Most community colleges across the country use a placement test to determine students’ readiness for college-level coursework, yet these tests are admittedly imperfect instruments. Researchers have documented significant problems stemming from overreliance on placement testing, including placement error and misdiagnosis of remediation needs. They have also described significant consequences of misplacement, which can hinder the educational progression and attainment of community college students.
Purpose/Objective/Research Question
We explore possibilities for placing community college students in mathematics courses using a holistic approach that considers measures beyond placement test scores. This includes academic background measures, such as high school GPA and math courses taken, and indicators of noncognitive constructs, such as motivation, time use, and social support.
Setting
The study draws upon administrative data from a large urban community college district in California that serves over 100,000 students each semester. The data enable us to link students’ placement testing results, survey data, background information, and transcript records.
Research Design
We first use the supplemental survey data gathered during routine placement testing to conduct predictive exercises that identify severe placement errors under existing placement practices. We then move beyond prediction and evaluate student outcomes in two colleges where noncognitive indicators were directly factored into placement algorithms.
Findings/Results
Using high school background information and noncognitive indicators to predict success reveals as many as one quarter of students may be misassigned to their math courses by status quo practices. In our subsequent analysis we find that students placed under a holistic approach that considered noncognitive indicators in addition to placement test scores performed no differently from higher scoring peers in the same course.
Conclusions/Recommendations
The findings suggest a holistic approach to mathematics course placement may improve placement accuracy and provide access to higher level mathematics courses for community college students without compromising their likelihood of success.
Get full access to this article
View all access options for this article.
References
1.
AlmeidaD. (2015). The roots of college readiness. In TierneyW. G., & DuncheonJ. (Eds.), The problem of college readiness (pp. 3—44). SUNY Press: Albany.
2.
ArmstrongW. B. (2000). The association among student success in courses, placement test scores, student background data, and instructor grading practices. Community College Journal of Research and Practice, 24(8), 681—695.
BaileyT., JeongD. W., & ChoS.-W. (2010). Referral, enrollment, and completion in developmental education sequences in community colleges. Economics of Education Review, 29(2), 255—270. http://doi.org/10.1016/j.econedurev.2009.09.002
5.
BraccoK. R., DadgarM., AustinK., KlarinB., BroekM., FinkelsteinN…., & BuglerD. (2014). Exploring the use of multiple measures for placement into college level courses: Seeking alternatives or improvements to the use of a single standardized test. San Francisco, CA: WestEd.
6.
BurdmanP. (2012). Where to begin? The evolving role of placement exams for students starting college. Boston, MA: Jobs for the Future.
7.
ChingosM. M. (2016). Instructional quality and student learning in higher education: Evidence from developmental algebra courses. The Journal of Higher Education, 87(1), 84—114.
CooperJ. (1997). Marginality, mattering, and the African American student: Creating an inclusive college environment. College Student Affairs Journal, 16(2), 15—20.
10.
CovingtonM. V. (2000). Goal theory, motivation, and school achievement: An integrative view. Annual Review of Psychology, 51, 171—200.
11.
DennisJ. M., PhinneyJ. S., & ChuatecoL. I. (2005). The role of motivation, parental support, and peer support in the academic success of ethnic minority first generation college students. Journal of College Student Development, 46(3), 223—236.
12.
Dixon RayleA., & ChungK.-Y. (2007). Revisiting first-year college students' mattering: Social support, academic stress, and the mattering experience. Journal of College Student Retention: Research, Theory and Practice, 9(1), 21—37.
13.
DixonS. K., & KurpiusS. E. R. (2008). Depression and college stress among university undergraduates: Do mattering and self-esteem make a difference?Journal of College Student Development, 49(5), 412—424.
14.
DuckworthA. L., PetersonC., MatthewsM. D., & KellyD. R. (2007). Grit: Perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92(6), 1087—1101.
15.
DuckworthA. L., & YeagerD. S. (2015). Measurement matters: Assessing personal qualities other than cognitive ability for educational purposes. Educational Researcher, 44(4), 237—251.
16.
