Online Courses Search - Public College Program IPEDS

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Note: Information provided in this article is obtained from the project 'DataMaster -IPEDS'. Detail of the project can be found in Youtube, and EdPond articles.

Using Panels provided in this tool/article, readers can locate online courses( program) offered by the public colleges of the United States. The project is hosted at the Tableau Public. For online programs offered by the private colleges of the United States, please see this article.

Through the years, based on US Education Department's IPEDS (Integrated Postsecondary Education System) survey, the per-cent of students involved in distance classes have increased in almost all sectors of 2-year and 4-year colleges. The recent trend from year 2012 to 2016 can be visualized in my previous article:
"IPEDS College Data - Online/Distance Education Enrollment Trend".

Even though not directly related, public institutions in the United States also provide opportunities for students to obtain degrees through distance education 'completely'. Based on IPEDS definition, a 'Distance Education Program' is a program for which all the required coursework for program completion is able to be completed via distance education courses, in which the instructional content is delivered exclusively via distance education. IPEDS' definition for 'Distance Education Course' do reserve the possibilities that students maybe asked to physically participate in some activities like testing, orientation, or academic support services. This can mean that, in reality, some of the degrees listed in this articles may not be completely feasible remotely.

Anyway, it is the intention of this article to provide a list of disciplines and colleges that were reported to IPEDS as 'Distance Education Program'. Students are cautioned to check the details with institutions before committed to work toward the degrees.

Given all the above, let's now look at the overall picture of the 'Distance Education Program' offered by United States' public institutions.

Based on the IPEDS data, there are total 13,380 distance education programs offered by United States' public institutions, 4-year or 2-year. Of these programs, 7,264 are in the Associate or Certificate level. At the Bachelor-degree level, there are 2,105 programs. At higher degree levels, there are 945, 2,820, 241, and 5 programs respectively for post-bachelor, master, post-master, and doctor degree.

Information about these distance education programs can be examined via the following interactive panels.

Panel 1 - State Category

In panel 1, by selecting the state of interest and the degree level, user can exam the number of (distance education) programs offered in each discipline branch, depicted by the two-digit CIP (Classification of Instructional Program) code. By selecting all levels and all states, it can be observed that most programs are offered at the category of CIP 52, the Business, followed by CIP 51, the Health, and CIP 13, the Education branch. Summing over all states, at the Associate and Certificate level, the CIP 11, the Computer, ranked 3rd instead of CIP 13, the Education. At the bachelor level, CIP 24, the Libral Art, comes before CIP 13, and ranked as the 3rd. At the post bachelor and master level, CIP 13 is way ahead of Business (CIP 52) and Health (CIP 51), where they are of similar magnitude and traded each other with levels. For the doctor level, there are only 3 CIPs: 51, 13, and 44 (social services).

The state summary in Panel 1 is good if you are interested in in-state degrees. However, an online program being an online program is the freedom to enrolled from anywhere. In this case, searching from the program of interested maybe the way to go. Panel 2 shows exactly that.

Panel 2 - Find States

In Panel 2, reader can select the degree level:
    Assoicate and Certificates (DeCrtAssct)
    Bachelor (DeBchlr)
    Post Bachelor Certificates (DePstBchlr)
    Master (DeMstr)
    Post Master Certificates (DePstMstr)
    Doctor (DeDctr)
, the two-digit cip category, and, then, the cip program title. This allows reader to see from which states the selected programs are available. With this information, reader can continue to find out which college/institution offering the particular program.

Panel 3 - State Detail

With this above panel, reader can find specific programs offered at the 6-digit CIP level - example are the Accounting training in the Business field (CIP 52).

Panel 4 - Find college

With Panel 4, reader can narrow their selection to the desired programs and the colleges that offered the programs.

Panel 5 - Overview Table

Panel 5 allows readers to compare program offered by each state. By selecting the desired states, readers can view program offerings side by side. For policy makers and higher education leaders, these data can be important in making decisions on what program to provide for the benefits of the society.

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College Data Search, an IPEDS tool - Monitoring Peer Institutions

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IPEDS (Integrated Postsecondary Education Data System) data, without doubt, can be considered as the most important data source for United States' postsecondary education. However, even though IPEDS made efforts to make the data accessible to general public, barriers for using and analyzing those data are still high.

As described in my previous articles(IPEDS College Data - Distance Education Enrollment Trend, Higher Education IPEDS College Data UI and RESTful API - defnition, charting, demonstration) and youtube videos(IPEDS College Data UI and API project), at this moment, I am personally developing a data system that will make accessing to IPEDS data easier.

