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Part IV - Rethinking Higher Education Admissions

Published online by Cambridge University Press:  09 January 2020

By
Cathy Wendler
Edited by
María Elena Oliveri  and
Cathy Wendler
María Elena Oliveri
Affiliation:
Educational Testing Service, Princeton, New Jersey
Cathy Wendler
Affiliation:
Educational Testing Service, Princeton, New Jersey
Get access

Summary

The three chapters in this part move beyond current concepts of higher education admissions. They present alternatives as to how the admissions process might be conceived and maintained. Taking into account threats related to fairness, diversity, and access, the chapters propose new frameworks for conceptualizing what the role of higher education should be and methods for rethinking the assessments used as part of admissions.

Keywords

Part IV overview
Type
Chapter
Information
Higher Education Admissions Practices
An International Perspective
 , pp. 303 - 375
Publisher: Cambridge University Press
Print publication year: 2020

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References

Barrett, D. & Zapotosky, M. (2019, March 12). FBI accuses wealthy parents, including celebrities, in college-entrance bribery scheme. Washington Post. Retrieved from www.washingtonpost.com/world/national-security/fbi-accuses-wealthy-parents-including-celebrities-in-college-entrance-bribery-scheme/2019/03/12/d91c9942-44d1-11e9-8aab-95b8d80a1e4f_story.html?noredirect=on&utm_term=.01cd84ecbce3.Google Scholar
Korn, M., Levitz, J., & Ailworth, E. (2019, March 13). Federal prosecutors charge dozens in college admissions cheating scheme. Wall Street Journal. Retrieved from www.wsj.com/articles/federal-prosecutors-charge-dozens-in-broad-college-admissions-fraud-scheme-11552403149.Google Scholar
Taylor, K. (2019, March 13). Fallout from college admissions scandal: Arrests, damage control and a scramble for answers. New York Times. Retrieved from www.nytimes.com/2019/03/13/us/college-admissions-probe.html.Google Scholar

