Abstract:
A computing system and computer-implemented method may be used by prospective students and their influencers to choose an academic offering, such as a college major. The computing system enables its user to query an academic institution&#39;s database using exact match terms or intelligent-associated keywords. In response to the query, the computing system may identify an academic offering that most closely matches the search query. In addition, or in the alternative, the computing system may further identify alternative academic offerings. The system and method may further be utilized by academic institutions to tailor academic offerings to prospective students. The collected data may be shared among multiple participating academic institutions, and in some embodiments reports of user data relevant to each academic institution are generated for that institution&#39;s consideration and use.

Description:
CROSS REFERENCE TO RELATED APPLICATION 
       [0001]    The present application claims the benefit of the provisional patent application having the Ser. No. 61/670,718 (filed on Jul. 12, 2012), the disclosure of which is hereby incorporated by reference in its entirety. 
     
    
     TECHNICAL FIELD 
       [0002]    The present disclosure relates to a computing system and computer-implemented method that may be used by prospective students to choose an academic offering, such as a college major. The system and method may further be utilized by academic institutions to tailor academic offerings to prospective students or attract .students to offerings related to nonacademic subjects in which the prospective student has interest. 
       BACKGROUND 
       [0003]    Whereas many needs are universal (food, shelter, etc.) much of what we need to flourish is individualized. Choice is what enables each person to pursue those objects and activities that best satisfy one&#39;s own preferences within the limits of one&#39;s resources. Yet modern life presents us with ever-increasing choices, such as what car to buy, where to take a vacation, or importantly, what college to attend. As the number of choices increases, making an exhaustive investigation of the possibilities becomes more difficult, particularly if dispositive information is not readily available to the individual faced with making a decision. 
         [0004]    For example, recent research suggests that the availability of academic offerings ranks among the top three criteria in the minds of prospective students who are faced with the decision of which college to attend. Yet despite this data, most colleges and universities continue to provide academic offering information using course catalogs. Utilizing this format may be problematic in that it may not make the data needed for making an informed decision readily accessible to the prospective student. Inaccessibility may arise for a number of reasons. 
         [0005]    First, higher education has a jargon-ridden vernacular that may not be familiar to the layperson. For example, a prospective student may not understand many of the terms utilized in a college course catalog such as “bachelor of science,” “bachelor of arts,” “minor of study,” “externship,” “microbiology,” or “bovine sciences.” 
         [0006]    Second, most colleges and universities do not associate careers with searchable academic interests in their course catalogs. Therefore, the link between a desired career and the academic offerings that are listed in a course catalog may not be clear to the prospective student. For example, students who would like to be medical doctors typically look for “pre med” or “biology” as academic offerings that will enable them to pursue a career in medicine. Thus students like these may overlook other viable academic avenues that will enable them to pursue their chosen careers. For example students wishing to be medical doctors may overlook “engineering” and “psychology” as possible majors of study. 
         [0007]    Third, colleges and universities have been slow to adapt their course catalogs from their traditional, printed form. Thus the prospective student is left with the often difficult task of searching materials such as PDFs and rudimentary online databases for exact matches of academic offerings; often this results in the prospective student missing alternative academic offerings that may also be of interest to the student. 
         [0008]    Given these and other considerations, it is clear that many prospective students may not have access to the data that they need to make the best choice of an academic offering, such as a major of study. Consequently, there is clearly a need for a tool that will facilitate this choice. Moreover, there is a need for a tool that operates effectively in spite of a prospective student&#39;s lack of familiarity with the vernacular utilized by academic institutions. Additionally, there is a need for a tool that allows a student to easily explore available options based upon his or her general interests without having to know exactly which academic offerings are relevant to those interests. Further, there is a need for a tool that will allow a student to explore a variety of academic offerings that will lead to his or her career of choice. It would be advantageous if such a tool would allow an academic institution offering the courses of study to gather information about prospective students and their use of the tool so that the tool and the data presented in it may be tailored to facilitate the choices to be made by future students. Moreover, it would be advantageous if such a tool would allow an academic institution to provide academic offerings that more closely match those desired by prospective students. 
       SUMMARY 
       [0009]    The present disclosure addresses the aforementioned needs by providing a new computing system and computer-implemented method for facilitating a user&#39;s choice from a plurality of academic offerings offered by an academic institution. The user may be a prospective student, a current student and/or a student&#39;s influencers. Non-limiting examples of influencers include the student&#39;s parents, guardians, friends, teachers, high school counselors and college advisors. 
