College Search, a tool and tutorial on using IPEDS college data

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IPEDS (Integrated Postsecondary Education Data System) data is a vital data source for learning about colleges in the United States. As indicated in my previous articles, a good tool/program/application is very important in making a data usable.


In my previous article, I talked about how to use a program to monitoring the performance of peer institutions. In this article, I will go through the details of using the application to access IPEDS data and search for desired colleges/institutions. The process has many implications. For one, it can be used by high school graduates to search for college of interest. The same process can also be used by institution researchers in looking for potential peer institutions.

Information on the tool/program/application I used can be found at: IPEDS College Data UI and API project. The one interested for this article is: College Search - IPEDS data for High School Graduates + Researcher.


Before we begin, we need understand that when using any dataset, it is always important to have some basic knowledge about the industry/subject. For IPEDS, or, college/higher-education in the United States, these can include how institutions are classified and how these classification can change. For this article, what we need to understand is that institution can change - control, ownership included, and when searching them, it is important to look for them at a specific point in time, say, year. What you learn about an institution in one year, may or may not be hold for other years.

Back to the topic, the program we are going to look at has many uses. For this article, we will concentrate on just one tab/function - the institution tab. Under the institution tab, there are five sub-tabs that each provides well defined purposes to guide user to accomplish their goals.


The first sub-tab is the 'basic' sub-tab. The most important function for this tab is to establish the year of interest. User begin by searching the database for all years that are available and, then, select the year of interest. Once the year is selected, this tab also provide simple filter to limited the scope of search. Available options are detailed to assist user to make decisions.

After the basic categorical filter been applied, quantitative filtering can be applied by moving to the measures sub-tab. In this sub-tab, users can iteratively search and select the measures/quantities that are interested to them.

Once the measures of interest were selected, the Variable sub-tab is ready. In this tab,user get a chance to further qualify the measure/quantity they selected. For example, user maybe looking a the quantity of part-time enrolled male students while the qualifying 'factor' can be students levels, like undergraduate, or graduate students. By selecting applicable qualifying options and assign a name, a 'user-measure' is created ... like part-time-under-men, part-time-men-under-plus-graduate, ... etc.

With fully defined 'user-measures', user can now set the 'quantitative filters'. By moving to the Query sub-tab and typing in things like: part-time-under-men>1000 or
part-time-under-men/part-time-men-under-plus-graduate > 0.5, user can select institutions that met those criteria.

After the execution of the Query sub-tab, institutions found are appended to UnitId sub-tab. From there, you can retrieve the basic identity information of each selected institutions.

Once institutions were decided, user can use other major tabs to retrieve trend data about these institution and present these data in charts. For example: College Data Search - IPEDS tool for Peer Institutions Monitoring, the video and College Data Search, a tool - Monitoring Peer Institutions, the article.

As mentioned in the video, the process is very general. It can easily apply to any measures in the IPEDS database. The process also support the combination of measures and criteria. For example, user can even check if an institution's student minority ratio is higher than faculty's minority ratio.

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How to interpret and select Peer Institution Criteria - An Essay

Other Peer Institution Selection Article

Since we are interested in ranking the performance of the school management, our pick of peer institutions should have similar resources and constrains so that the differences in performance can be attributed to the management of the school.

Peer institution comparison is a common practice for gauging higher institution progresses.

However, the practice of selecting peer institution and how comparison should be examined are not well understood.

This article is trying to shad some light on these two topics.

For selecting peer institutions, the general idea is pick institutions with similar values on some variables/measures. Once these peer institutions are selected, other measures are commonly used to gauge institutions progresses. A logic question that raised from this process is whether a variable should be treated as the picking variable or the comparison variable? If we are interested in gauging progresses caused by an institution's management/administration team, the answer to the question can then be answered logically.

Since we are interested in ranking the performance of the school management, our pick of peer institutions should have similar resources and constrains so that the differences in performance can be attributed to the management of the school. The resources and constrains should referred to things that isn't normally changeable by the will of the school.

To demonstrate the point, let's compare the number of graduates and enrollment a year of an institution. In this comparison, the enrollment could be a better variable than the number of graduates to be used as the picking variable since the enrollment to a large degree are constrained by the size or resource of the school while the number of graduates can be influenced by the deployment of better student support system by the management team. On the other hand, the resources provided by government to public institutions can be a better picking variable than the enrollment since with given resources, institutions can still achieving different level of enrollment success by management team's recruiting efforts.

The topic on how comparison should be examined can also be demonstrated with examples. For example, library expenditure can be used to rank peer institutions. The assumption is that the higher the spending, the better is the school. However, we can argue that in the name of servicing the students and faculties, the library spending is not the meaningful measure since the thing that really matter to students and faculties is the amount of content that is available to students and faculties. An institutions could have lower the library spending by subscribing to online libraries. While the spending is less, the content available to students and faculties are increased.

The other common case is that of the faculty salary. Institutions constantly use the peer institutions to solicit State's support in increasing faculty's salaries. Even though these are legitimate use of peer institutions, there are usually untold stories. Suppose two peer institutions are similar in all measures, the increase of the faculty salaries will inevitably increase the cost of of a degree in that institution. What is mean is that in order to convincingly present its case, institution have to also show their competitiveness in their management too. Likely than not, when presented these kind of agenda, institutions will choose to ignore the other measures, it is, then, the responsibility of the overseeing professional agency, be it the coordination board or legislature, to articulate the case.