A closer look at the National Assessment of Education Progress (NAEP)

July 21, 2014

We noted in a previous post that students in Michigan and Detroit post weaker performances on the National Assessment of Educational Progress (NAEP) than states across the country, particularly Minnesota. For many years, researchers have attempted to identify factors associated with NAEP scores, which would be of considerable interest to stakeholders who want to address Michigan and Detroit’s NAEP performance. Here, we will briefly summarize some of these factors and selected research addressing them.

For several reasons, NAEP scores in mathematics and reading have been of primary interest to researchers. Much of the research on NAEP score predictors, therefore, focuses on performance in these two subject areas.

Given the primacy of demographic factors such as race, ethnicity, and gender in education research, researchers have also asked whether these variables might predict students’ NAEP performance. For example, Vanneman et al. (2009) and Hemphil & Venneman (2011) noted achievement gaps in NAEP mathematics scores between African-American and White students and between White and Hispanic students. A number of peer-reviewed studies also identify race as a factor in NAEP results (Tate, 1997; Fuchs & Reklis, 1994; Thomas & Stockton, 2003). Some studies explore this factor at a greater depth; for example, Card & Rothstein (2007) attribute the race/ethnicity gap (though using SAT, not NAEP scores) to racial segregation of particular geographic areas, while Lubienski (2006) finds that varying test modes for NAEP mathematics appears to have little or no impact on performance.

There is less evidence for the influence of gender on NAEP scores (Abedi & Lord, 2001; Tate, 1997; Hyde & Linn, 2006; Guthrie et al., 2001), though Thomas and Stockton (2003) identify a small positive relationship between female students and NEAP reading scores and McGraw and colleagues (2006) find a negative relationship between female students and NAEP mathematics scores.

The results are also fairly consistent for socioeconomic status (SES). Biddle (1997) and McQuillan (1998) find a negative relationship between poverty and NAEP scores while Abedi & Lord (2001) and Nelson et al. (2003) find a negative relationship between Free lunch/Aid to Families with Dependent Children (AFDC) status and NAEP scores. Byrnes (2003) and Fuchs & Reklis (1994) find a positive association between parental education levels and students’ 12th and 8th grade NAEP math scores, respectively. Using 1996 NAEP data, Lubienski (2002) finds that SES factors such as parent education and number of literary resources in the home do not explain the African-American/White achievement gap discussed above. Inherent in these studies is, of course, the selection and validity of individual-level or school-level (e.g., Title I designated school) definitions of SES (Thomas & Stockton, 2003).

Some researchers have also considered other literacy-related factors and their possible effect on NAEP scores. For instance, Abedi et al. (2001) and Abedi and Lord (2001) find that English Language Learner (ELL) and Limited English Proficiency (LEP) statuses are negatively related to NAEP mathematics performance. Length of stay in the United States appears to be positively associated with NAEP mathematics performance (Abedi et al., 2001). Access to printed reading material (McQuillan, 1998) and access to school and public libraries (Krashen et al., 2012) also appear to be positively associated with NAEP reading scores.

In general, coursework and related preparation seem to be consistent predictors of NAEP scores. Tate (1997), Abedi & Lord (2001), and Abedi et al. (2001) find that advanced mathematics preparation and coursework are positive predictors of NAEP math scores. Guthrie et al. (2001) and Pinnell et al. (1995) find that reading opportunities and reading prosody, respectively, are positively associated with NAEP reading performance. Abedi et al. (2001) find evidence of a positive association between students’ overall grades since 6th grade and NAEP mathematics performance.

Some authors have considered more systemic or institutional factors in their NAEP research, though this research is less consistent and (less?) extensive. Lubienski (2006) finds a positive association between NAEP math scores and (1) collaborative problem-solving instruction, (2) teacher knowledge of National Council of Teachers of Mathematics (NCTM) standards, and (3) certain ‘reform-oriented’ teaching practices such as non-number math strands. Guthrie (2001) finds that balanced reading instruction is positively associated with Grade 4 NAEP Reading Comprehension in Maryland. Grissmer et al. (2000) and Fitzpatrick (2008) find that greater levels of Kindergarten and pre-Kindergarten participation are positively associated with NAEP scores. Carnoy & Loeb (2002) find a positive association between gains in NAEP mathematics results and strength of state accountability (based on high-stakes testing to sanction and reward schools), but no effect on 9th grade retention rates. In a study supported by the American Federation of Teachers (AFT), Nelson et al. (2003) find that charter school attendance, especially in autonomous charter schools in urban areas, are negatively associated with NAEP math and reading test scores. Nevertheless, institutional factors such as these are not definitive in the literature, and their results should be viewed with caution.