         [0010]    In some embodiments, a computing system that facilitates a user&#39;s choice of an academic offering from a plurality of academic offerings. The computing system comprises a processor and a memory encoded with programming instructions. The programming instructions are executable to perform a search query, entered by a user, of a database. The database comprises a plurality of academic offerings and intelligent-associated keywords. Each of the intelligent-associated keywords is related to at least one of the plurality of academic offerings, and that relation is stored in the database. In response to the user-entered query, the programming instructions are further executable to process the data in the database and to identify at least a first academic offering from the plurality of academic offerings that most closely matches the user&#39;s search query. The programming instructions are further executable to communicate the first academic offering to the user. 
         [0011]    In some embodiments, a computing system conveys information to a user regarding an academic offering among a plurality of academic offerings that are proffered by a first academic institution and at least a second academic institution. The computing system comprises a processor and a memory encoded with programming instructions. The programming instructions are executable to perform a user-entered query of a database that contains a plurality of academic offerings offered by the academic institutions and intelligent-associated keywords. Each of the intelligent-associated keywords is related to at least one of the plurality of academic offerings. In response to the user-entered query, the programming instructions are further executable to process data in the database and to identify at least a first academic offering from the plurality academic offerings that most closely matches the user search query. The programming instructions are further executable to communicate the first academic offering to the user. In these embodiments, the first academic institution has a first front end associated with a first unique identifier, and the at least a second academic institution has a second front end associated with a second unique identifier. The user may access the database and perform his or her search through either the first or the second front end. 
         [0012]    In some embodiments, the disclosure is directed to a computer-implemented method of facilitating a user&#39;s choice from a plurality of academic offerings that are proffered by a first academic institution and at least a second academic institution. The method comprises the following steps. At least a first academic offering that most closely matches a user-queried search of a database is identified. The database comprises the plurality of academic offerings and intelligent-associated keywords from a data set other than academic offerings, and at least some of the intelligent-associated keywords are related to at least one of the plurality of the first academic institution&#39;s academic offerings. Each of the intelligent-associated keywords is related to at least one of the academic offerings. At least the first academic offering is communicated to the user. In many of these embodiments, the first academic institution has a first front end associated with a first unique identifier, and the at least a second academic institution has a second front end associated with a second unique identifier. The user may access the database and perform his or her search through either the first or the second front end. 
         [0013]    For the purpose of clarity, certain terms used in the description above should be understood as having particular meanings. Thus, the phrase “based on” is used as an indication that something is determined at least in part by the thing that it is identified as being “based on.” When something is completely determined by a thing, it will be described as being “based exclusively on” the thing. Further, a “set” should be understood to mean a number, group, or combination of one or more things of similar nature, design, or function, while an “element” should be understood to refer to a discrete and identifiable thing. Thus, an example of an element from a set of missing information could be a departure time, if the user was expected to provide a departure time, but such time had not yet been provided. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0014]    It is believed that the inventors&#39; technology will be better understood from the following description of certain examples taken in conjunction with the accompanying drawings, in which like reference numerals identify the same elements and in which: 
           [0015]      FIG. 1  is a block diagram showing one embodiment of a computing system according to the disclosure. 
           [0016]      FIG. 2  is a block diagram showing another embodiment of a computing system according to the disclosure. 
       
    
    
       [0017]    The drawings are not intended to be limiting in any way, and it is contemplated that various aspects of the disclosed technology may be implemented in a variety of other ways, including ways not necessarily depicted in the drawings. The accompanying drawings, incorporated in and forming a part of the specification, illustrate several aspects of the inventors&#39; technology, and together with the description serve to explain the principles of that technology; it being understood however, that the protection accorded by this document or any related document should not be limited to the precise arrangements shown. 
       DETAILED DESCRIPTION 
       [0018]    The following description of certain examples demonstrates how aspects of the technology disclosed herein could be implemented. Such examples should be understood as being illustrative, and should not be used to limit the protection accorded by this document, or by any related document. Other examples, features, aspects, embodiments and advantages of the inventors&#39; technology will become apparent to those skilled in the art from the following description, which is by way of illustration, one of the best modes contemplated for using the technology disclosed herein. As will be realized, the inventors&#39; technology is capable of different and obvious aspects, all without departing from the material disclosed herein as it would be understood by one of ordinary skill in the art. Accordingly, the descriptions herein should be regarded as illustrative in nature and not restrictive. 