DuncheonJ. (2015). The problem of college readiness. In TierneyW. G., & DuncheonJ. (Eds.), The problem of college readiness (pp. 3—44). Albany: SUNY Press.
17.
EcclesJ., & WigfieldA. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109—132.
18.
EhrenbergR. G., & ShermanD. R. (1987). Employment while in college, academic achievement, and postcollege outcomes: A summary of results. Journal of Human Resources, 22(1), 1.
19.
FieldsR., & ParsadB. (2012). Tests and cut scores used for student placement in postsecondary education: Fall 2011. Washington, DC: National Assessment Governing Board.
20.
FongK., & MelguizoT. (2015). Utilizing additional measures to buffer against students' lack of math confidence and improve placement accuracy in developmental math. Paper presented at the annual meeting of the American Educational Research Association, Chicago, IL.
21.
FranceM. K., & FinneyS. J. (2010). Conceptualization and utility of university mattering: A construct validity study. Measurement and Evaluation in Counseling and Development, 43(1), 48—65.
22.
GerlaughK., ThompsonL., BoylanH., & DavisH. (2007). National study of developmental education II: Baseline data for community colleges. Research in Developmental Education, 20(4), 1—4.
23.
GossettB. J., CuyjexM. J., & CockrielI. (1996). African Americans' and Non-African Americans' sense of mattering and marginality at public, predominantly white institutions. Equity and Excellence in Education, 29(3), 37—42.
24.
HornL., NevillS., & GriffithJ. (2006). Profile of undergraduates in US postsecondary education institutions, 2003-04: With a special analysis of community college students. Statistical Analysis Report. NCES 2006-184. National Center for Education Statistics.
25.
HughesK. L., & Scott-ClaytonJ. (2011). Assessing developmental assessment in community colleges. Community College Review, 39(4), 327—351.
26.
HusmanJ., & LensW. (1999). The role of the future in student motivation. Educational Psychologist, 34, 113—125.
27.
JenkinsD., JaggarsS. S., & RoksaJ. (2009). Promoting gatekeeper course success among community college students needing remediation: Findings and recommendations from a Virginia Study. New York, NY: Community College Research Center. Retrieved from http://eric.ed.gov/?id=ED507824
28.
KaneM. T. (2001). Current concerns in validity theory. Journal of Educational Measurement, 38(4), 319—342.
29.
KaneM. T. (2006). Validation. In BrennanR. L. (Ed.), Educational Measurement (4th ed., pp. 17—64). Westport, CT: ACE/Praeger Publishers.
30.
MarkleR., Olivera-AguilarM., JacksonR., NoethR., & RobbinsS. (2013). Examining evidence of reliability, validity and fairness for the SuccessNavigator assessment (Research Report No. RR-13-12). Princeton, NJ: Educational Testing Service. http://dx.doi.org/10.1002/j.2333-8504.2013.tb02319.x
31.
MarshallS. K. (2001). Do I matter? Construct validation of adolescents' perceived mattering to parents and friends. Journal of Adolescence, 24(4), 473—490.
32.
MarwickJ. D. (2004). Charting a path to success: The association between institutional placement policies and the academic success of Latino students. Community College Journal of Research and Practice, 28(3), 263—280.
33.
MatternK. D., & PackmanS. (2009). Predictive validity of ACCUPLACER scores for course placement: A meta-analysis (Research Report No. 2009-2). New York, NY: College Board.
34.
MelguizoT., BosJ., NgoF., MillsN., & PratherG. (2016). Using a regression discontinuity design to estimate the impact of placement decisions in developmental math. Research in Higher Education, 57(2), 123—151.
35.
MichaelsJ. W., & MietheT. D. (1989). Academic effort and college grades. Social Forces, 68(1), 309.
36.
MillerR. B., & BrickmanS. J.A model of future-oriented motivation and self-regulation. Educational Psychology Review, 16, 9—33.
37.
National Center for Public Policy and Higher Education & Southern Regional Education Board. (2010). Beyond the rhetoric: Improving college readiness through coherent state policy. Atlanta, GA: NCPPHE. Retrieved from http://publications.sreb.org/2010/Beyond%20the%20Rhetoric.pdf
38.