Those who are interested in understanding why Michigan and Detroit students lag behind the rest of the nation in NAEP scores might explore some of the variables discussed above. There is not, however, any one variable or combination of variables that appears to serve as a sole and consistent predictor of NAEP performance, and this will pose a challenge for both understanding and devising solutions to the matter.

 

Bibliography

Abedi, J. & Lord, C. (2001). The language factor in mathematics tests. Applied Measurement in Education 14(3), 219-234.

Abedi, J., Lord, C., & Hofstetter, C. (2001). Impact of selected background variables on students’ NAEP math performance. Center for the Study of Evaluation, University of California, Los Angeles.

Biddle, B.J. (1997). Foolishness, dangerous nonsense, and real correlates of state differences in achievement. Phi Delta Kappan 79(1), 8-13.

Byrnes, J.P. (2003). Factors predictive of mathematics achievement in white, black, and Hispanic 12th graders. Journal of Educational Psychology 95(2), 316-326.

Card, D. & Rothstein, J. (2007). Racial segregation and the black-white test score gap. Journal of Public Economics 91(11) 2158-2184.

Carney, M. & Loeb, S. (2002). Does external accountability affect student outcomes? A cross-state analysis. Educational Evaluation and Policy Analysis 24(4), 205-331.

Fitzpatrick, M.D. (2008). Starting school at four: The effect of universal pre-kindergarten on children’s academic achievement. The B.E. Journal of Economic Analysis & Policy 8(1) 1-38.

Fuchs, V.R. & Reklis, D.M. (1994). Mathematical achievement in eighth grade: Interstate and racial differences. National Bureau of Economic Research. Working Paper No. 4784.

Grissmer, D., Flanagan, A., Kawata, J., & Williamson, S. (2000). Improving Student Achievement: What state NAEP test scores tell us. RAND Corporation.

Guthrie, J.T., Schafer, W.D., & Huang, C.W. (2001). Benefits of opportunity to read and balanced instruction on the NAEP. Journal of Educational Research 94(3), 145-162.

Hemphil, F.C. & Vanneman, A. (2011.) Achievement gaps: How Hispanic and white students in public schools perform in mathematics and reading on the national assessment of educational progress. Statistical Analysis Report. NCES 2011-459. National Center for Education Statistics.

Hyde, J.S. & Linn, M.C. (2006) Gender similarities in mathematics and science. Science-New York Then Washington 314(5799), 599.

Krashen, S., Lee, S., & McQuillan, J. (2012). Is the library important? Multivariate studies at the national and international level. Journal of Language & Literacy Education 8(1), 27-36.

Lubienski, S.P. (2002). A closer look at the black-white mathematics gaps: Interactions of race and SES in NAEP achievement and instructional practices data. Journal of Negro Education 71(4), 269-287.

Lubienski, S.P. (2006). Examining instruction, achievement, and equity with NAEP mathematics data. Education Policy Analysis Archives 14(14), 1-33.

Mcgraw, R., Lubienski, S.P., & Strutchens, M.E. (2006). A closer look at gender in NAEP mathematics achievement and affect data: Intersections with achievement, race/ethnicity, and socioeconomic status. Journal for Research in Mathematics Education 37(2), 129-150.

McQuillan, J. (1998). The literacy crisis: False claims and real solutions. Portsmouth, NH: Heinemann.

Nelson, F.H., Rosenberg, B., & Van Meter, N. (2003). Charter school achievement on the 2003 National Assessment of Educational Progress. American Federation of Teachers, AFL-CIO.

PInnell, G.S., Pilulski, J.J., Wixson, K.K., Campbell, J.R., Gough, P.B., & Beatty, A.S. (1995). Listening to children read aloud: Data from NAEP’s integrated reading performance record (IRPR) at grade 4. National Center for Education Statistics.

Thomas, J. & Stockton, C. (2003). Socioeconomic status, race, gender, & retention: Impact on student achievement. Essays in Education 7.