         [0019]    The elements or features of the various embodiments are described in detail hereinafter. Any reference to a singular characteristic or limitation of the present disclosure shall include the corresponding plural characteristics or limitations, and vice versa, unless otherwise specified or clearly implied to the contrary by the context in which the reference is made. 
         [0020]    The system and methods described herein may comprise, consist of, or consist essentially of the elements and features of the disclosure described herein, as well as any additional or optional components, or features described herein, that are otherwise useful in the systems and methods. 
         [0021]    All documents (patents, patent applications and other publications) cited in this application are incorporated herein by reference in their entirety to the extent that they are not inconsistent with the disclosure set forth herein. 
         [0022]    As used herein, “academic institution” means a high school, college, university, trade school, or any other institution which proffers academic offerings. 
         [0023]    As used herein, an “academic offering” is a course of study. Non-limiting examples of academic offerings include: a certificate program, a major of study, a minor of study, an emphasis of study, a certificate; or the like. 
         [0024]    As used herein, “alternative academic offering” means an academic offering that is similar or related to another academic offering. For example, alternative academic options to the college major of “biology” might include the majors “microbiology” or “zoology.” 
         [0025]    As used herein, “intelligent-associated keyword” is used interchangeably with “tag” to describe words that are relevant to an academic offering including, but not limited to, a college major. For example, if the college major is “biology,” intelligent-associated keywords may include: “microbiology,” “cells,” and “animals.” In some embodiments, the intelligent-associated keywords include terms and phrases from popular culture. For example, if the college major is “advertising,” the intelligent-associated keywords may include reference to television shows such as “Mad Men®.” In some embodiments, the intelligent-associated keywords include careers that require a certain college major. For example, to have a career as a lab technician, the required college major may be “biology,” or “chemistry.” 
         [0026]    As used herein, “electronic messaging” includes electronic communication, for example, via email or posting to websites (including but not limited to social media such as Twitter® or Facebook®). 
         [0027]    The present disclosure relates to a computing system and a computer-implemented method for facilitating a user&#39;s choice of an academic offering. These and other features of the disclosure are discussed below. 
       Computing System 
       [0028]    Computing systems for facilitating a user&#39;s choice of an academic offering from a plurality of academic offerings may comprise a processor and a memory encoded with programming instructions which are executable to perform a number of functions. In some embodiments or implementations of the computing system, the programming instructions are described as a series of steps. However, those skilled in the art will appreciate that alternative embodiments and implementations are within the scope of this teaching. 
         [0029]      FIG. 1  is a block diagram showing one embodiment of a computing system  100  according to the disclosure. Referencing  FIG. 1 , a number of participants are each connected to a virtual private server  200 , which may be in the form of a web server or other server as would be understood by one of ordinary skill in the art. The participants include a user  120 , an academic institution  130  and a third-party administrator  140 . Each of the participants has data connections, either permanent or intermittent, to at least the virtual private server  200 . In some embodiments, the third-party administrator  140  hosts and/or maintains the virtual private server  200 . 
         [0030]    The virtual private server  200  stores data in a database  210 . A non-limiting example of a useful database is a “MySQL” database. The database  210  comprises a first data set  230  and at least a second data set  240 . In some embodiments, the database may further comprise a third data set, a fourth data set, a fifth data set, and so on up to and including as many data sets as are desired. In the embodiment shown in  FIG. 1 , a first data set  230  contains a listing of the academic offerings that are offered by the academic institution  130 . A second data set  240  contains a listing of intelligent-associated keywords, each of which relates to at least one of the academic offerings contained within the first data set  230 . 
         [0031]    The administrative interface of virtual private server  200  also comprises an administration interface  250 . The academic institution  130  may use the administration interface  250  to edit the data in the database  210 . For example, the academic institution  130  may add or remove academic offerings from the first data set  230 . In a further example, the academic institution  130  may update the intelligent-associated keywords in the second data set  240  to reflect changes in popular culture (e.g., new slang, new television programs and the like) or add a new data set (not shown) to show the same. In a yet further example, the software running on virtual private server  200  is programmed to enable academic institution  130  to add additional data sets. 
         [0032]    The user  120  can communicate with the virtual private server  200  through a computing resource (e.g., a computer, a smartphone, a tablet). The user  120  performs a search query of the database  210 . Non-limiting examples of search queries include entering an exact match term for an academic offering, and entering an intelligent-associated keyword from the second (or a subsequent) data set. 