References

Aeppel, T. (2015, March 13). It took the telephone 75 years to do what Angry Birds did in 35 days. But what does that mean? [Blog post]. Retrieved from https://blogs.wsj.com/economics/2015/03/13/it-took-the-telephone-75-years-to-do-what-angry-birds-did-in-35-days-but-what-does-that-mean/.Google Scholar
Allen, J., & Robbins, S. B. (2008). Prediction of college major persistence based on vocational interests, academic preparation, and first-year academic performance. Research in Higher Education, 49, 62–79. https://doi.org/10.1007/s11162-007-9064-5.Google Scholar
Allen, J., & Robbins, S. B. (2010). Effects of interest–major congruence, motivation, and academic performance on timely degree attainment. Journal of Counseling Psychology, 57, 23. https://doi.org/10.1037/a0017267.Google Scholar
Asendorpf, J. B., & Wilpers, S. (1998). Personality effects on social relationships. Journal of Personality and Social Psychology, 74, 1531–1544. https://doi.org/10.1037/0022-3514.74.6.1531.CrossRefGoogle Scholar
Ashton, M. C., Lee, K., Perugini, M., Szarota, P., de Vries, R. E., Di Blas, L., Boies, K., & De Raad, B. (2004). A six-factor structure of personality-descriptive adjectives: Solutions from psycholexical studies in seven languages. Journal of Personality and Social Psychology, 86, 356–366. https://doi.org/10.1037/0022-3514.86.2.356.Google Scholar
Autor, D. H. & Price, B. (2013). The changing task composition of the US labor market: An update of Autor, Levy, and Murnane (2003). Retrieved from https://economics.mit.edu/files/11600.Google Scholar
Baller, S., Dutta, S., & Lanvin, B. (Eds.). (2016). The global information technology report 2016. Retrieved from www.weforum.org/reports/the-global-information-technology-report-2016.Google Scholar
Bolton, L. R., Becker, L. K., & Barber, L. K. (2010). Big Five trait predictors of differential counterproductive work behavior dimensions. Personality and Individual Differences, 49, 537–541. https://doi.org/10.1016/j.paid.2010.03.047.Google Scholar
Bowman, N. A., & Denson, N. (2014). A missing piece of the departure puzzle: Student-institution fit and intent to persist. Research in Higher Education, 55, 123–142. https://doi.org/10.1007/s11162–013-9320-9.Google Scholar
Brough, P., Timms, C., O’Driscoll, M. P., Kalliuth, T., Siu, O-L, Sit, C., & Lo, D. (2014). Work–life balance: A longitudinal evaluation of a new measure across Australia and New Zealand workers. International Journal of Human Resource Management, 25, 2724–2744. https://doi.org/10.1080/09585192.2014.899262.Google Scholar
Camara, W., O’Connor, R., Mattern, K., & Hanson, M. A. (2015). Beyond academics: A holistic framework for enhancing education and workplace success (ACT Research Report Series 2015 No. 4). Iowa City, IA: ACT Inc.Google Scholar
Campbell, J. P. (1990). Modeling the performance prediction problem in industrial and organizational psychology. In Dunnette, M. D. & Hough, L. M. (Eds.). Handbook of Industrial and Organizational Psychology (pp. 687–732). Palo Alto, CA: Consulting Psychologists Press, Inc.Google Scholar
Carter, S. D. (2002). Matching training methods and factors of cognitive ability: A means to improve training outcomes. Human Resource Development Quarterly, 13, 71–88.Google Scholar
Chen, A., & Yao, X. (2015). Socialization tactics, fit perceptions, and college student adjustment. Journal of Career Assessment, 23, 615–629. https://doi.org/10.1177/1069072714553082.Google Scholar
Clinedinst, M., & Koranteng, A. (2017). 2017 State of college admission. Retrieved from www.nacacnet.org/globalassets/documents/publications/research/soca17final.pdf.Google Scholar
Colquitt, J. A., LePine, J. A., & Noe, R. A. (2000). Toward an integrative theory of training motivation: A meta-analytic path analysis of 20 years of research. Journal of Applied Psychology, 85, 678–707. https://doi.org/10.1037/0021-9010.85.5.678.Google Scholar
Common Core State Standards. (2010). Common core state standards for English language arts and literacy in history/social studies, science, and technical subjects. Washington, DC: National Governors Association Center for Best Practices & Council of Chief State School Officers.Google Scholar