Tate, W.F. (1997). Race-ethnicity, SES, gender, and language proficiency trends in mathematics achievement: An update. Journal for Research in Mathematics Education 28(6), 652-679.

Vanneman, A., Hamilton, L., Anderson, J.B., & Rahman, T. (2009). Achievement gaps: How black and white students in public schools perform in mathematics and reading on the National Assessment of Education Progress. Statistical Analysis Report. NCES 2009-455. National Center for Education Statistics.

Minnesota easily reins in carbon emissions

July 20, 2014

According to the New York Times,  Minnesota continues to mandate strict energy regulations, a fete that residents easily comply with. The article showcases how the state uses more wind energy than all but four states in the country and has reduced its carbon emissions by about 33 percent since 2003. To read more click here.

 

Detroit vacancies increase from September 2013 to March 2014

July 17, 2014

vacancy

According to data provided by the US Postal Service, residential vacancies have increased by 1,502 from January 2014 to March 2014. From September 2013 to March 2014 vacancies increased by over 2,000. According to USPS, they determine that a residency is vacant if an occupant has not collected their mail for 90 days are more.

The Center for Urban Studies creates a data base with this information and it provides a more in-depth look at the vacancies. The USPS publicly releases the vacancy data on a quarterly basis; this is possible through an agreement with the U.S. Department of Housing and Urban Development.  

Region’s percentage of Asian residents higher than state average

July 14, 2014

As we continue to explore what makes up Southeast Michigan’s population we find that those of Asian descent make up a growing proportion of certain communities’ populations. This post examines both the percentage of residents of Asian descent in each community in the region along with their background.
In this post we see that although some counties have an overall higher percentage of Asian residents than others, there are pockets throughout the region with much higher proportions of Asians than what exists in their county or in the region.

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Overall, the average percent of Michigan residents with Asian ancestry was 2.4 percent according to the 2012 5-year estimates of the American Community Survey. In the seven-county region, three of the seven counties are below this average (Monroe, Livingston and St. Clair counties). The county with the highest population of residents of Asian descent in the region was Washtenaw County; 7.4 percent of its indicated an Asian background.

The map above not only shows what percent of residents are of Asian descent in each county, but also what Asian subgroup is most dominant. For example, in Washtenaw and Livingston counties, those of Chinese descent make up the majority of the Asian population. However, in St. Clair County, those of Filipino descent are the most common subgroup; Asian Indian descent is the most common subgroup for the remaining counties and the City of Detroit (Note that this identity may also be selected by those with Bangladeshi or Pakistani backgrounds who often choose this designation). 

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While the first map showed the most dominant Asian subcultures represented in each county, this map shows what cultures are most represented in each community.

As may have been expected by the first map, those of Asian Indian descent were most heavily represented in Wayne, Oakland and Macomb counties.  However, in the City of Taylor and on Grosse Ile, located in Wayne County, those of Pakistani descent were the most represented. In Pontiac in Oakland County, those of Hmong descent were the most represented Asian subgroup.  

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The previous maps showcased what Asian subgroups were represented throughout the region and this one shows the percentage of residents of Asian descent in each community. At 19.6 percent, the City of Troy in Oakland County had the highest percent of residents with Asian descent of all the communities in the region. The majority (48.4 percent of Asians) are of an Asian Indian background, followed by Chinese (25.2%) and Koreans (9.3%). Also in Oakland County, the city of Novi has a high percentage of residents of Asian descent; this percentage is 16.5.

The highest proportion of Asian residents in Wayne County was in Hamtramck at 18.9% (second in the region, behind Troy).  Residents identified Asian Indian (1,882) as the predominant subculture, ahead of Bangladeshi (1,664), however, the country of birth for Hamtramck residents during the same period was listed as India for 43 residents, and Bangladesh for 2,928, suggesting that many Bangladeshis may have identified as Asian Indian.

In Washtenaw County, Ann Arbor Township has the highest percent of residents of Asian descent. This percentage is 16.1, majority of whom are Japanese. The city of Ann Arbor’s population is at 14.6 percent, majority of whom are Chinese. 