         [0033]    The computing system  100  is programmed to respond to the user search query by processing the data in the first data set  230  and the second data set  240  to identify at least a first academic offering that most closely matches the user search query. In some embodiments, more than one academic offering that closely matches the user query may be identified. In some embodiments, at least one alternative academic offering in addition to, or in lieu of, the first academic offering is identified. 
         [0034]    Once at least a first academic offering is identified, the computing system  100  comprises programming instructions which are executable by the system&#39;s processor to communicate the academic offering to the user  120 . In some embodiments, the computing system  100  is further programmed with a facility enabling user  120  to share the results of his or her query with others via electronic messaging. Non-limiting examples of electronic messaging include messaging via email, Twitter®, Facebook®, and the like. 
         [0035]    The computing system  100  may additionally comprise programming instructions that are further executable by the computer system&#39;s processor to collect data about the user  120  and/or his or her use of system  100  (collectively, “user data”) and store it for access via the administrative interface  250  of the virtual private server  200 . Any user data that is of use to the academic institution  130  may be collected. In some embodiments, the user data may be selected from the group of: frequency of the user&#39;s searching returning a particular academic offering; frequency of the user&#39;s search using an intelligent-associated keyword; number of queries made by the user during a search session; amount of time spent by the user making queries during a search session; and number of requests made to share an academic offering via electronic messaging. 
         [0036]    The computing system  100  may additionally comprise programming instructions that are further executable by the processor to analyze user data collected in relation to a plurality of users; identify trends in and/or compile aggregate information characterizing the user data collected from the plurality of users; and to report the trends to the academic institution  130 . In some embodiments, the processor may automatically execute these steps, and in some embodiments, the steps may be initiated by the third-party administrator  140 . In the latter embodiments, the third-party administrator  140  may have access to the computing system of one or more additional academic institutions. In these embodiments, the third-party administrator  130  may be able to synthesize the trends across two or more academic institutions and provide analysis of the synthesized trends to one or more of the academic institutions. In some embodiments, such analysis is automatically performed by software on the virtual private server. The analysis may provide the academic institution(s) with valuable information as to how the users search for academic offerings, their changing interests, goals that resonate with them, and the like, both as to individual users and the users in the aggregate. 
         [0037]    The academic institution  130  may modify the database by adding or deleting a data set or by modifying an existing data set. In some embodiments, the modification may be made by the academic institution in response to the reported user trends in order to facilitate future user search queries. In some embodiments, the modification may include the addition of new academic offerings. 
         [0038]    In some embodiments the computing system  100  may allow the user  120  to perform a query in an alternative way from the one previously described. Instead of entering the exact match term for an academic offering or an intelligent-associated keyword, the user may perform a query by choosing (for example by clicking with a mouse) an academic offering from a list of academic offerings. In these embodiments, when the academic offering is chosen, an abstract of the academic offering may appear in a window. The window may further contain photos associated with the academic offering and/or similar academic offerings that may be of interest to the user. 
         [0039]    In some of these embodiments, the display of the chosen academic offering includes related topics from academia as well as other informational domains. These may be derived from second data set  240  (and/or additional data sets in database  210 ) of from another source. In some such displays, these related concepts are presented as clickable links to other academic offerings related to the same concept. Some systems are programmed to keep track of the various search queries and selections made by a particular user, then to prioritize and/or filter search results based on relevance to previous queries, mutual relatedness with previous search terms, relationship to other academic offerings that have been viewed, user data, and the like as will occur to those skilled in the art. 
         [0040]      FIG. 2  illustrates various participants in another embodiment of the computing system  100 . Unlike the embodiment shown in  FIG. 1 , the participants in  FIG. 2  include more than one academic institution: a first academic institution  130  and a second academic institution  135 . In this embodiment, the first academic institution  130  has a branded front end  305  that is coded with a unique identifier, and the second academic institution  135  has a branded front end  310  that is coded with its own unique identifier. Various technologies will occur to those skilled in the art for this coding, including, but not limited to hidden or non-hidden fields transmitted with search queries, browser or Flash® cookies, any of a number of scripting techniques, or the like. In some embodiments, front end  305  is custom-designed responsively to the preferences of first academic institution  130 , while in others front end  305  shares a design with second academic institution  135 . 