NgoF., & KwonW. (2015). Using multiple measures to make math placement decisions: Implications for access and success in community colleges. Research in Higher Education, 56(5), 442—470.
39.
NgoF., & MelguizoT. (2016). How can placement policy improve math remediation outcomes? Evidence from community college experimentation. Educational Evaluation and Policy Analysis, 38(1), 171—196.
40.
NobleJ. P., & SawyerR. L. (2004). Is high school GPA better than admission test scores for predicting academic success in college?College and University Journal, 79(4), 17—22.
41.
NoonanB. M., SedlacekW. E., & VeerasamyS. (2005). Employing noncognitive variables in admitting and advising community college students. Community College Journal of Research and Practice, 29(6), 463—469.
42.
PajaresF., & RaynerS. (2001). Self-beliefs and school success: Self-efficacy, self-concept, and school achievement. Perception, 239—266
43.
PascarellaE. T., EdisonM. I., NoraA., HagedornL. S., & TerenziniP. T. (1998). Does work inhibit cognitive development during College?Educational Evaluation and Policy Analysis, 20(2), 75.
PintrichP. (2003). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667—686.
PorceaS. F., AllenJ., RobbinsS., & PhelpsR. P. (2010). Predictors of long-term enrollment and degree outcomes for community college students: Integrating academic, psychosocial, socio-demographic, and situational factors. The Journal of Higher Education, 81(6), 750—778.
48.
RauW., & DurandA. (2000). The academic ethic and college grades: Does hard work help students to “make the grade”?Sociology of Education, 73(1), 19.
49.
RikoonS., LiebtagT., Olivera-AguilarM., RobbinsS., & JacksonT. (2014). A pilot study of holistic assessment and course placement in community college: Findings and recommendations. Retrieved from https://www.ets.org/Media/Research/pdf/RM-14-10.pdf
50.
RobbinsS., AllenJ., CasillasA., PetersonC. H., & LeH. (2006). Unraveling the differential effects of motivational and skills, social, and self-management measures from traditional predictors of college outcomes. Journal of Educational Psychology, 98(3), 598—616.
51.
RoderickM., NagaokaJ., & CocaV. (2009). College readiness for all: The challenge for urban high schools. The Future of Children, 19(1), 185—210.
52.
RosenbergM., & McCulloughB. C. (1981). Mattering: Inferred significance and mental health among adolescents. Research in Community and Mental Health, 2, 163—182.
53.
SawyerR. (1996). Decision theory models for validating course placement tests. Journal of Educational Measurement, 33(3), 271—290.
54.
SawyerR. (2007). Indicators of usefulness of test scores. Applied Measurement in Education, 20(3), 255—271.
55.
SedlacekW. E. (2004). Beyond the big test: Noncognitive assessment in higher education. San Francisco, CA: Jossey-Bass.
56.
SchlossbergN. K. (1989). Marginality and mattering: Key issues in building community. New Directions for Student Services, 1989(48), 5—15.
57.
Scott-ClaytonJ. E. (2012). Do high-stakes placement exams predict college success? (Working Paper No. 41). New York, NY: Community College Research Center. Retrieved from http://academiccommons.columbia.edu/catalog/ac:146482
58.
Scott-ClaytonJ. E., CrostaP. M., & BelfieldC. R. (2014). Improving the targeting of treatment: Evidence From college remediation. Educational Evaluation and Policy Analysis, 36(3), 371—393. http://doi.org/10.3102/0162373713517935
SternbergR. J., GaboraL., & BonneyC. R. (2012). Introduction to the special issue on college and university admissions. Educational Psychologist, 47(1), 1—4.
61.
StinebricknerR., & StinebricknerT. R. (2003). Working during school and academic performance. Journal of Labor Economics, 21(2), 473—491.
62.
StinebricknerR., & StinebricknerT. R. (2004). Time-use and college outcomes. Journal of Econometrics, 121(1–2), 243—269.
63.
TovarE., SimonM. A., & LeeH. B. (2009). Development and validation of the college mattering inventory with diverse urban college students. Measurement and Evaluation in Counseling and Development, 42(3), 154—178.