Conley, D. T. (2007). Toward a more comprehensive conception of college readiness. Eugene, OR: Educational Policy Improvement Center.Google Scholar
Conley, D. T. (2008). Rethinking college readiness. New Directions for Higher Education, 144, 3–13. https://doi.org/10.1002/he.321.CrossRefGoogle Scholar
Cullinane, C., & Montacute, R. (2017). Life lessons: Improving essential life skills for young people. Retrieved from www.suttontrust.com/research-paper/life-lessons/.Google Scholar
de Vries, A., de Vries, R. E., & Born, M. Ph. (2011). Broad versus narrow traits: Conscientiousness and honesty–humility as predictors of academic criteria. European Journal of Personality, 25, 336–348. https://doi.org/10.1002/per.795.CrossRefGoogle Scholar
Facione, P. A. (1991). Using the California critical thinking skills test in research, evaluation, and assessment. Retrieved from https://files.eric.ed.gov/fulltext/ED337498.pdfGoogle Scholar
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019.Google Scholar
Grove, A. (2018). What are holistic admissions? At selective colleges, admission is based on more than grades and test scores. Retrieved from www.thoughtco.com/what-are-holistic-admissions-788426.Google Scholar
Gu, M., & Magaziner, J. (2018). The Gaokao: History, reform, and rising international significance of China’s national college entrance examination. Retrieved from https://wenr.wes.org/2016/05/the-gaokao-history-reform-and-international-significance-of-chinas-national-college-entrance-examination.Google Scholar
Hanushek, E. A., & Woessmann, L. (2008). The role of cognitive skills in economic development. Journal of Economic Literature, 46, 607–668.CrossRefGoogle Scholar
Hart Research Associates. (2010). Raising the bar: Employers’ views on college learning in the wake of the economic downturn. Retrieved from www.aacu.org/sites/default/files/files/LEAP/2009_EmployerSurvey.pdfGoogle Scholar
Hong, L., & Page, S. E. (2004). Groups of diverse problem solvers can outperform groups of high-ability problem solvers. Proceedings of the National Academy of Sciences of the United States of America, 101(46), 16385–16389. https://doi.org/10.1073/pnas.0403723101.Google Scholar
Huffman, W. H., & Huffman, A. H. (2012). Beyond basic study skills: The use of technology for success in college. Computers in Human Behavior, 28, 583–590. https://doi.org/10.1016/j.chb.2011.11.004.CrossRefGoogle Scholar
Jackson, N. E. (2005). Are university students’ component reading skills related to their text comprehension and academic achievement? Learning and Individual Differences, 15, 113–139. https://doi.org/10.1016/j.lindif.2004.11.001.Google Scholar
Jonassen, D. H., & Kim, B. (2010). Arguing to learn and learning to argue: Design justifications and guidelines. Educational Technology Research and Development, 58, 439–457. https://doi.org/10.1007/s11423–009-9143-8.Google Scholar
Judge, T. A., Bono, J. E., Ilies, R., & Gerhardt, M. W. (2002). Personality and leadership: a qualitative and quantitative review. Journal of Applied Psychology, 87, 765–780. https://doi.org/10.1037/0021-9010.87.4.765.Google Scholar
Judge, T. A., Rodell, J. B., Klinger, R. L., Simon, L. S., & Crawford, E. R. (2013). Hierarchical representations of the five-factor model of personality in predicting job performance: Integrating three organizing frameworks with two theoretical perspectives. Journal of Applied Psychology, 98, 875–925. https://doi.org/10.1037/a0033901.Google Scholar
Kalsbeek, D., Sandlin, M., & Sedlacek, W. (2013). Employing noncognitive variables to improve admissions, and increase student diversity and retention. Strategic Enrollment Management Quarterly, 1, 132–50. https://doi.org/10.1002/sem3.20016.Google Scholar
Koen, J., Klehe, U.-C., Van Vianen, A. E. M., Zikic, J., & Nauta, A. (2010). Job search strategies and reemployment quality: The impact of career adaptability. Journal of Vocational Behavior, 77, 126–139. https://doi.org/10.1016/j.jvb.2010.02.004.Google Scholar
Kristof-Brown, A. L., Zimmerman, R. D., & Johnson, E. C. (2005). Consequences of individuals’ fit at work: A meta-analysis of person-job, person-organization, person-group, and person-supervisor fit. Personnel Psychology, 58, 28–342. https://doi.org/10.1111/j.1744-6570.2005.00672.x.Google Scholar
