system to be configured to allow those granted access to use the risk management solution.,

[0044] Videos must be developed specific to each campus to instruct new students, existing students, and faculty on the system, how to use and who to call for assistance.

[0045] Current students registered at the institution are contacted by the on campus clubs, activities and organizations to get participation in populating the initial database. Applicants are contacted immediately upon acceptance and are introduced to the systems capability and use (for student connections and reporting).

[0046] Immediately upon completion of the survey the incoming applicant is connected with the campus and their matches on student connections and reporting pages via a social network (Facebook®) connection or other connection.

[0047] To add additional data for analysis along with the survey data, each school may provide data collected on the application to the scoring & analysis engine.

[0048] Students who have elected to have roommates assigned are sent the roommate match questionnaire and entered into the pool of students for matching. When the school triggers the system a machine learning algorithm is used to match the most compatible students as roommates. Once notified, the student is encouraged to contact their match and enter accepted in the system. If they wish to re-match to another student, this can be done via the system by responding to the student match link requesting another roommate match. The school determines in their policy how many re-matches are allowed.

Phase Two - Process Elements Inter-relation to the Retention Engine

[0049] Phase two of the scoring engine analysis takes place after the student connections and reporting module is populated and after social, academic, and roommate matches are complete. Once the students register, the system records their enrollment and provides data analysis from the scoring & analysis engine, compiling data on those students that were accepted and did not register, and collecting data on those students that were accepted and registered,

[0050] Data analysis is available through the dashboard for the following: personality, institutional fit, and social preferences and interests of the students. Additional analysis is available to identify common characteristics of the students in any category [e.g., those that, did not register, those that registered but did not stay through mid terms first semester, those that leave after first semester, and those that leave after the first year, etc.). All these and more categories can be set and all correlative data that identifies a student that might fall into any of these categories is processed and identified as risk factors or indicators of positive results is made available to the institution.

The POWeR Benchmark Model (Figure 2 )

[0051] To accurately collect and analyze applicant information a unique and leading edge solution has been developed called the POWeR Benchmark Model, as previously mentioned. The term "POWeR" stands for Purpose, Openness, Willpower, and Resourcefulness Modes of behavior. Each of these behaviors has traits as shown in Figure 2 and explained below.

Personality Data: Personality Traits That Predict Academic Success

[0052] Personality reflects an individual's characteristic patterns of thought, emotion, and behavior, together with the psychological mechanisms behind those patterns. Many studies show that personality characteristics predict academic success even after controlling for high school GPA and test scores. Although there is still considerable debate on this topic, some industrial psychologists have argued that personality tests have less risk of adverse impact than cognitive ability measures, a concern that extends to cognitively-loaded tests such as the SAT or ACT. Adverse impact concerns still need to be investigated in the higher education context, but personality measures at least offer the promise of fewer ethnic group differences than other psychological measures. Finally, personality measures are relatively easy, fast, and inexpensive to administer, making them highly useful in practical settings.

[0053] There is no single approach to personality definition or measurement recommended by all personality scholars. However, many scholars rely on the Five Factor Model of Personality (FFM) as a broad, inclusive, and empirically supported model of traits. The FFM reflects the lexical tradition in personality research, which suggests that the fundamental dimensions of personality are encoded in the natural language terms people use to describe themselves and others. Lexical researchers argue that most personality- related variation between individuals can be captured by five broad dimensions, each of which is composed of several more specific facets. High scorers on neuroticism {i.e., low emotional stability) tend to be impulsive, self-conscious, and prone to negative emotions such as depression, anger, and anxiety. Extroverts tend to experience more positive emotions and to be outgoing, assertive, and energetic. Agreeable people are more trusting, helpful, modest, and kind. People with higher levels of openness to experience tend to be more imaginative, humorous, and interested in arts, culture, and unconventional ideas. Finally, conscientious people are hard working, organized, responsible, self-disciplined, and dutiful.

[0054] Embodiments of the present invention use a composite trait approach to develop the Personality POWeR Inventory. Composite trait models examine clusters of traits that share some conceptual and empirical similarities, but that, in contrast with the Five Factor Model, are not intended to be all-inclusive frameworks. We also drew from research on self-evaluations, motivational traits, and stress tolerance. Self-evaluations refer to individual differences in peoples' general appraisals of themselves and the world around them; examples include self-confidence, self-esteem, and the perceived ability to control events in one's life. Motivational traits are patterns of underlying needs that guide behavior in specific life roles. Examples include the need for achievement, and the relative priority of learning and performance goals. Stress tolerance refers to general tendencies people have to interpret events as challenges presenting opportunities for personal growth or as stressors to be avoided. Research on hardiness describes the importance of having a sense of purpose or meaning in one's life, a tendency to see demanding events as challenges rather than as threats, and the belief that one can act to create positive outcomes in life.