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The map above is a dot-density map of Asian subgroups, showing where residents live, instead of the percentage of the population. From this map you can see that while there may be a smaller percentage of the population that is Asian in some areas, the actual number of residents of Asian descent in highly populated areas may be large. There is a large number of Asian residents forming a semi-circle around the north and west of the city of Detroit, and some sub-group patterns arise. Hmong Asians live primarily in Pontiac and along the Macomb and Wayne county borders. Pakistanis form a cohesive presence between the airport and the rive. Laotians dominate the New Haven area.

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Within Wayne County, in addition to the Pakistanis, Cambodians are prevalent in Garden City and Hmong in Northeast Detroit. The large numbers of Asians in Northwest Wayne demonstrates an eclectic mix of cultures, and is more apparent when viewed with dot-density rather than percentage.

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In the Detroit area, the expanse of the Hmong is apparent up the Gratiot Avenue corridor into Macomb beyond Detroit. Various ethnicities have chosen small areas of Detroit to call home, including Filipinos near and in Hazel park, Chinese in west Detroit neighborhoods, Thais near Redford, Pakistanis and Japanese on the East side,.

Wayne County has highest pregnancy, abortion rates

July 7, 2014

In this post we examine rates in the region related to fertility and pregnancy including abortion and birth rates. In all four of the maps shown below, Wayne County’s rates are above the state average are also the highest in the region. All rates were obtained from the Michigan Department of Community Health and are based on birth rates per 1,000 residents for population ages 15-44.

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The fertility rate is defined as the number of live births per 1,000 women between the ages of 15 and 44, according to the Michigan Department of Community Health.

For the State of Michigan, the average fertility rate in 2013 was 59.3. Wayne County was the only county in the seven-county region whose fertility rate was higher than the state average at 64.8. Washtenaw County had the lowest fertility rate at 44.0.

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The pregnancy rate is defined as the sum of live births, abortions and estimated miscarriages per 1,000 women between the ages of 15 and 44, according to the Michigan Department of Community Health. In 2013, Macomb and Wayne Counties both reported pregnancy rates above the state average of 85.9, although Macomb County was only slightly above average, with a rate of 86.6. Wayne County’s rate was more than 20 points above the state average at 109.9.

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The birth rate is defined as the number of live births per 1,000 residents, according to the Michigan Department of Community Health.  The state average for the birth rate in 2013, was 11.4. Wayne County’s birth rate was the only county in the region above the state average at 13.1. Monroe and Livingston counties had the lowest birth rates in the region, with both reporting at 9.2.

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The abortion rate is defined as the number of abortions per 1,000 women between the ages of 15 and 44, according to the Michigan Department of Community Health. The average abortion rate for the State of Michigan in 2013 was 13.4. Wayne County’s abortion rate was more than double the state’s at 28.9. Macomb and Oakland Counties also had  rates above the state average at 15.8 and 14.4, respectively. Monroe County had the lowest rate at 7.3.

 

Earlier this year, several local media outlets reported on Detroit’s high abortion rate. To read more, click here.

 

Region’s child population higher than elderly population

June 30, 2014

The focus of this post is on the percent of children under the age of 18 in the seven-county region. In 2012, according to the American Community Survey, the average percent of children in the state of Michigan was 23.6 percent. This post shows that the percent of children across the region  is higher than the elderly population in the region. Three of the seven counties in Southeastern Michigan had a lower percentage of children than the state average.

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Although children under the age of 18 made up 23.6 percent of the state’s population, there were only four counties in the region at or above this threshold. St. Clair was right at the state average, while three counties were above and three below the state average. The three counties with a higher percentage of children were Livingston (25.3%), Wayne (25.3%), and Monroe (24.0%). Washtenaw County had the lowest percent of children under the age 18 (20.7%).

In last week’s post on the elderly population, St. Clair (14.8%) and Macomb (14.4%) counties had the highest population of residents age 65 and above. Washtenaw County had the lowest elderly population at 10.6 percent.

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The above map provides a closer look at how the child population is distributed across the region. Livingston County only has one community that has a lower percentage of children than the state average, however, there are few areas with 800 children or more (it should be noted Livingston County has a much lower population than Macomb, Oakland and Wayne counties). As the yellow dots show, there is a high concentration of children in the City of Detroit and the communities surrounding it, such as Warren, Southfield and Dearborn.

In Washtenaw County, the child population is concentrated in the Ann Arbor area. In Macomb County, which had the second lowest percentage of children in the region, the southern part of the county had a high number of children despite having a lower than state average percentage of children.

