Reflections on Summer Research

Now that I can see the light at the end of the data tunnel and the end of U.Discover is on the horizon, I thought I’d sum up a few things I’ve gotten out of this program.

1. Doing research on public K-12 schools and expecting to complete it during the Summer months is not the best idea.

While I didn’t need IRB approval since I only needed to ask if the school was named for MLK and what year it was so named (basically public information), I vastly overestimated my ability to get people on the phone at the end of the school year and into the summer.  If I had it to do over, I would have started with the more available part (sifting through mounds of data) instead of the hard part (contacting real humans). Luckily, I don’t need that data to complete something reasonable for U.Discover and I’ll be able to do the remaining work to expand the U.Discover research during the Fall in time to present at Ideafest.

2. Sifting through data is tedious and time-consuming, especially to ensure a good, solid sample that can maintain integrity for analysis.

I started with so many MLK schools, I thought even after weeding them down to have a consistent sample of neighborhood-style schools, where children attend based on where they live, that I would still have over 100 MLK schools. After excluding alternative/continuation, vocational, selective, magnet and charter schools, as well as schools without 2007-08 data available, my MLK sample dwindled to 75 schools. 

3. Coming up with a strong research design takes time and is harder than it looks.

While I spent too much time in the beginning trying to collect data that would be easier (actually possible!) during the Fall, I also underestimated the time needed to ensure consistent sample and a good design. Creating a good design requires thought about what is bad in one’s design, then trying to fix it, repeat that process about 10 times. It takes awhile, but is very satisfying once it’s done.

4. Unexpected data and ideas for future research

Since a majority of the students at MLK schools are minorities (at least it seems that way in the raw data so far), there were a fair number of schools whose students were solidly one minority or possibly two minorites. In many of these schools, there were significant differences in the assessment data that didn’t comport to what one would expect from what is learned in the Sociology core classes. It seems that research on minority students in schools made up solely of that minority group, possibly one more, could show drastically different results than the research done in the past when white students were a majority in most state/county/districts and minority students couldn’t be studied as a majority in a regular public school. Anyways, the point of this is that I have found more areas to research later that also interest me. This is good!

5. One big, huge, invaluable learning experience

The reason I applied for U.Discover (beyond tripping over the sign in the hallway) is that I thought it would be a way for me to learn more about research from the presentations and my fellow students. I was going to try to do this research on my own this summer (before I fell over the sign) and I thought the structure, faculty mentor, and weekly lecture would be an extra bonus. The U.Discover program provided exactly what I had hoped for and also made me think about the projects my fellow U.Discover people were working on and apply it to my interests and discipline, as well as contribute my thoughts on their projects and incorporate their thoughts about mine. While we still have a couple weeks left, I’m ready to call the program and my research a real learning experience and I’m really thankful that I was given the opportunity to participate!


What to do about the Filipinos!

So, I’ve got a Filipino problem! California breaks Filipinos out as a separate demographic from both Asians and from Pacific Islanders. Culturally, I can understand that. We owned the Phillippines for awhile (they might still be a protectorate for all I know) and they were colonized by Spain for a whole lotta years before that. They aren’t really cultural Asian or PI after all that Spanish/American influence. However, this is annoying me. I don’t have a Filipino spot in my spreadsheet! I’ve considered adding them together with the Asian or PI numbers, but I don’t know. I really had no clue I’d run into so many data issues for something as straightforward as “get test assessment data and plug into excel”.

Willie L Brown Jr. Elementary School

Man, I don’t know what these folks are doing at Willie L. Brown Jr. Elementary in San Francisco, CA, but they could have instructed the kids to pick option C for every test question and scored better on their state assessments than this. I’ve seen some pretty bad scores working on this project, and as a Cali native I know how sad their education is, but this is seriously so bad, I had to put ’em on blast:

So, Willie L. Brown Jr. Elementary, why in the heck are only 5% of your student body proficient in English Language Arts by 7th grade? Why only 3% proficient in Math in 7th grade?? How is that even statistically possible?????

I’d also like to point out that 0% of their female students are proficient in Math. That’s right, folks, ZERO.

(I’m so glad this school isn’t named after MLK 🙂 But I guess I should mention that Willie Brown is a former mayor of San Francisco and is Afro-American for people who aren’t familiar with CA politics)

Strange Things Along the Way

So my life is still data gathering and Excel, but I’ve been noticing some interesting things that I may look into later. The first thing I’ve been noticing was a trend in Salinas, CA elementary schools that I was using as a comparative sample to my MLK school in Salinas. At these schools, male and female students are either nearly dead even in math proficiency scores or the females are proficient 10-20% points above the males.  The schools in Salinas are completely Latino, as far as statistically reportable goes. This has me wondering if this pattern will emerge in other fully Latino schools. I haven’t seen it in more diverse schools.

Another random thing I’m noticing is in San Francisco middle schools. California apparently collects data on the level of parental education for their students who test.  Now, traditional thought on this subject is that the higher the parental level of education, the higher scores the children will get.  But check these scores out! (the percentage refers to the percentage of children who got proficient or above on state testing whose parents are in the particular category)

At Visitacion Valley Middle, the breakdown was :

Not high school grad – 25%

High school grad – 17%

Some college – 35%

Decline to state – 18%

At Horace Mann Middle:

Not high school grad – 25%

High school grad – 21%

Some college – 10%

Decline to state – 18%

It seems that the kids of non-high school grads are really holding there own there! I have two theories of why this could be. First theory is that maybe the non-high school grads are also not able to afford day care and are thus at home with their kids during the day to supervise and assist with homework to a greater extent than the other parents. The second theory would be that those parents wish they had more opportunities for a better education and push the importance of learning on their children more than some other parents would.  I saw a lot of both groups growing up. A lot of the migrant families I knew pushed education very hard for their children and their kids did very well, even though the parents had a limited education (often only to 8th grade, if that). I also grew up in the days without time limits on welfare and knew plenty of welfare moms who made sure their kids did their homework and helped them learn at home to supplement what the school was doing.

I’d love to hear any other theories if anyone has any! I just thought I’d share my little bright spot in this whole data collection thing. There’s some really random trends in some of these neighborhoods. I’m loving how researching one thing can lead to so many more ideas to work on later.

Forward Motion!

I finally feel like this project is moving forward! I spent a lot of time (too much time??) deciding on data/sample parameters that would provide for accurate results. I suppose that is really the most important part. If the design is bad, the whole thing is bad, right?  So, I’m definitely running behind, but at least whatever I get done I will be confident in and be able to defend and stand behind. My intention for this project has always been thoroughness and publication so if it isn’t 100% at the end of U.Discover, I will be able to present some representative findings, but not the “final word” in findings.  Luckily the school library is open about 15 hours a day, so I might actually get back on track 🙂

As for some results, out of 9 schools, the MLK school in the Tuscaloosa City District in Alabama has the lowest test scores in the district.

Data + Excel = *yawn*

Sorry folks, but compiling data someone else collected is kinda boring! It’s times like this that I wish I could just run some script to spider MLK websites for me and plug the state data into an excel sheet. That would be nice.  Instead, I’m rating school websites based on the scale I posted earlier, looking for year of founding, and finalizing exactly what data is going to get analyzed out of the mountains of stuff the Feds are requiring the states to collect. The upside is all the data is there. The downside is there is tons of it. So, if anyone wants to hear my adventures in plugging data into Excel, I’ll be happy to expound on that. No really, I would be thrilled.

Draft Essay: Intro/stereotype/partial data sample

“You know what’s sad? Martin Luther King stood for non-violence. And I don’t care where you are in America, if you’re on Martin Luther King Boulevard, there’s some violence going down.” –Chris Rock 

            Many people in the U.S. have heard the comedy routine by Chris Rock talking about the violence on Martin Luther King Boulevard. Part of great comedy is the comedian’s ability to tap into the stereotypes and nuances of society, exaggerate them and laugh heartily. Chris Rock did exactly that. There is a fairly pervasive stereotype that locations named after Martin Luther King, Jr. (MLK) are in bad neighborhoods, substandard, and even violent. Focusing in on schools named for MLK, there is a wide belief that these schools should be avoided as they are under-performing institutions serving poor, minority children.

            Naming schools in honor of MLK has continuously raised controversy. In the early 1970’s in Omaha, Nebraska, members of the Black community spoke out against putting a school named in honor of MLK in the heavily Black section of northern Omaha because they felt it would cause further segregation (School’s website). In 1998, a controversy arose in Riverside, CA over the plan to name a new high school after MLK in an area that was predominately White. Many parents expressed concerns that their children would be perceived as coming from a Black school and that perception would hurt the children’s college prospects. People also expressed concerns that MLK was not relevant to the area and should not have a school named for him (Alderman 2002).  As recently as June 18, 2009, Dr. Ben Chavis, advisor emeritus and former principal of American Indian Public Charter School, on the Bill Handel Show on KFI 640 in Los Angeles, stated:

 “I’m Indian. Why can’t something good be called American Indian? Most schools called American Indian or Cesar Chavez or Martin Luther King, they suck! If you want to check out a bad school, call it after a minority […]or the streets, Martin Luther King Way. Don’t hang out on Martin Luther King Way, you’ll get jumped.[…] They name these schools and we’re embarrassing our former leaders by doing that because Martin Luther King wouldn’t want all these losing schools after him.”

            This stereotype where MLK schools are often perceived as being rough, inner-city schools with low academic performance inspired this research paper. While Dr. Alderman addressed the perception of MLK schools as being “Black schools” in his 2002 research published in Urban Geography, his focus is from the perspective of a cultural geographer with more of a focus on location and dispersal. The focus of the research herein is to directly address the concept of MLK schools churning out uneducated citizens more so than other neighborhood schools. To address this issue, a sample of over 100 MLK schools is examined as to racial composition, percentage of students receiving free/reduced lunch or classes as “economically disadvantaged”, and academic proficiency as quantified on NCLB testing. This data will also be collected on a sample of non-MLK schools within 5 miles and within the same district as each MLK school in order to compare whether or not MLK schools are really doing any worse than the other schools in the neighborhood.