[0055] Twelve personality facets were selected that are organized into sub elements that comprise the major dimensions of the personality model: Purpose, Openness, Willpower, and Resourcefulness (POWeR). Figure 2 shows how the Twelve sub elements are organized,

[0056] Purpose is defined by commitment, challenge-seeking, and control. The general idea of the importance of a sense of purpose as an aspect of personality comes from literature on hardiness as well as similar concepts such as core self-evaluations, Hardiness is typically viewed as a cognitive personality trait reflecting general beliefs people have about their lives as well as the way they tend to interpret potentially stressful events. Hardiness is conceptualized as having three components: commitment, control, and challenge. Thus, people who score higher on the purpose dimension tend to be able to find meaning in the events in their lives (commitment), seek out challenging experiences that will help them grow as people (challenge seeking), and believe they can control events in their lives (control). Consistent with some past hardiness literature, students who score higher on this dimension would be expected to be more resilient to the stressors of college and be expected to be more engaged in their academic work,

[0057] Openness reflects intellectual curiosity, creativity, and a genuine interest in new experiences. People who score higher on openness enjoy new experiences, are flexible and adaptable in new situations, A great deal of organizational and educational research on the broader FFM concept of openness to experience supports its importance in training performance and success in school. Thus, we expect students who score higher on this dimension to enjoy learning new information and having the new experiences that help them thrive in higher education.

[0058] Willpower concerns a student's general sense of self-discipline and self- control. Two aspects of will-power - hard-working and prudent - resemble elements of the FFM dimension of conscientiousness. These facets indicate the extent to which students are driven to success, resist giving up easily, avoid making careless mistakes and generally display good levels of impulse control. Conscientiousness is a particularly important attribute to capture in this context because a great deal of research in a wide variety of circumstances shows that people with higher levels of conscientiousness tend to be more successful in major life activities and roles, including job performance, occupational attainment, mortality, marital stability, health maintenance behavior, and academic performance. The third will-power facet stable resembles aspects of the FFM dimension of neuroticism/emotional related to emotional stability. Neuroticism is another critically important personality trait across a wide variety of outcomes. Students with higher scores on this facet should be less reactive to stressful circumstances, and generally exhibit higher levels of self-control. Students with high levels of will-power should work hard, even under difficult circumstances, to have good study habits, and to be generally able to tolerate the demands of higher education.

[0059] Resourcefulness addresses another general theme in personality literature.

People differ in the extent to which they respond effectively to events in their lives as well as their patterns of positive beliefs about themselves and their future. We call this general concept resourcefulness, as these beliefs and behavioral styles serve as important psychological resources in many situations. We focused on three facets of resourcefulness: proactivity, self-confidence, and hopefulness. Each of these captures personality content shown to be important in previous research, has clear theoretical links to student outcomes, and is conceptually different from the other POWeR dimensions. People with strong proactive personalities tend to confront problems in their lives rather than avoiding them and tend to see problems as opportunities rather than as obstacles. People with self- confidence generally believe they will be successful at challenges they face and that they can effectively handle problems in their lives. Finally, people who are hopeful, have an optimistic self-view and feel confident and positive about their future. Given these qualities, students who are more resourceful should have better academic/retention outcomes because they are more likely to take on challenging work, deal with issues at school before they become problems, and believe they can handle the demands of their school role.

Institutional Fit

[0060] Hundreds of studies in vocational and organizational psychology demonstrate that individuals whose personal characteristics fit a particular organizational/vocational environment perform better, report higher levels of satisfaction, and have stronger desires to remain members of the organizations, It is assumed that a similar process guides students' decisions to attend, and to remain a member of, an institution. That is, students will have better academic outcomes (grades, retention, etc.) when they have a better fit with that institution.