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The above map provides a look at the child population in the City of Detroit. When comparing this map to the Detroit map in the previous post about the elderly population, it can be seen there are several Census tracts where the elderly population is above the state average but the child population is below. Many of these Census tracts are northwest of Highland Park, around Palmer Park, and in the area between Highland Park and Belle Isle.

St. Clair, Macomb counties have highest percent of elderly population

June 23, 2014

As our population ages, there are many factors that will need to be considered.  As the Baby Boomers reach retirement age and beyond, there are many issues that will need to be discussed and addressed, from housing surpluses to medical care. In order to address these issues, however, we must first understand the size of the elderly population, ages 65 and older.

In this post, we will examine that population in the seven county region for the year 2012. All data was received from the American Community Survey.  According to this data, an average of 13.9% of all residents in the State of Michigan were age 65 and older.

Slide3

As the above map shows, St. Clair (14.6%) and Macomb (14.4 %) counties have the highest percent of residents age 65 and older in the region. Washtenaw County, which is home to the University of Michigan, has the lowest percent of elderly in the region at, 10.3 percent. Reportedly, in the City of Detroit, 11.5 percent of the population is aged 65 or older.

Slide5

This map shows that, overall, a majority of communities in the region had less residents aged 65 and older than the state average of 13.9%. The yellow dots depict concentrations where there are 200 or more residents are age 65 and older. While the City of Detroit is lower than the state average (11.54%),  the size of the population means that there are still a large number of residents within the city limits or nearby who are aging and may need additional services, such as transportation to health facilities and senior activity centers. There are about 20 communities outside of Wayne County, and southern Oakland and Macomb counties, where the percent of residents age 65 or older is above the state average, including areas near the Ohio border and along Lake St. Clair

Slide7

This map sheds additional light on Detroit’s elderly population. The yellow dots depict concentrations of 200 people aged 65 or above. While there are dozens of such areas with such a presence of the elderly population, there are four concentrated areas in the city where the elderly population resides, and comprises a higher proportion than the state average. These areas, colored in red, are located in clusters between the city’s border and Highland Park (which also has a significant elderly population), and on the near East side.

 

Middle school students also show slow progress in MEAP testing

June 16, 2014

Last week, we examined the MEAP scores for students in grades three through five in the intermediate school districts located within the seven-county region as well as the Detroit Public Schools. This week, we will examine the MEAP scores for students grades six through nine within the same region. As our earlier post showed, progress for students in grades three through five was slow. This week’s post, however, shows more promising results, with the exception of seventh-grade reading and sixth- and ninth-grade social studies.

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In St. Clair County, the St. Clair Regional Education Service Agency (RESA)  experienced a decrease in MEAP math scores for sixth- and seventh-grade students from fall 2012 to fall 2013. For the sixth-graders, there was a 2.8 decrease in the percent of students proficient in math, and for the seventh-graders, it was a 0.2 percent decrease.

 

Overall in the region, the percent of students proficient in math increased the most among sixth-graders. The Oakland ISD had both the highest percent of sixth-graders proficient in math (55%) and the highest percent increase of sixth-graders proficient in math (7.3%). Washtenaw County had the highest percent of seventh- and eighth-graders proficient in math (53.7 and 53.9%, respectively) while Detroit Public Schools had the lowest percent proficient across all three grade levels (6th: 14.8%, 7th: 11.8%, 8th: 12.2%).

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The eighth-grade map is currently not available; please check back soon. 

As can be seen by one of the maps above, seventh-graders across the seven-county region struggled to increase their reading proficiency as not one ISD or DPS experienced an increase in the percent of proficient students. The Monroe ISD experienced the largest decrease among seventh-graders from fall 2012 to fall 2013 at 4.9 percent. It was DPS, though, that had the lowest percent of students proficient in seventh grade reading, 29.1 percent. Even though there were decreases in proficiency across the region, some ISDs, like Livingston and Washtenaw, did have more than 70 percent of their students prove to be proficient on the test (74.2 and 70.9 percent, respectively).

Except for Wayne County and DPS, all the other ISDs in the region had more than 70 percent of their sixth- and eighth-graders test as proficient in reading, and post an increase from the prior year. For the sixth grade, the Livingston ISD had the highest percent of students proficient in reading (84.5%) while the Monroe ISD had the highest increase from the year prior (5.4%). For the eighth-graders, the Washtenaw ISD (82.8%) had the highest percent of students proficient in reading while the St. Clair RESA (8.3%) had the largest increase.

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As the maps show, only one ISD and DPS posted an increase in the percent of students proficient in social studies from fall 2012 to fall 2013. For the sixth-graders, DPS had a 6 percent increase in the percent of students proficient in social studies. However, DPS still had the lowest percent of students proficient, 14.8 percent. The Livingston ISD (42.5%) had the highest percent of sixth-graders proficient in social studies and the Macomb ISD (4.5%) experienced the largest decrease.

For the ninth-grade social studies MEAP exam, only the Washtenaw ISD experienced an increase in the percent of students proficient (0.4 percent); it also had the highest percent of students proficient (43.4%). The Monroe ISD experienced the largest decrease from fall 2012 to fall 2013 (7.8%), though it should be noted that the specific numbers for DPS could not be reported, according to the Michigan Department of Education, because less than 10 percent of students in the ninth grade were proficient on their social studies MEAP exam.

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All ISDs and DPS in the region showed an increase in the percent of students proficient on the eighth-grade science test. The St. Clair RESA had the highest percent increase from fall 2012 to fall 2013 (8.3%) and Washtenaw ISD had the highest percent of eighth-graders proficient (30.3%). DPS had fewer than 10 percent of its eight-graders test proficient on the science exam last fall.

Progress and problems with education scores for children in Southeast Michigan

June 9, 2014

Currently, the Michigan Legislature is considering moving the oversight of the Michigan Education Assessment Program (MEAP) testing from the Michigan Department of Education (MDE) to the Treasury Department through House Bill 5581 and Senate Bill 0945. This suggested move, as proposed by Rep. Bob Genetski (R-Saugatuck), is so a “more responsive” department can control the state’s performance testing mechanism. The lack of responsiveness Genetskialleges refers to the decision by MDE to cease using the MEAP test as the MDE’s standardized test. Rather, the MDE plans to implement the Smarter Balance Assessment, standardized tests based on the Common Core Standards. The math and language arts portions of the MEAP test were no longer supposed to be given after this past fall. The upcoming state school aid budget, however, could require schools to use MEAP tests to receive funding, if the bills pass. While the Senate bill passed, House Republicans have not passed their version as yet.

Despite this ongoing debate, the MEAP has recently indicated some progress. Here we  MEAP results from the 2013-14 school year.

In this post, we examine the MEAP results for third, fourth and fifth graders. Overall, these maps show there has been a decline in MEAP scores in at least one county at each grade level for each subject tested for, with one exception. The science scores for fifth-graders saw an increase across the seven county region this past school year. In each case we present the scores for the Intermediate School District in the county, which represents the aggregate scores for the students across the county. In addition, we present scores for Detroit Public Schools (DPS).

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Of the three grades examined in this post, third-graders experienced the least growth in MEAP proficiency from the fall 2012 to fall 2013. In math, the Washtenaw Intermediate School District (ISD) was the only one in the region to experience growth (1.3 percent). In Monroe County, the Monroe ISD had the largest decline in the percent of students proficient in math from 2012 to 2013 (4 percent), but it was Wayne County’s Regional Education Service Agency (RESA) that had the lowest percent of students proficient in math (31 percent), of the counties. The Detroit Public Schools had the lowest percent of students proficient in third grade math (14.6 percent) and third grade reading (35.3 percent).

No county in the region had an increase in the percentage of students proficient in third grade reading between fall 2012 and fall 2013. Again, the public schools in Monroe County experienced the largest decrease in the percent proficient (7.9 percent) but Wayne RESA had the lowest percent of third-grade students proficient in reading (49.2 percent).

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There were four ISDs (Livingston, Oakland, Washtenaw and Wayne), along with Detroit Public Schools, that had a decrease in the percent of fourth-graders proficient in math.  Of those, Livingston ISD had the largest decrease (3.3 percent) but it also had the highest percent of students proficient in math (59.6 percent) in the region.

All intermediate school districts, and the public schools in the City of Detroit, experienced an increase in the percent proficient in reading, with the exception of the intermediate school district in Livingston County. Livingston ISD experienced a 4.1 percent decrease. Even with the decrease, the Livingston ISD had the region’s highest percentage of students proficient in reading (80.3%), as well as in math (59.6%) and writing (80.3%). The Monroe ISD had the largest percent increase of third-graders proficient in all three subjects.

Similar to the percent changes of students proficient in math, the Livingston ISD also had the largest decrease in fourth-graders proficient in science (3.3 percent) but the highest percent of students proficient in the subject (80.3 percent). In terms of overall percent increase, Monroe County had the largest (11.8 percent)

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From fall 2012 to fall 2013, there was a decrease in the percent of students proficient in both math from fall 2012 to fall 2013  for the St. Clair RESA and DPS. St. Clair RESA had the largest decrease in students proficient from fall 2012 to fall 2013 (7.3 percent). Wayne and Oakland intermediate school districts, along with Detroit Public Schools also experienced a decrease.

For reading, the St. Clair RESA experienced a 1 percent decrease, which was the largest decrease of the counties. The Detroit Public Schools experienced a 1.4 percent decrease in the percent of fifth-graders proficient in reading though.  Overall, Livingston ISD had the highest increase in the percent students proficient in reading (2.7 percent) and the highest percentage of students proficient (85.3 percent).

For fifth-grade students in the region, all intermediate school districts experienced an increase in the percent of students proficient in science; the intermediate school districts in St. Clair and Washtenaw counties had the largest percent increase (4.8 percent). The Washtenaw ISD also had the highest percent of students proficient in science (24.7 percent).

Next week we will examine the MEAP scores for sixth through ninth graders in the region.

Bike Accident Data Show Need for More Protection

June 2, 2014

In 2013, there were 1,871 traffic accidents reported to the police that involved a bicycle in the seven counties that comprise Southeast Michigan. Here, the locations of these accidents are overlaid with previously displayed data about bicycle ridership rates for commuting that was reported to the Census Bureau. There is some overlap  between high bicycle commuting and accidents, particularly in Royal Oak and Ann Arbor, but accidents are widely distributed across the populated areas of the metro area.

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More accidents (40 percent) were in Wayne County than in the Southeast Michigan suburban counties. Wayne County and Detroit have a larger number of bicyclists on the road than many of the other locations in the region. Nearly a third (33.1 percent) of the Wayne County accidents took place in Detroit. Ann Arbor, in Washtenaw County, also has a large biking community. It was the site of two thirds of the accidents in the county; overall these accidents were 10 percent of the region’s total. Oakland and Macomb counties had the majority of their accidents in the areas of their counties that were closest to Detroit, while Monroe, Livingston and St. Clair counties experienced most of their bicycle accidents in their larger communities.

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There was an increase in bicycle accidents when the weather was warmest. Just less than a third (31 percent) occurred in July and August combined. There was a decrease in accidents on weekends (average=211) vs. weekdays (average=290).

Our second map displays the same accident information, but does so by creating a “heat map” that displays the data by increasing the hue where there is a higher concentration of accidents. This map demonstrates that areas with a high number of cyclists, such as Ann Arbor and Midtown Detroit, have higher rates of accidents, which is shown in the yellow and red hues on the map. The map also highlights a second set of areas where there are a high number of accidents. It shows that some of the Suburban areas just outside Detroit are dangerous places for bikers to navigate safely – areas such as Ferndale and Eastpointe.

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The third map shows Detroit and its immediate vicinity, allowing us to look more closely at the pattern of accidents. With the addition of information about state-regulated roads, we can see that major thoroughfares create safety hazards for cyclists, and these corridors are particularly problematic in the suburbs. The corridors of Woodward Avenue, Mound Road, Gratiot Avenue, Grand River Avenue, Telegraph Road, 8 Mile Road , Ford Road, Michigan Avenue and Fort Street each have accident clusters just beyond the Detroit city limits. The same pattern of accidents along thoroughfares is evident in Detroit proper. Again, we see that areas that connect two biking communities provide high hazards. Woodward and Grand Boulevard, which connect high-biking areas of Highland Park and Hamtramck to high-biking Midtown provides one example, but there are other areas throughout the city and its near suburbs that follow this pattern. These patterns indicate a need for cycling infrastructure that connect locations to improve safety and increase cycling.

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