My most recent video that demonstrated the recent improved to my app/program can be found at the Youtube.com: College Data Search - IPEDS tool for Peer Institutions Monitoring

The video demonstrated how to use the app/program to monitor the status of a list of institutions over time. In our particular case, we use the peer institutions list of the Indiana University at Bloomington. The list can be obtained directly from Indiana University's web site: http://uirr.iu.edu/index.html

As is demonstrated by the video, Indiana University at Bloomington has the highest number of undergraduate degree-seeking enrollment headcount comparing to all its peers. On the other hand, the percent of students that took on-line classes ranked Indiana University the third from the last among its peers (year 2016).

One institution also stand out from the video. As shown in the video, the University of Texas at Arlington started out as an plausible peer of the Indiana University at Bloomington even though it did have the highest number of online students. Over the years, however, it is obvious that the University of Texas at Arlington has taken an initiative that grown its online community way faster than the rest of the institutions, including Indiana University at Bloomington.

The video also try to make few points on the peer institution selection. As pointed out, the most important thing in selecting peer institutions is look at the restrictions or constrains. In the case of the out-of-state online enrollment, one possible restriction would be the mission of the institution. For example, if the Indiana University at Bloomington was limited by either the public opinion or the legislature to focus its resources on in-state students while the University of Texas at Arlington is not. The two institutions, then, should not be considered peers even if they have the similar resources to operate.

With the improvement done to the app/program, an upcoming video will demonstrate a way to select institutions based on profiles - a process that helps selecting possible peer institutions. That same process can also be used by high school graduates looking for similar institutions that meet their college expectations.

Please visit my video and feel free to comment on it. For one, any indication of interest in the program will drive me to put more time into the project.

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Online Education Statistics (IPEDS Enrollment Trend)

If you are looking for online program offered by United States' public colleges, please use this online search tool/application to find colleges offering them.

With higher education continuing to be considered the footstep to reaching personal economic sufficiency, the demand for postsecondary education continues to grow. With the growing demands, governments, states, private companies, and institutions were working hard to capitalize and meet the demands. Distance education, with its nature, overcome several traditional higher education limitations.

Basic statistics of the distance education in United States were published in the 'Digest of Education Statistics' by National Center for Education Statistics (NCES). The most recent summary table published can be found here.

The table presents national level data with sector break down using the preliminary 2016 IPEDS (Integrated Postsecondary Education Data System) data published back in Feb. 2018. The table shows two years (2015 and 2016) of data, which are of limited use in showing the trends.

The purpose of this article is to fill the gaps and present some trend data using the 'data master' data system developed by the author. Information about the data system can be found at the ITTidbit, the Youtube, and the Vimeo.

For this article, I will be dealing with the National level data only as opposed to State level data, which will be dealt with in separate articles. The data presented here would be an enhancement to the basic statistics published by NCES in terms of the years of coverage, the break down of categories, and the revision of the data. The data used are revisions published by IPEDS as of Oct. 24, 2018.

The general observations of the data are:

1. For degree-seeking students (include graduate students), which is the majority of undergraduates, the fraction of students taking online classes continue to grow.
2. For 4-year schools, public and private not-for-profit schools, the number of students taking online classes are continue to grow.
3. For 4-year degree seeking, private for-profit schools show high degree use of distance education - 65-80% vs. 15-30% for public and private not-for profit schools.

DC+50States of US; 4-year Inst.; Undergraduate Total; Any Online Course;

  Head Count : (4-year; Under)

The chart above presents the enrollment headcount for undergraduate students that taking any online course in 4-year institutions located in the DC or the 50 states of United States. The blue line represents the public 4-year institutions while the orange line represents the private not-for-profit 4-year institutions. The green line represents the private for profit 4-year institutions.

  Percent of Undergraduate Enrollment : (4-year; Under)

Head count is important, but it does not tell the whole story. Percent of total enrollment provides a different level of details. As shown in this above chart, the private for-profit institution (green line) actually utilized the distance education to higher degree while the public 4-year institution (blue line) comes next even though it has more students as shown in previous chart.

DC+50States of US; 4-year Inst.; Undergraduate Degree Seeking; Any Online Course;

  Head Count : (4-year; Under; Degree Seeking)

The chart above presents the enrollment headcount for undergraduate degree seeking students that taking any online course in 4-year institutions located in the DC or the 50 states of United States. The blue line represents the public 4-year institutions while the orange line represents the private not-for-profit 4-year institutions. The green line represents the private for profit 4-year institutions.