[0061] Defining the concept of fit involves several considerations. One challenge is to define the set of attributes of the person and environment under consideration. Possible attributes of people include skills, interests, personality traits, values, and goals. Possible attributes of organizations include the demands of one's role, organizational values, the climate of the organization, the characteristics of people who are satisfied in a particular role, and so on. The organization also can include a variety of different fit targets, including the general organization, the demands of a particular role, or particular groups of people within the organization. Each of these personal and organizational qualities could, in theory, be matched to any of the others, so researchers must make careful choices.

[0062] Another challenge in fit research concerns how each person and organization attribute will be measured, Some researchers simply ask people to indicate the extent to which they perceive themselves to have a good fit with a particular environment. Another approach involves assessing the characteristics of the person and the environment separately and then calculating a quantitative measure of fit reflecting the degree to which the characteristics are similar. As we will show below, a variation of this approach is used.

[0063] institutional match is defined as the degree to which characteristics of the higher education institution match students' preferences and needs. A great deal of research has investigated student retention issues; much of this research has described institutional characteristics related to retention. This research demonstrates that higher education institutions can affect student retention outcomes. Most retention research focuses on characteristics thought to promote retention for all students (such as support for students or advising quality). However, students may differ in their preferences for particular kinds of institutions - an issue that has received relatively less attention in the literature.

[0064] Two features of these characteristics are the extent to which the characteristic is present at the university and the importance of the characteristic to the student, For example, school size is a potentially important aspect of institutional match, Yet school size may be important to some students, but not others. Moreover, some students may strongly desire to attend a large school, others may desire to attend a small school. Therefore, fit models need to consider both the size of the focal school and the importance of the characteristic to the student in question to determine the overall match of the student to the school, Thus, our approach to conceptualizing institutional fit involved (a) generating a large list of institutional characteristics, (b) assessing how important those characteristics were to the students, and (c) assessing whether the school possessed the characteristic. The details of this approach are described in the sections below.

[006S] Figure 3 is a diagram of another example of a method for processing the data collected by the scoring and analysis engine, The input data represented by the personality data and the institutional fit data is processed to indicate the school stressors, adaptability to the institution, and the institutional commitment resulting in a determination of academic performance and the likelihood of the retention of that student This is further described below referred to as "Conceptual Model".

Conceptual Model

[0066] It is expected that institutional fit and student personality to influence academic outcomes through their influences on student engagement (broadly defined). Three engagement-related pathways are a focus; (1) experiences of stress in the academic role ("school stressors"), (2) adjustment to the academic role ("adaptation to school"), and (3) institutional commitment School stressors are defined as students' perceptions of the demands they face from their student role. Examples include conflicting demands from instructors, uncertainty about how to fulfill one's responsibilities as a student, and feeling stretched to the limit by school demands. Student adjustment reflects to the extent to which students successfully transition into the college student role. Four dimensions of adjustment were studied, including social adjustment (e.g., establishing close social ties at school), emotional adjustment [e.g., maintaining emotional well-being), academic adjustment (e.g., being successful/satisfied with academic work), and institutional adjustment {e.g., a strong desire to stay at the school), Finally, institutional commitment refers to a student's emotional ties to and identification with their school),

[0067] Figure 3 shows how these pathways link the institutional fit and personality data measures to student performance and retention. As shown in the model, students with better matches to their institution and higher scores on the personality data matching generally report lower role stress, better adjustment to their student role, and stronger commitment to their institution. Students reporting higher scores on these engagement- related factors are less likely to intend to leave their school, less likely to actually be searching for another school, and more likely to report higher academic performance.

[0068] Figure 4 illustrates a diagram of a system for student retention according to an embodiment. In block 400, a central processing unit resides in a secured facility with redundant hardware, power, communications facilities, and 24 x 7 maintenance, Within the central process is a Crypto Processor 410 that provides the secured operating environment that prevents third party intrusion. Other components of the central process include memory or RAM 430 and ROM 440, and clock 420 as may be required by the central processor to operate efficiently and fast enough to respond to the demands of the operating environment and transaction load. Connectivity of the hardware to the network is achieved though an ethernet communications facility 450 though a communication port device. Connection to the Internet 460 is provided by the hosting company and the communications provider. In block 470, the user community can connect to the Internet cloud 460 via a computer, cellular phone or a number of compatible devices. Connectivity to the network is controlled by the central processor 400 and the crypto processor 410, Institutional users may be the academic advising faculty, admissions faculty, student affairs, housing and administration, Student users include accepted applicants, current students, campus organizations and clubs, Student access is limited to the student connections and reporting application,