Lanvin, B. & Evans, P. (2018). The global talent competitiveness index 2018. Fontainebleau: INSEAD, Adecco, and HCLI.Google Scholar
Latino, C. A., Way, J., Colbow, A., Bouwers, S., Casillas, A., & McKinniss, T. (2017). The Development of Behavioral Performance Level Descriptors (ACT Research Report Series 2017 No. 7). Iowa City, IA: ACT Inc.Google Scholar
Le, H., Robbins, S. B., & Westrick, P. (2014). Predicting student enrollment and persistence in college STEM fields using an expanded P-E Fit framework: A large-scale multilevel study. Journal of Applied Psychology, 99, 915–947. https://doi.org/10.1037/a0035998.CrossRefGoogle ScholarPubMed
Lee, K., Ashton, M. C., & de Vries, R. E. (2005). Predicting workplace delinquency and integrity with the HEXACO and five-factor models of personality structure. Human Performance, 18, 179–197. https://doi.org/10.1207/s15327043hup1802_4.Google Scholar
Lent, R. W., Brown, S. D., & Gore, P. A. (1997). Discriminant and predictive validity of academic self-concept, academic self-efficacy, and mathematics-specific self-efficacy. Journal of Counseling Psychology, 44, 307–315. https://doi.org/10.1037/0022-0167.44.3.307.Google Scholar
Lent, R. W., Taveira, M., Pinto, J. C., Silva, A. D., Blanco, A., Faria, S., & Goncalves, A. M. (2014). Social cognitive predictors of well-being in African college students. Journal of Vocational Behavior, 84, 266–272. https://doi.org/10.1016/j.jvb.2014.01.007.CrossRefGoogle Scholar
Lievens, F., Ones, D. S., & Dilchert, S. (2009). Personality scales validities increase throughout medical school. Journal of Applied Psychology, 94, 1514–1535. https://doi.org/10.1037/a0016137.CrossRefGoogle ScholarPubMed
Lindqvist, E., & Vestman, R. (2011). The labor market returns to cognitive and noncognitive ability: Evidence from the Swedish enlistment. American Economic Journal: Applied Economics, 3(1), 101–128. https://doi.org/10.1257/app.3.1.101.Google Scholar
Lounsbury, J. W., Saudargas, R. A., Gibson, L. W., & Leong, F. T. (2005). An investigation of broad and narrow personality traits in relation to general and domain-specific life satisfaction of college students. Research in Higher Education, 46, 707–729. https://doi.org/10.1007/s11162–004-4140-6.Google Scholar
McAbee, S. T., Oswald, F. L., & Connelly, B. S. (2014). Bifactor models of personality and college student performance: A broad versus narrow view. European Journal of Personality, 28, 604–619. https://doi.org/10.1002/per.1975.CrossRefGoogle Scholar
Mattern, K. D., Burrus, J., Camara, W. J., O’Connor, R., Gambrell, J., Hanson, M. A., Casillas, A., & Bobek, B. (2014). Broadening the definition of College and Career Readiness: A Holistic Approach. Iowa City, IA: ACT, Inc.Google Scholar
Mattern, K. D. & Patterson, B. F. (2011). The validity of the SAT for predicting fourth-year grades: 2006 SAT validity sample (College Board Statistical Report 2011-7). New York, NY: The College Board.Google Scholar
Morgeson, F. P., Reider, M. H., & Campion, M. A. (2005). Selecting individuals in team settings: The importance of social skills, personality characteristics, and teamwork knowledge. Personnel Psychology, 58, 583–611. https://doi.org/10.1111/j.1744-6570.2005.655.x.Google Scholar
Mount, M. K., Barrick, M. R., & Stewart, G. L. (1998). Five-factor model of personality and performance in jobs involving interpersonal interactions. Human Performance, 11, 145–165. https://doi.org/10.1080/08959285.1998.9668029.CrossRefGoogle Scholar
National Research Council. (2013). Education for life and work: Developing transferable knowledge and skills in the 21st century. Washington, DC: National Academies Press.Google Scholar
No Child Left Behind Act of 2001. (2002). P.L. 107-110, 20 U.S.C. § 6319.Google Scholar
Nye, C. D., Su, R., Rounds, J., & Drasgow, F. (2012). Vocational interests and performance a quantitative summary of over 60 years of research. Perspectives on Psychological Science, 7, 384–403. https://doi.org/10.1177/1745691612449021.Google Scholar