  Percent of Undergraduate Degree Seeking Student : (4-year)

DC+50States of US; 4-year Inst.; Undergraduate non-Degree Seeking; Any Online Course;

  Head Count : (4-year; Under; non-degree seeking)

  Percent of Undergraduate non-Degree Seeking students: (4-year)

DC+50States of US; 4-year Inst.; Graduate; Any Online Course;

  Head Count : (4-year; Graduate students)

The chart above presents the enrollment headcount for graduate students that taking any online course in 4-year institutions located in the DC or the 50 states of United States. The blue line represents the public 4-year institutions while the orange line represents the private not-for-profit 4-year institutions. The green line represents the private for profit 4-year institutions.

  Percent of Graduate enrollment : (4-year)

DC+50States of US; 2-year Inst.; enroll total; Any Online Course;

  Head Count : (2-year; enroll total)

The chart above presents the enrollment headcount for undergraduate students that taking any online course in 2-year institutions located in the DC or the 50 states of United States. The blue line represents the public 2-year institutions while the orange line represents the private not-for-profit 2-year institutions. The green line represents the private for profit 2-year institutions. One thing stand out in this chart is that the public 2-year institutions have much more students than that of private 2-year institutions.

   Percent of enrollment total : (2-year)

DC+50States of US; 2-year Inst.; degree seeking; Any Online Course;

  Head Count : (2-year; degree seeking)

Again, comparing with previous chart, it shows that majority undergraduate students are degree seeking students. For data concerning non-degree seeking students, please see the following section.

   Percent of degree seeking students : (2-year)

   
DC+50States of US; 2-year Inst.; non-degree seeking; Any Online Course;

  Head Count : (2-year; non-degree seeking)

   Percent of non-degree seeking students : (2-year)

 
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Data published by NCES Digest of Education Statistics:

• Compare with private, public institution show less (%) distance students. Also less (%) exclusive distance students.
• Compare with graduate, undergraduate show less (%) exclusive students but more none-exclusive students.
• For profits shows much more exclusive students (4-year) - I assuming 2-year of smaller scale and not enthusiasm about distance ed.
• 2 year, in general, more exclusive.
• public has more in-state than out-of-state; private, the reverse is true. 

Data in general show the growing trend on distance/on-line education.
For public institution, because of the mission of educate state residents, public institution, in general, enrolls state residence and, therefore, less students from out of state and less students taking distance education courses from out of state.

It, however, can be a strategy move for public institution to accept out of state students if the capacity is allowed and to recover the cost of development.

It is also interested to see if it is possible to relate fields distribution to the number of students taking online courses since, likely, some fields are more suitable for online presentation.

From policy point of view, it may not be easy to make arguments with simple head count distribution since there are many factors in deciding what is an appropriate % of online courses.

Distance education, by definition, allow students to take courses away from the campus and, in that way, reduces spaces requirement. On the other hand, the requirement for staff's time may not reduced - staff will be transferred to work on tutorial duties. In a sense, you increase the quality in liue of reduce cost.

Serve the public - student body - the whole state.
How privates contributes.

Institution size - related to distance ed. - Serve each other institution.


 here

Distance picked, peer institution selected, the nearest IPEDS

Other Peer Institution Selection Article

** If you are using Microsoft Internet Explorer or Google Chrom browser, you would not be able to read the formulas in this article. These formulas were written in MathML, a W3C standard, and can be viewed in FireFox.

Summary
The goal of this article is to provide mathematical insights into the selection of nearest peer institutions. The discussion begins with a general review of distance in mathematics and extended the idea to the measurement of nearness. Examples were used to demonstrate the importance of properly selected distance function.

The idea of peer
In many fields of study, it is a useful practice to tag objects that are similar to a particular object, the Anchor, as peers. The similarity can customarily be measured by the shortness of distance. The smaller the distance, the more similar an object is to the Anchor and the more likely an object to be selected as a peer of the Anchor.

Distances in Mathematics
In mathematics a metric or distance function is a function that defines the distance between two elements/objects (see Wikipedia article). However, as the abstract nature of the mathematics, the 'set theory' set criteria on behavior of the distance function but left the explicit definition of the distance to the case of application since the explicit definition is irrelevant in the content of the set theory.

For cases were the elements are Euclidean geometry points, the distances are commonly defined as:  $\sqrt{{(x_1-x_2)}^2+{(y_1-y_2)}^2}$

However, this is not the only permissible definition for distance.


Distance in a case of study
The lack of explicit definition of distance for a case of study call into question of the distance between the mathematics and the real world.

However, contrary to most believes, mathematics is not isolated in its own abstract world, plenty of mathematical branches grow out of real world problems. For example, the criteria for the distance function are abstracted qualities of the common distance definition of the Euclidean geometry.

The absent of the definition, in essence, offer the opportunity to select a sensible definition for the case of study.

In the land of peer selection, properties are constantly associated with objects and distances are customary defined through properties.

In the case of higher-education-institution objects, possible properties are fall enrollment headcounts, percent of male enrollment, total revenue, ... etc, like those collected by IPEDS ( Integrated Postsecondary Education Data System) survey.

Distance of Interest for this article
Of all the possible choice of distance definitions, the following are of demonstrative interest. The subscript i denoted various properties while the X denoted the Anchor object in the set and x a different object. The D denote the distance

1. Sum of the square of the difference
   $D=\sum _i{d}_i=\sum _i{(x_i-X_i)}^2$
2. Sum of the Ranking of difference
   $D=\sum _i{d}_i=\sum _i$ Ranking of $|x_i-X_i|$
   where the minimum value has a rank of 1 and the next smallest has a rank of 2 ... etc.
3. Sum of the square of the percent difference
   $D=\sum _i{d}_i=\sum _i{(\frac{x_i}{X_i}-1)}^2$
4. Sum of the absolute value of the percent difference
   $D=\sum _i{d}_i=\sum _i|\frac{x_i}{X_i}-1|$

Fabricated demonstrative data
For the sack of demonstration, higher education institution IPEDS like objects were considered. The Anchor institution, My Inst, alone with three other institutions and their fabricated property values were listed in Table 1. Comparisons of these institution were presented in Figure 1. Data are fabricated to demonstrate that a good methodology would not depend on data to produce reasonable result. With Figure 1, it is clearly shown that Inst-1 is the institution that most similar to My Inst, the Anchor institution, followed by Inst-2 and Inst-3.

Table 1 - demonstrative data

Inst	Enrollment	% Men	Revenue
Institution 1	1900	63%	105,000
Institution 2	2050	90%	101,000
Institution 3	1970	35%	104,000
My Institution	2000	60%	100,000

Figure 1 - comparing institutions (click to see the picture)

Distance evaluated with each illustrative definition

Table 2 - Sum of the square of the difference

Inst	Enrollment	Percent Men	Revenue	Distance
Inst 1	10000	0.0009	25,000,000	25,010,000.0
Inst 2	2500	0.09	1,000,000	1,002,500.1
Inst 3	900	0.0625	16,000,000	16,000,900.1

With the 'sum of the square of the difference' approach, the similarity ranking is in the order of Inst-2, Inst-3, and followed by Inst 1. Table 2 demonstrated that, in this model, the property having larger value would overshadow differences in other properties. It is, therefore, important to scale properties to a compatible matter.t


Table 3 - Sum of the Ranking of difference

Inst	Enrollment	Percent Men	Revenue	Distance
Inst 1	3	1	3	7
Inst 2	2	3	1	6
Inst 3	1	2	2	5

The 'Sum of the Ranking' practice considered the Inst-3 as the most similar peer with Inst-2 and Inst-1 following. The problem with this approach may not be obvious. Couple of points can be made, if observe carefully. First of all is the misrepresentation of the true differences with category like integers, which by itself can't even avoid rounding errors. Using ordering also create problem in that distances between adjacent values are been replaced by 1.

Table 4 - Sum of the square of the percent difference

Inst	Enrollment	% Men	Revenue	Distance
Inst 1	0.3%	0.3%	0.3%	0.8%
Inst 2	0.1%	25.0%	0.0%	25.1%
Inst 3	0.0%	17.4%	0.2%	17.5%

Inst-1 is ranked as the most likely followed by Inst-3 and Inst-2 in the 'Sum of the square of the percent difference' process. 

Under this approach, differences are represented by the percent difference from the Anchor with no categorization attempted. Another benefit of this approach is the straightforward approach and the ease of explanation to audiences. Weighting to each property, as will be discussed later, is also plain to see and easy to identify.

Lesson learned
Properties' value varied in magnitudes, invoking values directly undermined the difference in properties with smaller magnitude. The employ of ranking could over-shadow the difference in value and, in effect, assigned a difference of 1 for all adjacent values.

The square vs. the absolute value (definition 3 vs. definition 4) 
The fact that ${\left(\sum _i{A}_i\right)}^2\succ \sum _i{A_i}^2$ implied that the squared method would favor multiple smaller differences than a single larger difference while the absolute value method will weight small differences and single bigger difference equally. Visually, the squared method made sense.

Weighting properties
Once standardize to the 'sum of the square of the percent difference', weighting can easily be done by multiples to the 'square of the percent difference' before the sum.

* While customized distance can be used in Nearest Neighbor analysis, Nearest Neighbor represent a specific topic in the cluster analysis.