[0069] Figure 5 is a flowchart detailing the software architecture of the risk management solution. The software architecture is based upon the development of a specialized scoring and analysis database engine that processes the data provided by the surveys and information on the accepted applicants provided by each institution. The scoring and analysis engine contains specialized machine learning algorithms, survey algorithms and roommate matching algorithms to process the data,

[0070] In block 500, applicants or students that are accepted by the client institution are requested to complete a brief survey, institutions are encouraged to provide data 510 collected from their application process to aid in the development of the present system. In block 520, the survey and institutional data provides input, for personality, institutional fit, social, academic and roommate match processing. The POWeR Model (previously discussed with Figure 2) 550 provides the behavioral analysis process developed by the survey questionnaire while additional survey algorithms 530 (personality, institutional fit, social, academic and roommate match processing) are utilized to process other deliverables to the system. Processing takes place in the scoring and analysis engine 540. Outputs from the scoring and analysis engine 540 provide data displayed on the dashboard screens and reports for administrative reporting and student, connections and reporting.

[0071] Figure 6 is a block schematic diagram of the risk management process flow according to an embodiment. This identifies the solution from customer acquisition to deployment Once implemented, embodiments of the present invention works in conjunction with the various departments of an institution (e.g., Admissions, Student Affairs, Student Services, Academic Affairs, Provost's office, etc. ) to develop the surveys, identifies the required student application data and loads the scoring & analysis engine. Then the process of data collection form the student begins.

[0072] The method of Figure 6 engages with the institutions and sets up the program once all contracts are accepted by both entities. In block 610, new clients 600 agree to provide data on the campus activities, such as data on academic resources, social activities and clubs, athletic resources, and sports functions. In block 620, appropriate groups at the institution develop the personality data, institutional fit data, student social and academic data, and roommate match surveys. The input from the meetings is used to create an institution specific survey tool, in block 640, data is collected for currently- enrolled students. For example, a video announcement may be created for use with the incoming students and the currently enrolled students to collect the necessar data for each individual, The video announcement may be distributed and the results are tracked (video opens, views, uncompleted survey, completed survey) as the databases are being built, 650 At the agreed upon timeframe the student connections and reporting is launched by the institution for use by the students. The dashboard tools 660 are available to the administration and access as defined by the institution is made available to the administration and faculty, Training videos 670 with instruction on use of the system are prepared and delivered to the institution's faculty users,

[0073] Figure 7 is a block schematic diagram of the risk management operations according to some embodiments, This identifies the actionable items that represent the implementation of the risk management solution. The challenge is to obtain information on as many existing students and accepted applicant, as possible, to insure the data collected is accurate from the individual prospective as well as the representation of the group is accurate. Also, all questions must be the most appropriate with the correct scale, and asked in the proper manner to eliminate confusion and assure accuracy. A scale for anti-gaming may also be present to identity people trying to select the "right answer".

[0074] In blocks 700 and 710, data is received from the institution with the names of the individuals accepted by the institution. This file is submitted two weeks after the beginning of early acceptance and is received every two weeks thereafter until class registration. This action insures that records of all potential registering students for the targeted semester are active and included in the system. All other steps illustrated in Figure 7 are implemented immediately and directly in response to the student being accepted or admitted to the institution, in block 720, contact information for the accepted students is used to send an email video campaign to introduce the applicant to the student connections & reporting system, triggering the initial data collection process. In block 730, all phases of the data collection process are tracked and reviewed. In block 735, data collected from the accepted applicant and entered into the system is simultaneously processed by the scoring & analysis engine. In block 740, during the survey response phase all activities are available to the institution and are displayed on their dashboard. In block 750, upon completion of the survey, the student connections & reporting system is activated for both the student and the institution. In block 760, roommate matching is part of this process and can take place at this point or initiated separately by the institution. The roommate match process is described below with regard to Figures 8-9. In block 770, the institution has collected additional data from its application process that can be input at this point, It is recommended that the institution only input data on those applicants accepted. This process of adding additional data will be scheduled with the institution to facilitate a smooth integration. In block 775, the fully populated dashboard will be available to the institution after processing of the application data. In block 780, dashboards for all departments are generated automatically by the system. Reports are available on-line in graphical formats or can be printed by the user. In block 780, as discussed above in block 735, data is needed from the institution on an agreed upon timeframe to update the retention/attrition report and begin analysis on the available data to determine data that can be correlated as relevant in the retention process. It is the ability to identif common data points that will allow the institution to develop a plan that can reduce attrition and improve retention. In block 790, as the recruiting cycle commences for a new semester or new year, the process begins again. With the previous year(s) data available as a guide to identify at. application or upon acceptance any student who is likely to be a retention risk, institutions can act in a proactive manner to improve the likelihood that that individual will be retained.

[0075] Figure 8 is a block schematic diagram of the process that identifies students desiring a roommate match and the collection of the initial data for the match process, according to an embodiment. In block 800, during the application process the request for a roommate match is presented. In 805, 810, and 815, if the applicant opts not to use the system he is placed into a database for these applicants and summary reports are provided to the appropriate departments. A dashboard report is available for this database. In block 820, if the applicant requests a roommate match then a questionnaire is completed. If the matching information is not completed then, in block 825, a database is compiled of those not completing the request and, in block 840, a report of this information is compiled and made available to the appropriate department as well as a query capability of the database. A database 850 with a list of the responses for the roommate matching and the previous data collected on the applicant is made available for the roommate matching process.

[0076] Figure 9 is a block schematic diagram of a process that describes the actual matching process of the students to determine their roommate for the coming year if they select to be matched by the institution. In block 900, the roommate matching process uses the data 905 collected from the accepted applicant and applies the IP for matching roommates to create the optimal match. In block 915, these matches are forwarded to the applicants that are matched with instructions 920 on how to connect with their new roommate along with important questions that should be asked during the introduction, The roommates are required to decide 925 on whether they will accept the match and they are recorded in the database as an accepted match if accepted. In block 940, reports are issued to the appropriate departments within the institution upon acceptance of the roommate match. A query system is available to the responsible department to access current status of roommates, produce reports or to review specific questions on the information. If the roommates reject the match, the process continues to block 930 and they are then resubmitted for a second roommate match process. In the case the match is resubmitted a letter of explanation accompanies the notification of the students involved explain the process and noting that this does happen and no one is at fault or should be offended and then starts 915 the introduction process again. Only two matches are allowed for the system. [0077] Figure 10A and 10B are graphical depictions of the modeling techniques used to evaluate the data collected in the personality, institutional fit, social, academic and roommate match data. Additional methodologies are included in the scoring & analysis engine, It should be noted that every attempt possible is made to create grouping or clusters.

The _.Dashboard_. Design

[0078] The purpose of the dashboard is to provide the administration with quick and easy access to the data utilized by the system. The aggregation and disaggregation of data requires a thoughtful interface to be useful to the administration, with ease of navigability and the ability to find the desired content quickly. This design focuses on input data and the reports generated as output and reflected in the dashboard.

[0079] The following sections outline each of the major pages of the dashboard and begin with a mocked screenshot of the page. The screenshot illustrated in Figure 11 through 19 follow.

[0080] In many places on the dashboard there is an arrow (►) indicating the ability to drill down on that option. For instance, on the homepage the first section in the top left corner (Survey Respondent Statistics}, the data points "Completed", "In Progress" and "Not Started" each have this arrow. Clicking on the arrow for "Completed" would then cause the list of all respondents who have completed the survey to appear. The user would then have the option to click on any individual student's name in the list, which would take them to the individual student's profile.

[0081] Many sections provide the capability to choose from multiple data sets, viewable by clicking on a drop-down menu below the section header. These options vary, but are often between "Accepted Students", "Enrolled Students" and "Applicants" to compare data amongst these groups. The specifics on each of these will be provided in the respective section in the document,

[0082] Every section provides the opportunity to view lists of students based on the given parameters, and enables the user to click on individual students and go to their individual profile.

[0083] At the bottom of most sections is a "send to 'My Reports' " button, enabling the user to save of-interest content to their My Reports section, where they can store and print reports.

[0084] Printing reports allows the user to operate from the "My Reports" section.

Printing may require re-entry of the required password. Clicking print will prompt a password entry, where the user can then easily enter their password and print the desired content.

[0085] Figure 11 is an exemplary graphical user interface of the administrative reporting "system home page" highlighting the details available in the summarized data format. The top right of the screen indicates the report or interface provides the user information and statistics about the students that have been accepted by the institution. For example, the survey respondent statistics box indicates the status of those emails sent out to accepted students, indicating: (1) how many have been sent, (2) how many are in progress and (3) how many have been started but not completed. Data on each of these categories can be obtained by clicking on the arrow to the left of each category. The student connections and reporting usage box indicates the usage of the site overall Specific data for the categories of: (1) average number of connections, (2) number of connections made per visit (3) average time on the site, (4) and average connections for clubs, organizations and resources. Additional details on each of these categories are available by clicking on the arrow to the left of the specific category. The demographic statistics box provides data on the other categories selected by the institution for collection and measurement. These categories are selected by the institution during the original installation, are input from application applications data or other available sources and are aggregated on this page, Drilling down capability into the individual databases is available to the user by clicking on the arrow to the right of the specific category. The requested support box provides information to the institution on the various categories that are available for the student to select in the survey process. The top categories are either identified by the highest level of interest or those that are selected by the institution during installation to display on this page. Access to the database of the individuals in this category is available by clicking on the arrow to the right of the category.

[0086] Figure 12 is an exemplary graphical user interface of the administrative reporting system highlighting a summary of data on individual transfer students. This data can be aggregated. Data on this group allows the administration to understand the fit, social and academic requirements for each of the individual transfers.

[0087] Figure 13 is an exemplary graphical user interface of the administrative reporting system highlighting the retention summary data. This page provides a high level view of data involving all non-retained students, When students that are not retained leave the institution, data is collected and any relationship is displayed by the aggregate data collected on these individuals. This may include, but not be limited to, such factors as shown in the example: (1) out-of-state students, (2) scoring low on the willpower scale, (3) low social fit score, (4) low high school grade point average, and (5) 1^st generation college students, as illustrated in the figure. The figure illustrates each of the factors as the top characteristic of the non-retained students. Additional correlated topics are available by clicking on the "click for more" button. Retention rates by the intervals show also appear on this page (beginning of term, first six weeks, end of semester, end of year and more as shown).

[0088] Figure 14 is an exemplary graphical user interface of the administrative reporting system highlighting the overall personality and fit scores for all students. This data is presented in an analytical format with scores for both personality and institutional fit data being shown for the entire entering class. These numbers can be further studied in greater detail by clicking on the arrow to the left of the element or sub-element Also, by clicking on the "?" to the right of each category the definition of that element will be displayed providing ease of use and understanding of the data in that particular trait. Bar charts and graphs also display the aggregate data for ease of use. The navigation panel on the left of the page allows the user to move from one section to another within the Risk management solution.

[0089] Figure 15 is an exemplary graphical user interface of the administrative reporting system highlighting the overall social interests of the incoming accepted applicants as well as a second summary of the current enrolled class. This page provides information on the interest level in the clubs and organizations available on campus, This also provides interests of entering and current students to identify to the administration an interest level in those interests not current available on campus. This capability might be used to better focus resources of the institution on the areas that have the highest interest levels. Also included in the dashboard are the Cultural services, academic and professional interests of the students.

[0090] Figure 16 is an exemplary graphical user interface of the administrative reporting system highlighting the advanced search capability of the risk management system, This allow the collection of data from the incoming applicants and the ability to correlate that data to identify correlated data for students who stay at the institution, those that leave at varying intervals (first 6 weeks, last drop add date, mid semester, end of first semester , end of first year, and others).

[0091] Figure 17 is an exemplary graphical user interface of the administrative reporting system highlighting admissions information for the incoming potential students. Specifically this outlines the actions taken by accepted applicants once they have been sent the video request for the completion of the survey questionnaire.

[0092] Figure 18 is an exemplary graphical user interface of the administrative reporting system highlighting the reporting capability of the system. Once reports have been selected or special reports requested, the authorized user may request to either save or print the report.

[0093] Figure 19 is an exemplary graphical user interface of the administrative reporting system highlighting the roommate function and how it works. In the figure, the students are shown with their matched roommates with a Facebook connection for each pair. The incoming student that has been matched has a chance to review the individual they are matched with, call or communicate with that person and then if desired request another match if they feel this is a poor selection. Each school has the opportunity to limit the number of additional matches to a set limit [0094] Figure 20 is an exemplary graphical user interface of the individual student data available in the admissions and reporting system, This provides the individual data for use by a faculty advisor or any authorized administrative function or individual at the institution, Items in this report may be (1) personality inventory and institutional fit inventory. Users have the ability to select (in middle of the figure) additional information on the (goals, interests, and connections), (2) interactions of the student with the various sites available in the system, (3) create notes on that individual that can be shared or private for that student/advisor.

[0095] Figure 21 is an exemplary graphical user interface of the dashboard including additional features according to some embodiments. The dashboard has two additional features for use by the institution for achieving the user institution's goals of improving applicant yield, improving first year retention, increasing the graduation rate and assisting in achieving employment. In Figure 22, two items are used to increase usage of the student connections. The "challenges" section of the dashboard is a focused effort to attract the student to return to the site often to participate in contests and games with interesting and exciting prizes. By having new contests introduced on daily and weekly basis it insures that the students become active using the site. This in addition to the student matches, clubs and organizations, campus resources, student-campus-community life postings makes this an extremely useful tool for the student.

[0096] The second feature illustrated in Figure 22 is a jobs function added to the system using an interface. This is a button created on the site (located in the bottom right hand portion of the interface) that offers an opportunity to participate in a job matching solution/activity. Corporations can post jobs on the site. To do so, the listing company must have current employees in this job complete a personality and job traits survey. This provides an accurate benchmark for who will match the traits of the most successful employee. The students will complete a similar survey and will be matched with the jobs they are best suited for. Students will be allowed to apply for any job, but may be directed towards the one they best fit. The usage of this is determined by each institution. All results are provided to the employer along with the students application and resume.

[0097] As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a "circuit," "module" or "system." Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer readable medium(s) having computer readable program code embodied thereon.

[0098] Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device,

[0099] A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[00100] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing. Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C# or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[00101] Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

[00102] These computer program instructions may also be stored in a computer readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks. [00103] The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

[00104] As used herein, a class may define an abstract characteristic of a thing or object, such as a group of code or instructions for performing a particular operation or function. The abstract characteristics may include characteristics of the thing or object, for example attributes, fields or properties, behaviors, such as functions or methods that can be performed by the class, An object is a particular instance of a class. The set of values of the attributes of a particular object is the state of the object. The object includes the state and the behavior that is defined in the object's class. A method is an object's abilities or functions the object can perform.

[00105] The flowcharts and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention, in this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

[00106] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of embodiments of the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

[00107] The corresponding structures, materials, acts, and equivalents of all means or step plus function elements in the claims below are intended to include any structure, material, or act for performing the function in combination with other claimed elements as specifically claimed. The description of the present invention has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to embodiments of the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of embodiments of the invention. The embodiment was chosen and described in order to best explain the principles of embodiments of the invention and the practical application, and to enable others of ordinary skill in the art to understand embodiments of the invention for various embodiments with various modifications as are suited to the particular use contemplated.

[00108] Although specific embodiments have been illustrated and described herein, those of ordinary skili in the art appreciate that any arrangement which is calculated to achieve the same purpose may be substituted for the specific embodiments shown and that embodiments of the invention have other applications in other environments, This application is intended to cover any adaptations or variations of the present invention. The following claims are in no way intended to limit the scope of embodiments of the invention to the specific embodiments described herein.

Claims

CLAIMS What is claimed is:

1. A method for student retention and improvement, the method comprising:

collecting, using a computing device, data about a student after admitting a student to an educational institution;

providing the data to a scoring and analysis engine;

monitoring the student's performance during enrollment at the educational institution and storing performance data based on the monitoring;

providing a graphical user interface to monitor and report information about the student's performance, the graphical user interface using the performance data; and

providing a social connection between the student and other students and resources of the education institution,

2. The method of claim 1, further comprising implementing an academic plan using the data to keep the student enrolled in the educational institution.

3. The method of claim 1, further comprising matching common interests of the student with a second student using the data for roommate matching purposes.

4. A system, comprising:

a database;

a processor communicable with the database, the processor configured for: collecting, using a computing device, data about a student after admitting a student to an educational institution;

providing the data to a scoring and analysis engine;

monitoring the student's performance during enrollment at the educational institution and storing performance data based on the monitoring;

providing a graphical user interface to monitor and report information about the student's performance, the graphical user interface using the performance data; and

providing a social connection between the student and other students and resources of the education institution.

5. A non- ransitory computer readable medium having computer program product embodied therein such that when the computer program product is executed on a computer, the computer program product is configured to perform a method, the method comprising:

collecting, using a computing device, data about a student after admitting a student to an educational institution;

providing the data to a scoring and analysis engine;

monitoring the student's performance during enrollment at the educational institution and storing performance data based on the monitoring;

providing a graphical user interface to monitor and report information about the student's performance, the graphical user interface using the performance data; and providing a social connection between the student and other students and resources ducation institution.