Nye, C. D., Su, R., Rounds, J., & Drasgow, F. (2017). Interest congruence and performance: Revisiting recent meta-analytic findings. Journal of Vocational Behavior, 98, 138–151. https://doi.org/10.1016/j.jvb.2016.11.002.Google Scholar
Oh, I.-S., Guay, R. P., Kim, K., Harold, C. M., Lee, J.-H., Heo, C.-G., & Shin, K.-H. (2014). Fit happens globally: A meta-analytic comparison of the relationships of person-environment fit dimensions with work attitudes and performance across East Asia, Europe, and North America. Personnel Psychology, 67, 99–52. https://doi.org/10.1111/peps.12026.Google Scholar
Okun, M. A., & Finch, J. F. (1998). The big five personality dimensions and the process of institutional departure. Contemporary Educational Psychology, 23, 233–256. https://doi.org/10.1006/ceps.1996.0974.Google Scholar
Oliveri, M. E., & Markle, R. (2017 ). Continuing a culture of evidence: Expanding skills in higher education. (Research Report No. RR-17-09). Princeton, NJ: Educational Testing Service. https://doi.org/10.1002/ets2.12137.Google Scholar
Organ, D. W., & Ryan, K. (1995). A meta-analytic review of attitudinal and dispositional predictors of organizational citizenship behavior. Personnel Psychology, 48, 775–802.Google Scholar
Organisation for Economic Co-operation and Development (2013). OECD skills outlook 2013: First results from the survey of adult skills. Retrieved from www.oecd-ilibrary.org/education/oecd-skills-outlook-2013_9789264204256-enGoogle Scholar
Organisation for Economic Co-operation and Development (2014). OECD employment outlook. https://doi.org/10.1787/empl_outlook-2014-en.CrossRefGoogle Scholar
Organisation for Economic Co-operation and Development (2016). Global competency for an inclusive world. Retrieved from http://repositorio.minedu.gob.pe/handle/123456789/4561.Google Scholar
Pace, R. C. (1990). Personalized and depersonalized conflict in small group discussions: An examination of differentiation. Small Group Research, 21, 79–96. https://doi.org/10.1177/1046496490211006.Google Scholar
Page, S. E. (2008). The difference: How the power of diversity creates better groups, firms, schools, and societies. Princeton, NJ: Princeton University Press.Google Scholar
Paunonen, S. V., & Ashton, M. C. (2013). On the prediction of academic performance with personality traits: A replication study. Journal of Research in Personality, 47, 778–781. https://doi.org/10.1016/j.jrp.2013.08.003.Google Scholar
Perez, T., Cromley, J. G., & Kaplan, A. (2014). The role of identity development, values, and costs in college STEM retention. Journal of Educational Psychology, 106, 315–329. https://doi.org/10.1037/a0034027.Google Scholar
Peterson, C. H., Casillas, A., & Robbins, S. B. (2006). The student readiness inventory and the Big Five: Examining social desirability and college academic performance. Personality and Individual Differences, 41, 663–673. https://doi.org/10.1016/j.paid.2006.03.006.CrossRefGoogle Scholar
Pleitz, J. D., MacDougall, A. E., Terry, R. A., Buckley, M. R., & Campbell, N. J. (2015). Discrepancy between expectations and experiences on college student retention. Journal of College Student Retention: Research, Theory & Practice, 17, 88–104. https://doi.org/10.1177/1521025115571252.Google Scholar
Poropat, A. E. (2009). A meta-analysis of the five-factor model of personality and academic performance. Psychological Bulletin, 135, 322–338. https://doi.org/10.1037/a0014996.Google Scholar
Raelin, J. A., Bailey, M. B., Hamann, J., Pendleton, L. K., Reisberg, R., & Whitman, D. L. (2015). The role of work experience and self-efficacy in STEM student retention. Journal on Excellence in College Teaching, 26(4), 29–50.Google Scholar
Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130, 261–288. https://doi.org/10.1037/0033-2909.130.2.261.Google Scholar
Roberts, B. W., Kuncel, N. R., Shiner, R., Caspi, A., & Goldberg, L. R. (2007). The power of personality: The comparative validity of personality traits, socioeconomic status, and cognitive ability for predicting important life outcomes. Perspectives on Psychological Science, 2, 313–345. https://doi.org/10.1111/j.1745-6916.2007.00047.x.Google Scholar
Roberts, R. D., Martin, J. E., & Olaru, G. (2015). A Rosetta Stone for noncognitive skills: Understanding, assessing, and enhancing noncognitive skills in primary and secondary education. Retrieved from www.proexam.org/images/resources/A_Rosetta_Stone_for_Noncognitive_Skills.pdfGoogle Scholar
Roth, P. L., BeVier, C. A., Switzer, F. S. III, & Schippmann, J. S. (1996). Meta-analyzing the relationship between grades and job performance. Journal of Applied Psychology, 81, 548–556. https://doi.org/10.1037/0021-9010.81.5.548.Google Scholar
Sackett, P. R., & Walmsley, P. T. (2014). Which personality attributes are most important in the workplace? Perspectives on Psychological Science, 9, 538–551. https://doi.org/10.1177/1745691614543972.Google Scholar
Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124, 262–274. https://doi.org/10.1037/0033-2909.124.2.262.CrossRefGoogle Scholar
Schmidt, F. L., & Hunter, J. E. (2004). General mental ability in the world of work: Occupational attainment and job performance. Journal of Personality and Social Psychology, 86, 162–173. https://doi.org/10.1037/0022-3514.86.1.162.CrossRefGoogle ScholarPubMed
Schmitt, N., Keeney, J., Oswald, F. L., Pleskac, T. J., Billington, A. Q., Sinha, R., & Zorzie, M. (2009). Prediction of 4-year college student performance using cognitive and noncognitive predictors and the impact on demographic status of admitted students. Journal of Applied Psychology, 94, 1479–1497. https://doi.org/10.1037/a0016810.Google Scholar
Schoenbach, R., Greenleaf, C., & Murphy, L. (2012). Reading for understanding: How reading apprenticeship improves disciplinary learning in secondary and college classrooms (2nd ed.). San Francisco, CA: Jossey-Bass.Google Scholar
Schwab, K. (2016). The Fourth Industrial Revolution. New York, NY: Crown Business.Google Scholar
Simons, T., & Peterson, R. (2000). Task conflict and relationship conflict in top management teams: The pivotal role of intragroup trust. Journal of Applied Psychology, 85, 102–111. https://doi.org/10.1037/0021-9010.85.1.102.Google Scholar
Soria, K. M., & Stubblefield, R. (2015). Knowing me, knowing you: Building strengths awareness, belonging, and persistence in higher education. Journal of College Student Retention: Research, Theory & Practice, 17, 351–372. https://doi.org/10.1177/1521025115575914.Google Scholar
Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133, 65–94. https://doi.org/10.1037/0033-2909.133.1.65.CrossRefGoogle ScholarPubMed
Thomas, D. (2014). Factors that influence college completion intention of undergraduate students. Asia-Pacific Educational Research, 23, 225–235. https://doi.org/10.1007/s40299-013-0099-4.Google Scholar
Van Iddekinge, C. H., Putka, D. J., & Campbell, J. P. (2011). Reconsidering vocational interests for personnel selection: The validity of an interest-based selection test in relation to job knowledge, job performance, and continuance intentions. Journal of Applied Psychology, 9, 13–33. https://doi.org/10.1037/a0021193.Google Scholar
von Stumm, S., Hell, B., & Chamorro-Premuzic, T. (2011). The hungry mind: Intellectual curiosity is the third pillar of academic performance. Perspectives on Psychological Science, 6, 574–588. https://doi.org/10.1177/1745691611421204.CrossRefGoogle ScholarPubMed
World Economic Forum (2016). The future of jobs: Employment, skills and workforce strategy for the fourth industrial revolution. Retrieved from www3.weforum.org/docs/WEF_Future_of_Jobs.pdf.Google Scholar
Wright, S. L., Jenkins-Guarnieri, M. A., & Murdock, J. L. (2013). Career development among first-year college students: College self-efficacy, student persistence, and academic success. Journal of Career Development, 40, 292–310.CrossRefGoogle Scholar
Yu, K. Y. T. (2016). Inter-relationships among different types of person–environment fit and job satisfaction. Applied Psychology: An International Review, 65, 38–65. https://doi.org/10.1111/apps.12035.Google Scholar
Yue, H. & Fu, X. (2017). Rethinking graduation and time to degree: A fresh perspective. Research in Higher Education, 58, 184–213. https://doi.org/10.1007/s11162–016-9420-4.Google Scholar

References

Berkelaar, M. (2014). Package “lpSolve.” