This is a look at students enrolled in Maryland community colleges in fall 2019. In fall 2019, there were 113,288 students enrolled in Maryland Community College. Of those students, 35,905 (31.7%) were enrolled full-time and 77,383 (68.3%) were enrolled part-time. I decided to dig deeper into this information by combining attendance status with student age. The Maryland Higher Education Commission (MHEC) reports enrollment of students aged 25 and older by attendance status. Approximately one-third of community college students are aged 25 or older. About 85% of community college students aged 25 and older attend part-time, while approximately 60% of community college students under age 25 attend part-time.

I made a Sankey diagram to show both age and attendance status of community college students at the same time in the same diagram. This is a different use of a Sankey diagram than I have made in the past. In the past, I have used a Sankey diagram to show individuals flowing through the education system. This diagram shows two variables related to the same population of students. I am happy with the result and find it easy to understand and read; however, I don’t know if people unfamiliar with Sankey diagrams will find it easy to read and understand. My next step will be to ask my friends and family about what they think about the visualization. I also wonder if there are other data sets that I use that would be better understood using this formate. Another way to show this information would be with a single bar graph with four segments: 1) aged 25 and over and part-time; 2) aged 25 and older full-time; 3) under 25 and part-time; and 4) under 25 and full-time.

Sankey-Community College Fall 2019 Enrollment by age and attendance Status

Source: Maryland Higher Education Commission, Databook 2021

Bar Graph-community College Fall 2019 Enrollment by age and attendance Status

The bar graph shows the same information as the Sankey diagram above, but it is another formate. The purpose of this post is to show this data in different forms on the web and be able to test them on various platforms and to remember what I learned about the data. From the bar graph visualization, it is easy to see that the largest group are students who are under 25 and attending part-time and the smallest group (by far) are students who are 25 and older who are attending full-time.

AmCharts has updated its library to version 5. AmCharts5 includes updates to their Venn diagram library. Since I love Venn diagrams I spent the morning figuring it out. I created the Venn diagram below to show HS completers. It took me a while to figure out the syntax. Overall I think I was mostly able to make it do what I wanted to do. However, I since haven’t figured out how to put a category entirely in another category. For example, I would like a big circle with all HS completers that includes HS graduates and HS certificate students.

The Venn diagram below is of Maryland public school students that completed high school. It shows the overlap of how the students that: (1) earned a completion certificate (for completing a special education program); (2) met the University System of Maryland (USM) requirements); (3) met the Career and Technical Education (CTE) requirements; and/or (4) met the regular diploma requirements. “Normal diploma” is just to indicate students that did not earn either a USM or CTE credentials in addition to their high school diploma. This is primarily for my own understanding of the data and to learn web-based data visualization techniques.

Now that I have made this visualization I am not sure if using a Venn diagram is better than a Sankey diagram for this data. I would also like to add additional information to the chart such as a title and to have the actual numbers displayed on the chart. As far as the data goes, I wish that I had information about the post-high school behavior of these different groups of students. According to this data, about 60.5% of high school completers met the USM requirements.

The colors used below are not intended to mean anything beyond looking nice. It took me a while to figure out the colors. Once I figured it out I just used a rainbow with my only intention to combine blue and yellow to make green.

StateWide High School CompLetion Venn Diagram

Source: Maryland State Department of Education, 2019 High School Completion

I have been busy with other work, so I have not had much time to post. I have been using the information from my past posts in my other work, so I think this is a valuable use of my time. I am learning how to better visualize data and better able to remember what data I have already examined. The other day I got asked a question about dual enrollment, and the first place I looked to answer the question was at an old blog post I had written earlier in the year.

Today, I am taking a brief look at educator qualifications. I have not looked at this data before, and I saw it was posted on the Maryland State Department of Education’s website.

Types of Educator Qualifications

First I looked at the types of data that they publish. They publish the count and percent of inexperienced educators, inexperienced teachers, out-of-field teachers, and teachers with emergency or provisional credentials. The data has two files, one by poverty level and the other by students of color. I love that I can download this data in an Excel file easily, but a weakness of the data presentation is that I’m not always sure what the definitions mean and there isn’t any easily accessible documentation. I could probably get additional information if I asked, but it isn’t worth it for my purposes which are learning data visualization techniques, getting a better idea about the data available, and remembering what I have read.

For this chart, I kept it in the order that the data is published, which is mostly alphabetical with Baltimore City, SEED, School, and statewide at the bottom. For a more formal chart, I would move Baltimore City up into alphabetical order and decide what to do about SEED and statewide. That level of effort didn’t seem reasonable for this exploratory chart.

For this split bar chart, I think that it is interesting that the grayed-out area does not equal 100%, rather I think it is the largest value in the column. I’m not sure what I think about it, but I do think it makes it easier to compare some of the larger values.

I wonder why some local school systems have more educators and teachers that are inexperienced, teaching out-of-field, or on an emergency or provisional credential. I will have to do more research into this area, but it is good to know this data exists for my future work. Next, I plan to dig deeper into the out-of-field teachers poverty level.

This is a test of a waterfall chart with negative numbers. This is just a test to see if I can recreate a waterfall chart I saw using Amcharts. I have linked the document with the original waterfall chart in the source below, the chart is on page 16 of the document. Initially had trouble with showing the final two bars because they went into negative numbers, but I was able to play around with the formatting to get it to display properly. As I note I do not have access to the underlying data, I used the displayed figures to produce the chart below. To completely recreate the chart I need to still figure out how to format the Y axis numbers. I need to add a “$” sign and truncate the numbers. I will research this and update once I figure it out.

ARP: American Rescue Plan

COLA: cost-of-living adjustment

IT: information technology

Source: Department of Legislative Services

I have made a few updates to my Sankey diagram that shows college enrollment by dually enrolled students. I really wish I had college enrollment data on non-dually enrolled students so I could compare the two groups.

I am publishing this update because my primary goal of this blog is to document for myself how to make better data visualizations.

Dual Enrollment College Pipeline

Twenty-one percent of public school 12th graders in Maryland during the 2019-2020 school year had a college record, that is they had been enrolled in a college class. The majority of these students participated in a dual enrollment program through their local school system. In fall 2020, the fall after they were slated to graduate from high school 79% of students who had a college record enrolled in college. This was during the height of the COVID-19 pandemic. Of those who enrolled in college, 75% enrolled at an in-State institution and 25% enrolled at an out-of-state institution. A little more than half of the in-State students (55%) enrolled at a community college, the remaining 45% enrolled at a public four-year or State-aided independent institution. Further, approximately half (51%) of students who enrolled in an in-State institution enrolled at their college of dual enrollment.

Source: Maryland Longitudinal Data System Center

Further Questions

I would be curious to know how college enrollment patterns of dual enrollment students compare to all public school 12th graders in Maryland. The Sankey graph above with that information would be much improved. Without that information, I am not really sure what it all means.

I am also interested in whether the dual enrollment credits earned transferred to the college in a meaningful way. According to MLDS data, students that took dual enrollment courses in high school earned an average of 2.14 credits.

Further, I wish that I had information on whether these students took AP or IB courses, which can also lead to college credit. I am curious if students are taking dual enrollment courses in addition to or instead of these courses. I wonder if the courses taken are primarily due to student choice, or due to the courses available at the student’s particular high school.

Finally, I am curious how these students perform in college.

Every year the Maryland Longitudinal Data System (MLDS) Produces a report on the Maryland public school pathways. The current report shows the number of students who immediately enrolled in college earned a college degree by age 25 in the same sector that they initially enrolled. Recently MLDS updated the data to to show what has happened to the class of 2012. From the high school class of 2011 to 2012 the percentage of students who graduated from an independent non-profit four-year institution in the State and out-of-state instittuions decreased. Most other measures generally stayed about the same.

Source: Maryland Longitudinal Data Systen, Maryland Public School Pathways, 2012

Source: Maryland Longitudinal Data System, Maryland Public School Pathways 2011

NOTES ABOUT THE DATA

  • These notes are adapted from the notes provided by the Maryland Longitudinal Data System. Any errors are my own.
  • To be counted as a community college graduate, the student must have enrolled in any community college and graduated from any community college. Students who start at a community college but graduate from a college in another sector are not counted as graduates. Students who start in another sector but graduate from a community college are also excluded. To be counted as persisting (still in college), the student must have NOT graduated from any community college and be enrolled in any community college in Fall 2019. Some students who enrolled in community college transferred from the college and are enrolled in another four-year public, state-aided independent, or out-of-state institutions. Those students are not reported here.
  • To be counted as a public-four year college graduate, the student must have enrolled in any four-year public and graduated from any four-year public. Students who start at a four-year public but graduate from a college in another sector are not counted as graduates. Students who start in another sector but graduate from a four-year public are also excluded. To be counted as persisting (still in college), the student must have NOT graduated from any four-year public and be enrolled in any four-year public in Fall 2019. Some students who enrolled in a four-year public transferred from the college and are enrolled in another community college, state-aided independent institutions, or out-of-state institutions. Those students are not reported here.
  • To be counted as a State-aided indepented college graduate, the student must have enrolled in any state-aided independent institutions and graduated from any state-aided independent institution. Students who start at a state-aided institution but graduate from a college in another sector are not counted as graduates. Students who start in another sector but graduate from a state-aided independent institution are also excluded. To be counted as persisting (still in college), the student must have NOT graduated from any state-aided independent institutions and be enrolled in any state-aided independent institutions in Fall 2019. Some students when enrolled in a state-aided independent institutions transferred from the college and are enrolled in another community college, public, or out-of-state institutions. Those students are not reported here.
  • The out-of-state table above evaluates within sector college graduation independent of college of enrollment. To be counted as a college graduate, the student must have enrolled in out-of-state institutions of any type and graduated from an out-of-state institution of any type. Students who start at an out-of-state institution but graduate from a college in Maryland are not counted as graduates. Students who start at a college in Maryland but graduate from an out-of-state institution are also excluded. Out-of-state institutions may be community colleges, public four-year, or other types of private institutions.

Statewide about 14% of 12th graders in the 2019-2020 school year had participated in a dual enrollment program during high school; however, dual enrollment participation various by local school system. Approximately 50% of 12th graders from Frederick County Public School System participate in dual enrollment, while only about 3% of 12th graders from Anne Arundel County Public Schools participate.

In general, the counties with larger enrollment have fewer students participating in dual enrollment programs. Frederick County, and to a lesser extent Howard County, are the only larger systems with dual enrollment participation over the statewide average. Local school systems set their own rules about participation and establish relationships with colleges.

Overall 17 counties have dual enrollment programs

This map presents the same data in map format.

Dual Enrollment in Frederick County

Frederick County has the highest participation in dual enrollment programs in the State. Fifty percent of 12th graders in the county during the 2019-2020 school year participated in a dual enrollment program sometime during high school. As shown below, 75% of those who participated in dual enrollment earned between 0.5 and 2 credits.

The impact of earning college credit “early” as a high school-aged student interests me. As with many things in education, what is defined as dual enrollment depends on the program or the researcher. Factors that are considered in the definition include, when the course was taken during the year (summer programs often are not included), who paid for the course, and whether the student received both high school and college credit for the course.

I am trying to understand what dual enrollment “looks like” in Maryland using data published by the Maryland Longitudinal Data System (MLDS) Center. To make this sunburst chart I took the number of 12th graders enrolled in Maryland public schools for the 2019-2020 school year from the Maryland Report Card. Then I took dual enrollment information published by MLDS Center: the number of public 12th-grade students with a college enrollment record and the number of students with a dual enrollment record. Students with dual enrollment record have information on the number of college credits earned while in high school.

According to this data, approximately 20% of high school seniors had a college record, and about 14% had taken a dual enrollment course. About 45% of those who had taken a dual enrollment course earned between 0.5 and 1 credits. Almost 2% of students who had taken a dual enrollment course, 160 students, earned 12 credits or more.

It is unknown how many dual enrollment credits transferred and counted towards degree requirements.

Click on “Flagged Dual Enrollment” for information on credits earned by these students.

Data Notes From the MLDS Center data

This table provides data on the dual enrollment credits based upon dual enrollment activity that spans 9th to 12th grade for high school students in 12th grade in 2019-2020 academic year.  The following definitions apply:
The initial population was selected by identifying students who had both a high school enrollment record and a college enrollment record in the 2019-2020 academic year (fall to spring). Summer enrollment information was excluded from this analysis.   For the portions of this analysis that related to courses and credits, the initial population was reduced using the following logic:
1) the student’s course record must be flagged as a dual enrollment course (comprehensive course data is not available for all local school systems), and
2) the student must have both a college enrollment record for the same period as the high school course record, and
3) the course must have credits (0 credit courses were excluded which represent <1% of all courses flagged as dual enrollment courses).

Course records identified as duplicate were unduplicated to include only a single record in the analysis. The duplicate records appear to be a data reporting issue. Unduplicating the records may understate the overall course record total.

Earned credits were calculated based upon the course completion status of passed.  Attempted credits were calculated based upon the course status of passed, failed, withdrawn, and incomplete.  Due to timing of data extraction course outcome data may be incomplete.  It is possible that students not counted as earning credit did earn credit once courses with the status of incomplete were resolved.  It is also possible that courses with the status of failed or withdrawn had grade changes that occurred after data extraction.   All credit values were derived from course records from the Maryland State Department of Education.

Keeping up with the COVID-19 data published by Anne Arundel County Public Schools on an individual school basis is not really sustainable because it is currently being published daily. The data can not be downloaded so it has to be transcribed by hand. So I am looking at some other ways to visualize the data that might be less time-intensive, and still informative. My primary goals are to 1) learn how to build various data visualizations, and 2) explore the utility of various data visualizations. Maintaining a data dashboard, unless I am curious about the data that day is not my primary purpose.

One idea is to look at the cumulative COVID-19 cases by both students and staff on a daily basis. I did not think to capture this data earlier, so I have a few days of data missing. I also have missing days because life got in the way. It doesn’t seem hard to enter in a few data points every day until you get wrapped up in life and then you realize that you haven’t even looked at the website in a few days. I wish that they published the data in a way that I could download their archival data, but I will take what they share. The Maryland Health Department publishes their archival school outbreak data; however, their data only reflects outbreaks (as they have defined them) and is only published once a week on Wednesdays. Because of the missing data, I used the step model of lines as I think it is a more honest way to show the data.

This line chart shows the cumulative daily COVID-19 cases for students and staff for the 2021-2022 school year. The number of cases are from the Anne Arundel County Public Schools data dashboard. I have added dots for the days that I recorded the published data. There are no dots on the days that I do not record the data.