The Impact of Highly Capable Elementary Education on High Schooler’s Success

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Introduction

Ability grouping is defined as a logical means of organizing a student body with diverse academic skills (Gamoran et al, 1995), or a practice that places students into classrooms or small groups based on an initial assessment of their levels of readiness or ability (Kulik, 1992). Despite ongoing debate and extensive criticism, ability grouping remains a common practice in American education. Yet there is considerable belief and significant  research which indicates that the top 5-10% of students are dragged down by heterogeneous grouping and experience boredom from the lack of challenge (Steenburg et al, 2016). Additionally, it is generally conceded that, if high standardized test scores (SAT) are an important priority, it is better to sequester the top group of students. That is, ability grouping benefits the higher achieving students but may be detrimental to the lower ability groups of students. This is one of the main arguments against ability grouping and is due in large part to practices like assigning the more qualified and more exciting teachers to teach the higher level classes, while less experienced teachers, lower expectations, less teaching effort, and larger classes generally accompany lower tracks (Gamoran, 1993). As early as the 1920’s, studies have been exploring the impact of ability grouping in education following a number of different models (Kulik, 1992). In the Peninsula School District, a Highly Capable program has been implemented, placing top performing 4th and 5th graders in self-contained, specialized classes at Voyager, Discovery, and Minter Creek elementary schools. Those students are then classified as Highly Capable, and their progress can be tracked all the way to graduation. This program has existed since 2007 and has already graduated its first few classes of Highly Capable students. Today, the program has expanded, and high performing students can be referred by their teachers as early as first grade for the full CogAT Highly Capable test. Later, all students are screened for the program in second grade. Although they are not on an official separate track, Highly Capable students will be able to continue higher-ability learning either in a self-contained Language Arts class at Kopachuck and Key Peninsula Middle Schools in 6th grade or in clustered in Language Arts and Social Studies at Goodman Middle School and Harbor Ridge Middle School. This extends the time they are sequestered from the non-grouped students and allows them access to more accelerated pathways, including higher level and AP classes in high school. Not only do they  not have to waste instructional time waiting for their peers to catch up, this higher level track is expected to benefit these students by putting them on track to graduate and be prepared for college, with the most important factors to admission generally assumed to be GPA and standardized test scores. Yet, because there is no evidence to support this presumption, I was motivated to research this particular program to determine a correlation between participation in the Highly Capable program in elementary school and success in high school. In other words, does grouping students into a highly capable cohort actually benefit them in the long run? For our purposes, student success will be defined as achievement of significantly higher than average GPAs and SAT scores. This study should be conducted in order to test the efficacy of Highly Capable tracking and to clearly delineate the benefits or drawbacks that may be associated with ability grouping in the Peninsula School District. In Washington State, this research is limited, because each school district has a unique Highly Capable Program that follows general state guidelines. My research will be filling this gap in research on this particular program by comparing Highly Capable members of the class of 2019 to their non-tracked counterparts.

Literature Review

Ability grouping in schools has longer been the subject of heated debate. Many opponents have claimed that ability grouping does not produce academic gains for gifted students and impedes the learning of typical students (Matthews et al, 2013). In his 1990 best-evidence synthesis on tracking in secondary schools, Robert Slavin of Johns Hopkins University concluded that, when research on tracking compares homogeneous groups with heterogeneous groups, tracking holds no advantage. When research on tracking means comparing high-ability to low-ability groups, tracking yields positive outcomes for the high-ability groups and negative outcomes for low-ability groups. Trying to find the reasons for this latter outcome, Slavin concluded that the two groups differed on so many variables — initial achievement differences, motivation, socioeconomic status, material, quality of teaching, etc. — that deciding what produces the difference is nearly impossible (Slavin, 1990). For this reason, research outlined in this paper will focus on correlation, not causation. Oakes also noted the inequity of teacher and instructional quality for students grouped into low-track classrooms, though this likely is an implementation issue rather than a feature of ability grouping itself (Oakes, 1987). Much of the literature outlined here compares classes only on the basis of being grouped or not. But analyses have shown that the effects of each grouping program depends heavily on its features. Programs that adjust the curriculum to ability level more substantially have larger effects on learning, in which students from accelerated classes are reported to outperform those of the same age and IQ by almost 1 full year on achievement tests (Kulik, 1992).

Thomas Hoffer of Northern Illinois University set out to analyze the effects of tracking in the fall 1992 issue of Educational Evaluation and Policy Analysis. Unlike most research, Hoffer’s study compared tracked and non-tracked schools, not classes or within-class groups. Another difference between Hoffer’s work and most other research is that Hoffer’s seventh-grade students, as part of a larger study, were given tests composed of mathematics and science items taken from the National Assessment of Educational Progress. Although Hoffer does not describe these items in detail, it is likely that they test a wider range of achievement than the typical commercial standardized test. Hoffer controlled statistically for gender, ethnicity, and socioeconomic status. As with many other studies, Hoffer found a small positive effect for students in the high groups and larger negative effects for students in the low groups. Because there were more students in high groups than in low, the overall effect was essentially zero. “Ability grouping in seventh-and eighth-grade mathematics and science is clearly not an optimal arrangement compared with the non-grouped alternative, for low-group students are significant losers.” Conceding that these negative results might be offset, that low-ability students lose because of their lower status, Hoffer speculates that if there were a way to prevent the assignment of low and high status, grouping could be used to benefit higher achieving students without disadvantages lower-grouped students (Hoffer, 1992).

Similarly, in the American Journal of Education, prominent education sociologist and author of many scholarly articles on the subject, Adam Gamoran PhD, investigates whether ability grouping can be implemented to achieve high-quality instruction in low-ability classes using data from studies of 8th and 9th grade English classes. Examples of schools with apparently effective instruction in low tracks were characterized by (1) high expectations by teachers, (2) extra effort by teachers to cultivate discussions in class, and (3) no system of assigning weak or inexperienced teachers to lower tracks (Gamoran, 1993). By avoiding these practices, it may be possible to implement ability grouping and highly capable education without hindering lower track students.

One Austrian study from the British Journal of Educational Psychology comparing 186 students from 8 classes, 4 on a gifted track and 4 regular, reported a decrease in boredom levels in math over time after entering higher ability classes, supporting the theory that gifted classes provide more appropriate levels of challenge (Preckel et al, 2010). There is significant research showing that gifted students are more likely to drop out (Lajoie et al, 1981; Renzulli & Park, 2002; NELS:88), although there are many other reasons or factors for gifted students to drop out. Two computerized studies using the National Education Longitudinal Study of 1988 (NELS:88) and the Second Follow-up Dropout Questionnaire indicated that (a) many gifted students left school because they were failing school, didn’t like school, had a job, or were pregnant, (b) most parents whose gifted child dropped out of school were not actively involved in their child’s decision, (c) many gifted students who dropped out of school participated less in extracurricular activities, (d) few gifted students who dropped out of school had plans to return to school, (e) gifted students who dropped out of school had higher self-concepts, (f)  many gifted students who dropped out of school were from low SES families and racial minority groups, (g) gifted students who dropped out of school had parents with low levels of education, (h) gifted students who dropped out of school had used marijuana more than gifted students who completed school, and (i) dropout behavior for gifted students was significantly related to students’ educational aspirations, pregnancy or child-rearing, gender, father’s highest level of education, and mother’s highest level of education (Renzulli & Park, 2002). Additionally, the heavily cited report, The Silent Epidemic: Perspectives of High School Dropouts, found that nearly 50 percent of 470 dropouts surveyed said they left school because their classes were boring and not relevant to their lives or career aspirations (Bridgeland et al, 2006). While some students drop out because of significant academic challenges, most dropouts are students who could have, and believe they could have, succeeded in school. If Highly Capable education curbs this effect, there might be reason to recommend its continued or furthered implementation. Besides this effect, The Classroom Practices Survey conducted by The National Research Center on the Gifted and Talented to determine the extent to which gifted and talented students receive differentiated education in regular classrooms across the United States found that teachers outside ability grouped classrooms “make only minor modifications in the regular curriculum to meet the needs of the gifted students,” (Archambault et al, 1993). This result holds for public school teachers, for private school teachers, and for teachers in schools with high concentrations of ethnic minorities as well as to teachers and classrooms in various regions of the country and in rural, urban, and suburban communities. Teachers who make provisions for the gifted are likely to assign them advanced readings, independent projects, enrichment worksheets, and reports of various kinds. However, these modifications are not used widely. The survey also revealed that the regular classroom services provided to gifted students in schools with formal gifted programs are similar to those provided in schools without formal programs (Archambault et al, 1993). If not placed directly into a gifted program, high ability students are unlikely to receive any kind of differentiated education, suggesting that ability grouping may have net positive results as long as the implementation issues for the lower tracked group are avoided.

In “Achievement Effects of Ability Grouping in secondary schools: A Best Evidence Synthesis from the National Center on Effective Secondary Schools, the Office of Educational Research and Improvement, in Washington DC,” findings indicate that between-class ability grouping, and ability grouping by subjects, had no effect on student achievement. Their evidence of zero effects again contradicts my hypothesis that highly capable students have higher levels of student success and earlier conclusions that showed benefits for highly capable and gifted students, and detriments for low level students.

In their article in the Economics of Education Review, researchers Betts and Shkolnik from the Department of Economics, University of California, San Diego, and the National Opinion Research Center, respectively, found that “A school policy of grouping students by ability has little effect on average math achievement growth,” (Betts & Shkolnik, 1999). Like earlier research, this paper also finds little or no differential effects of grouping for high-achieving, average, or low-achieving students.

In “What One Hundred Years of Research Says About the Effects of Ability Grouping and Acceleration on K–12 Students’ Academic Achievement” researchers synthesize data from 13 ability grouping meta-analyses which show that overall, students benefited from within-class grouping, cross-grade subject grouping, and grouping for the gifted, but did not benefit from between-class grouping. (Steenburg-Hu et al, 2016). Acceleration appeared to have a positive, moderate, and statistically significant impact on students’ academic achievement. Overall, these findings provide support for using ability grouping to meet the learning needs of students.

Methodology

In order to determine the impact of this particular program, I conducted a case study, surveying a group of Highly Capable seniors at Peninsula High School as well as a control group made up of seniors who did not participate in the program. With this information, I did correlational research to determine the relationship between Highly Capable participation, GPAs, and test scores. In order to prevent bias and make the study more accurate, participants were selected from a list using a random number generator, then I emailed each student a link to the anonymous online survey with an explanation of the study that participation is anonymous and optional. The survey (Appendix A) could be taken privately at any time, so there was no pressure to participate, no personal information disclosed, and no time constraints placed on participants, minimizing rushing. 15 PHS  seniors, 7 of which were Highly Capable, completed the survey for this study. With the results outlined in Table A, I conducted three T-Tests for significance to determine correlation between Highly Capable involvement and (1) GPA, (2) SAT score, and (3) total AP courses.

Results

 I had hypothesized that PHS students of the class of 2019 identified in elementary school as highly capable will have more academic success in high school and be more likely to pursue traditional higher education. For the purposes of my research academic success is defined as higher than average GPA and SAT scores. The survey yielded results outlined in Table A. Unexpectedly, the cumulative mean GPA for Highly Capable students was only 3.311, compared to an average of 3.573 for non-accelerated students. After conducting a T-Test for significance, the resulting p-values is 0.53, meaning that not only does the data not provide statistically significant support for my hypothesis, but in some respects refutes it. Student number 7 of the Highly Capable group is a strong outlier, pulling the mean GPA down. Without student 7, the Highly Capable group has an average GPA of 3.663, slightly above the non-accelerated group, but falls to 3.311 with the addition of student 7. Either way, there is no correlation between Highly Capable participation and elevated GPA. SAT score results had even less correlation, as p=-0.23. The average Highly Capable SAT score is 1273, compared to an average of 1194 for non-accelerated students. Still, both groups are well above the national average of 1068. Highly Capable students are expected to follow an accelerated track throughout their secondary education, and difficult AP courses may account for lower GPAs. Results somewhat support this idea. While Highly Capable students averaged 6.8 AP classes total, non-grouped students had an average of only 4 AP classes. The T-Test indicated no strong correlation with a p-value of 0.25.

Discussion of Results

 The results of this study suggest that the initial hypothesis was wrong. There is no statistically significant evidence to suggest that being a part of the PSD Highly Capable Program had any effect on students’ test scores or GPAs. With a p-value of .53, there is no confirmed correlation between participation and student success.

 The implications of these findings is somewhat unclear. If there are truly no effects from Highly Capable education, should resources be pulled from these programs? This study and further research may influence the schools district’s decision to further or reduce the use of ability grouping in the future.

I have concluded that the experimental results did not yield completely reliable results because of some of my limitations. I had a small sample size of 15 students, making my statistical test for significance somewhat unreliable. A larger sample size would have produced much more accurate evidence to support or refute my hypothesis. There is also some nonresponse bias from those who chose not to participate in the survey, meaning that the data may be skewed based on who chose to respond. Additionally, although the surveys were anonymous, responses may be inaccurate in an attempt to make the participant look better on paper. Finally, I had an outlier in the Highly Capable group who had a very low GPA and test scores and who did not plan to graduate, meaning that my results may be skewed.

I originally planned to, instead of just a survey, obtain student data from the school district to analyze the impact on students in the highly capable program with more participants by expanding the study to both high schools in the district and longitudinally, by looking at data from the previous two graduating classes as well. Again, I would compare results to a control group of students not in the ability-grouped Highly Capable cohort. My plan to protect the privacy of the students was to have personal information blacked out by somebody with authority to view it, and to only use the data pertinent to my study. However, because this is all protected under the Family Education Rights and Privacy Act (FERPA), it needed to be voluntarily supplied by the students themselves, leading me to conduct the survey.

Further research should be done on this topic. While I did a small survey of students in the same school and graduating class to compare students who participated in the Highly Capable program in elementary school, placing them on a more advanced track through middle school and high school and account for more factors like gender, ethnicity, socioeconomic status, and relative age that might have a greater impact on student results.

Conclusion

The relationship between Highly Capable elementary education and success in high school was not proven by my experiment. Part of this can be attributed to the limitations, but also the style of the experiment. However, with more research, time, and participants, the researcher may be able to find a strong correlation between ability grouped students and elevated success in secondary education.

My study impacted the field by guiding future researchers on the appropriate procedures, both in the positive and the negative. The survey I conducted and distributed to research participants gathered of information that can go into calculating the relationship. However, for future studies, age, gender, race, ethnicity, and socioeconomic status should be evaluated to determine any correlation.    

References

  • Archambault, F. A., Jr., Westberg, K. L., Brown, S. W., Hallmark, B. W., Emmons, C. L., & Zhang, W. (1993). Regular classroom practices with gifted students: Results of a national survey of classroom teachers (Research Monograph 93102). Storrs: University of Connecticut, The National Research Center on the Gifted and Talented.
  • BERNHARDT, P. E. (2014). Making Decisions About Academic Trajectories: A Qualitative Study of Teachers’ Course Recommendation Practices. American Secondary Education, 42(2), 33–50. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=96548183&site=ehost-live
  • Betts, Julian R., and Jamie L. Shkolnik. “The Effects of Ability Grouping on Student Achievement and Resource Allocation in Secondary Schools.” Economics of Education Review, Pergamon, 19 Oct. 1999, econweb.ucsd.edu/~jbetts/Pub/A23%20Betts%20Shkolnik%20EER%20 2000%20Ability%20Grouping.pdf.
  • Catsambis, S., Mulkey, L., Buttaro, A., Steelman, L., & Koch, P. (2012). Examining Gender Differences in Ability Group Placement at the Onset of Schooling: The Role of Skills, Behaviors, and Teacher Evaluations. Journal of Educational Research, 105(1), 8–20. https://doi.org/10.1080/00220671.2010.514779
  • Gamoran, Adam. (1993). Alternative Uses of Ability Grouping in Secondary Schools: Can We Bring High-Quality Instruction to Low-Ability Classes?. American Journal of Education – AMER J EDUC. 102. 10.1086/444056.
  • Gamoran, Adam & Nystrand, Martin & Berends, Mark & Lepore, Paul. (1995). A Organizational Analysis of the Effects of Ability Grouping. American Educational Research Journal – AMER EDUC RES J. 32. 10.2307/1163331.
  • Grouping students into ability-based sets holds back less able pupils. (2018). Education Journal, (335), 8. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=a9h& AN=128789650&site=ehost-live
  • Highly Capable Program. (2018). Retrieved from https://psd401.net/highly-capable- program/
  • Hoffer, T. (1992). Middle School Ability Grouping and Student Achievement in Science and Mathematics. Educational Evaluation and Policy Analysis, 14(3), 205-227. Retrieved from http://www.jstor.org/stable/1164409
  • Kulik, J.A. (1992). An analysis of the research ability grouping: Historical and contemporary perspectives. Storrs, CT: National Research Center on the Gifted and Talented.
  • Matthews, M. S., Ritchotte, J. A., & McBee, M. T. (2013). Effects of schoolwide cluster grouping and within-class ability grouping on elementary school students’ academic achievement growth. High Ability Studies, 24(2), 81–97. https://doi.org/10.1080/13598139.2013.846251
  • Oakes, J. (1987). Tracking in Secondary Schools: A Contextual Perspective. Educational Psychologist, 22(2), 129. https://doi.org/10.1207/s15326985ep2202_3
  • Preckel, F., Götz, T., & Frenzel, A. (2010). Ability grouping of gifted students: Effects on academic self-concept and boredom. British Journal of Educational Psychology, 80(3), 451–472. https://doi.org/10.1348/000709909X480716
  • Renzulli, J. S., & Park, S. (2002). Giftedness and high school dropouts: Personal, family, and school-related factors (RM02168). Storrs: University of Connecticut, The National Research Center on the Gifted and Talented.
  • Rogers, K. B. (1991). The relationship of grouping practices to the education of the gifted and talented learner (RBDM9102). Storrs: University of Connecticut, The National Research Center on the Gifted and Talented.
  • Slavin, R. E. (1990). ACHIEVEMENT EFFECTS OF ABILITY GROUPING IN SECONDARY SCHOOLS: A BEST-EVIDENCE SYNTHESIS. National Center on Effective Secondary Schools, 22(2), 109. https://doi.org/10.1207/s15326985ep2202_2
  • Steenbergen-Hu, S., Makel, M. C., & Olszewski-Kubilius, P. (2016). What One Hundred Years of Research Says About the Effects of Ability Grouping and Acceleration on K–12 Students’ Academic Achievement. Review of Educational Research, 86(4), 849–899. Retrieved from https://doi.org/10.3102/0034654316675417
  • United States Department of Education. National Center for Education Statistics. National Education Longitudinal Study, 1988. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2006-01-18. https://doi.org/10.3886/ICPSR09389.v1

Appendix

Figure A: Survey

Are you graduating from Peninsula High School in 2019? *

Yes

No, not class of 2019

No, other graduating from another high school

No, not projected to graduate

Other:__

Gender

Male

Female

Prefer not to say

Other:__

Cumulative GPA (unweighted)

Your answer __

SAT Score

Your answer __

Number of AP Courses Taken PER YEAR *

0

1

2

3

4

5

6

7

8

9th Grade

10th Grade

11th Grade

12th Grade

How many AP classes total?

Your answer __

Are you or did you ever participate in Running Start?

No

Yes

Other:

How many college credits have you/will you earn from your time in running start?

Your answer

What School Did You Attend in 4th/5th grade?

Your answer

Were you in a WA State Highly Capable Cohort in Elementary School? *

Yes, both 4th and 5th grade

Yes, 5th only

No

Not Sure

Other:

What are your plans after high school/graduation? *

4 year Private University

4 year Public University

Community College

Technical College

Trade School

Apprenticeship

Workforce

Other:

Table A: Survey Results

Are you graduating from Peninsula High School in 2019?

Gender

Cumulative GPA (unweighted)

SAT Score

Number of AP Courses [9th Grade]

Number of AP Courses [10th Grade]

Number of AP Courses [11th Grade]

Number of AP Courses [12th Grade]

AP classes total?

Running Start?

College credits earned

What School Did You Attend in 4th/5th grade?

WA State Highly Capable Cohort

Plans after high school/graduation?

Yes!

Female

3.7

1290

1

2

0

0

3

Minter Creek Elementary

Yes, both 4th and 5th grade

4 year Private University

Yes!

Female

3.845

1320

0

3

4

3

10

Minter Creek

Yes, both 4th and 5th grade

4 year Private University

Yes!

Male

3.443

1310

1

2

3

1

7

Minter Creek Elementary

Yes, both 4th and 5th grade

4 year Public University

Yes!

Male

3

1160

1

2

0

2

5

Yes

2

Minter Creek Elementary School

Yes, both 4th and 5th grade

Apprenticeship, Workforce

Yes!

Female

4

1460

1

3

4

4

12

No

0

4th: Purdy 5th: Minter

Yes, 5th only

4 year Private University

Yes!

Male

3.987

1420

0

2

3

4

9

No

0

Minter Creek

Yes, 5th only

4 year Public University

No, not projected to graduate, Dropping out and getting my GED

Male

1.2

950

1

0

1

0

2

No

0

Minter Creek

Yes, both 4th and 5th grade

Full time job

Yes!

Male

3.262

1410

0

0

2

4

6

No

0

Harris Elementary School

No

4 year Private University

Yes!

Male

3.93

1270

1

2

3

3

9

No

0

St. Nicholas Catholic School

Not Sure

4 year Public University

Yes!

Male

3

0

0

0

0

No

Mullinex/purdy

Not Sure

Apprenticeship, Workforce

Yes!

Female

3.9

1050

0

0

2

1

3

No

Purdy elem

No

Community College

Yes!

Female

3

1010

0

0

0

0

0

No

Mint Valley

No

4 year Public University

Yes!

Female

3.741

1160

0

1

2

2

5

No

0

Purdy

No

4 year Public University

Yes!

Female

3.949

1350

0

1

3

3

7

No

Purdy

No

4 year Private University

Yes!

Female

3.8

1110

1

1

0

0

2

Yes

Notsure.Will be getting my Associate’s degree

Purdy Elementary

No

Gap year then Art School

Figure A:

Figure B:Figure C:Figure D:

Figure E:

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