         [0041]    In this embodiment, the user  120  accesses the virtual private server  200  through either the branded front end  305  of the first academic institution  130  or the branded front end  310  of the second academic institution  135 . The database  210  stores data in a first data set  230  and at least a second data set  240  for both the first academic institution  130  and the second academic institution  135 . The first data set  230  contains a listing of the academic offerings that are provided by the first academic institution  130  and/or the second academic institution  135 . The second data set contains a listing of intelligent-associated keywords, each of which is related to at least one of the academic offerings contained within the first data set  230 . 
         [0042]    Additionally, the server  200  contains an administrative interface  250  for the first academic institution  130  and an administrative interface  255  for the second academic institution  135 . Each academic institution may use its respective administrative interface to edit the data pertaining to that institution in the database  210 . In alternative embodiments, separate tables in database  210  store the information for each respective academic institution and are joined with tables containing the intelligent-associated keyword data sets to produce results for that given academic institution (e.g., responses to queries from that institution&#39;s customized front end). 
         [0043]    As in the embodiment described with reference to  FIG. 1 , the user  120  can communicate with the virtual private server  200  through a computing resource (e.g., a computer, a smartphone, a tablet). Unlike the embodiment illustrated in  FIG. 1 , however, the user might access the virtual private server  200  through either the branded front end  305  of the first academic institution or the branded front end  310  of the second academic institution  135 . In some such embodiments, each respective front end is integrated with the organizational website of that particular academic institution. 
         [0044]    The user  120  may perform a search of the database  210  as described in connection with the embodiment illustrated in  FIG. 1 . In response to the user search query, the computing system  100  is programmed to process the data in the first data set  230  and the second data set  240  to identify at least a first academic offering that most closely matches the user search query. In some embodiments, more than one academic offering matching the user query may be identified. In some embodiments, at least one alternative academic offering may be identified in addition to, or in lieu of, the first academic offering. 
         [0045]    Once at least a first academic offering is identified, the computing system  100  comprises programming instructions which are further executable by the system&#39;s processor to communicate the academic offering to the user  120 . The computing system  100  may be further programmed so that the user may share the results of his or her query with other people via electronic messaging. Non-limiting examples of electronic messaging include via email, Twitter®, Facebook® and the like. In addition, or in the alternative, the computing system  100  may be further programmed so that the user may contact the academic institution offering the first academic offering, and/or visit valuable links, such as the academic institution&#39;s Facebook® page. 
         [0046]    The computing system  100  may additionally comprise programming instructions which are further executable by the computer system&#39;s processor to collect data about the user  120  and/or his or her use of computing system  100  (collectively “user data”) and present it in the administrative interface  250  for the first academic institution  130  and the administrative interface  255  for the second academic institution  135 . Any user data that is of use to the academic institutions may be collected. In the present embodiment, the user data may be selected from the group of: which academic institution&#39;s front end was the conduit for a particular search; frequency of the user&#39;s searching returning a particular academic offering; frequency of the user&#39;s search using an intelligent-associated keyword; number of queries made by the user during a search session; amount of time spent by the user making queries during a search session; and number of requests made to share an academic offering via electronic messaging. 
         [0047]    The computing system  100  may additionally comprise programming instructions that are further executable by the processor to: analyze user data collected in relation to a plurality of users; identify trends in the user data collected from the plurality of users; and to report the trends to the first academic institution  130  and/or the second academic institution  135 . In some embodiments, the processor may automatically execute these steps, and in some embodiments, the steps may be initiated by the third-party administrator  140 . 
         [0048]    Based upon the trends, the first academic institution  130  and/or the second academic institution  135  may wish to modify their course offerings or the characterizations of their course offerings in the database  210 . Toward this end, the programming instructions are further executable by the processor so that either academic institution may modify the database  210  by adding or deleting a data set or by modifying an existing data set to more closely match academic offerings with past or future user search queries. In some embodiments, the modification may include the addition of new academic offerings. The programming instructions are further executable by the processor so that the modifications made by each academic institution may be stored in the database  210 . The programming instructions may be further executable to collate the modifications, to analyze the modifications and/or to report the modifications to each academic institution and/or to a third-party administrator  140  of the virtual private server  200 . 
         [0049]    In some embodiments of the computing system described herein, the computing resources that are applied generally take the form of a mobile, laptop, desktop, or server-type computer. The computer, as this example will generically be referred to, includes a processor in communication with a memory, output interface, input interface, and network interface. Power, ground, clock, and other signals and circuitry are used as appropriate as will be understood and easily implemented by those skilled in the art. 
         [0050]    The network interface connects the computer to a data network for communication of data between the computer and other devices attached to the network. Input interface(s) manage communication between the processor and one or more touch screens, sensors, push-buttons, UARTs, IR and/or RF receivers or transceivers, decoders, or other devices, as well as traditional keyboard and mouse devices. Output interface(s) provide a video signal to a display, and may provide signals to one or more additional output devices such as LEDs, LCDs, or audio output devices, local multimedia devices, local notification devices, or a combination of these and other output devices and techniques as will occur to those skilled in the art. 
         [0051]    The processor in some embodiments is a microcontroller or general purpose microprocessor that reads its program from the memory. The processor may be comprised of one or more components configured as a single unit. Alternatively, when of a multi-component form, the processor may have one or more components located remotely relative to the others. One or more components of the processor may be of the electronic variety including digital circuitry, analog circuitry, or both. In some embodiments, the processor is of a conventional, integrated circuit microprocessor arrangement, such as one or more CORE i3, i5, or i7 processors from INTEL Corporation of 2200 Mission College Boulevard, Santa Clara, Calif. 95052, USA, or OPTERON or PHENOM processors from Advanced Micro Devices, One AMD Place, Sunnyvale, Calif. 94088, USA. In alternative embodiments, one or more reduced instruction set computer (RISC) processors, application-specific integrated circuits (ASICs), general-purpose microprocessors, programmable logic arrays, or other devices may be used alone or in combination as will occur to those skilled in the art. 
         [0052]    Likewise, the memory in various embodiments includes one or more types such as solid-state electronic memory, magnetic memory, or optical memory, just to name a few. By way of non-limiting example, the memory can include solid-state electronic Random Access Memory (RAM), Sequentially Accessible Memory (SAM) (such as the First-In, First-Out (FIFO) variety or the Last-In First-Out (LIFO) variety), Programmable Read-Only Memory (PROM), Electrically Programmable Read-Only Memory (EPROM), or Electrically Erasable Programmable Read-Only Memory (EEPROM); an optical disc memory (such as a recordable, rewritable, or read-only DVD or CD-ROM); a magnetically encoded hard drive, floppy disk, tape, or cartridge medium; or a plurality and/or combination of these memory types. Also, the memory in various embodiments is volatile, nonvolatile, or a hybrid combination of volatile and nonvolatile varieties. 
         [0053]    Computer programs implementing the methods described herein will commonly be distributed either on a physical distribution medium such as CD-ROM, or via a network distribution medium such as an internet protocol or token ring network, using other media, or through some combination of such distribution media. From there, they will often be copied to a hard disk, non-volatile memory, or a similar intermediate storage medium. When the programs are to be run, they are loaded either from their distribution medium or their intermediate storage medium into the execution memory of the computer, configuring the computer to act in accordance with the method described herein. All of these operations are well known to those skilled in the art of computer systems. 
         [0054]    The term “computer-readable medium” encompasses distribution media, intermediate storage media, execution memory of a computer, and any other medium or device capable of storing for later reading by a computer a computer program implementing a method. 
       Programming 
       [0055]    The computing systems according to an embodiment of the present disclosure comprise a processor and a memory encoded with programming instructions which are executable by the processor to perform a number of functions as described herein. An exemplary work sequence for building the computing systems comprises the following steps, which may be executed in any order that is of use to one skilled in the art. 
         [0056]    In one step, the course catalog of an academic institution is obtained and converted into an XML document. The XML document also characterizes a collection of associations between data from different categories, or “data sets.” The collections of associations have contents directed to one or more of the following. 
         [0057]    A first category comprises interest tags. Exemplary interest tags may include popular topics which relate to individual academic offerings. For example, “bugs” may be an entry for the major “entomology” or the title of the television show “Crime Scene Investigation®” may be an entry for the major “criminal justice.” Zero, one or multiple interest tags may be associated with each individual major of study. 
         [0058]    An additional set of associations may relate to career tags. Exemplary career tags in a data set include popular interests and phrases that relate to individual majors of study. For example, “stock trader” may be a career tag for the major “business,” and “social worker” may be a career tag for the major “sociology.” Zero, one or multiple career tags may be associated with each individual major of study. 
         [0059]    Additional data sets and associations may individually have contents selected from the group of: a Uniform Resource Locator (URL); a particular department within the academic institution (e.g., each relevant college within a university); the department in which each major of study is housed; the name of each major of study available within the academic institution; the degrees offered by the academic institution (e.g., a Bachelor of Science, a Bachelor of Arts, a certificate, etc.); a description of each major of study offered by the academic institution, for example, as set forth in the catalog; off-campus study locations associated or available with a particular major of study; a photo folder; a “you may also like” column containing majors of study that are related to the major queried (for example, for the major “Advertising,” “Mass Media” will appear in this column); “naughty words” (i.e., a list of words that will return a response that suggests the term is not valid); an identification (ID) code associated with the academic institution so that its data can be differentiated from that of other universities; and combinations thereof. 
         [0060]    In another step in this exemplary method, a MySQL database is constructed using the contents of a series of associations of data in different categories, i.e., data sets, selected from those described above. 
         [0061]    In another step, the MySQL database is installed and hosted on a virtual private server. 
         [0062]    In another step, the branded administration interface for the academic institution is built. The academic institution may use the administration interface to edit the portion of the data in the database that relates to it. 
         [0063]    In another step in this exemplary method, a branded front end for the academic institution is built with a mixture of HTML, CSS, and jQuery. Other languages and/or libraries will be used in other implementations as will occur to those skilled in the art. 
         [0064]    In another step, the server side of the system is implemented in PHP to retrieve and display appropriate queried results. Again, other languages and/or libraries will be used in other implementations as will occur to those skilled in the art. 
         [0065]    In another step, a JavaScript “on click event” is created for each link on the front end of the database to feed data to a web analytics engine, such as Google Analytics. 
       Example 
       [0066]    Student R is a junior in high school and has begun her college search. She is interested in F College but is only considering colleges that offer programs that will allow her to achieve her dream of being a patent attorney. R thinks that college F needs to offer “pre-law” in order for her to consider applying for admission to the college. 
         [0067]    R visits the F College academic offering site. When she arrives at the site, she sees a full list of College F&#39;s academic offerings and a search field. 
         [0068]    R first types “pre-law” into the search bar. As she is typing, the list begins to highlight majors that match what she is typing. After she is done typing, the list of majors only includes those related to pre-law. In certain alternative embodiments, the full list is still displayed, but majors related to her input are visually highlighted in the display. In some embodiments, the list is filtered (or selectively highlighted) as R types, while in others, the filtering (or highlighting) is performed only after R indicates that input is complete, such as by pressing an “Enter” key or clicking a “Search” button in the interface. 
         [0069]    R then clicks on “pre-law” in the list of majors. The site returns an abstract of the pre-law program at College F, as well as a list of related majors that includes “Political Science,” but also “Biotechnology.” What R does not know is that there are several ways to pursue a career in patent law. College F, recognizing that an educational background in the sciences can provide for a career in patent law, relates the biotechnology major to the “career” of “attorney” and “lawyer.” 
         [0070]    R resets her search and enters the television program title “Law and Order” as her query. Using its database of intelligent-associated keywords the system returns “pre-law,” “political science,” “forensics” and “film” as related majors. 
         [0071]    R resets her search and queries “patent.” The query returns “pre-law,” “English,” “biology,” “physics,” “chemistry,” “engineering,” and “biotechnology.” R then clicks on biotechnology, and the abstract for the major appears. She is intrigued, so she clicks on the “email” icon and emails the results to her mother. She then wants her friends to know about the site, so she sends a Tweet® to all of her followers and posts it on her Facebook® wall. Finally, she prints a copy of the query results for herself. 
       Variations 
       [0072]    In addition to the various embodiments described above, variations of the disclosed systems include a variety of automated matching techniques for user queries and automatic construction of the data sets described herein. In some systems, for example, websites of a particular type or character are crawled, and relevant keywords are collected. The associations between such key words and academic offerings are manually or automatically produced based on the relationship between the concepts (or between categories or concepts to which each of them relates). In some alternatives, matching is only done literally, while in others text expansion and varying word forms are accounted for. In the matching algorithms either has the data sets or databases are constructed and/or when the query is being processed. Other techniques for indexing and searching the data sets and databases will occur to those skilled in the art in view of this disclosure. 
         [0073]    While the computing system has been illustrated and described in detail in the drawings and foregoing description, the same is to be considered as illustrative and not restrictive in character, it being understood that only the preferred embodiments have been shown and described and that all changes and modifications that come within the spirit of the disclosure are desired to be protected.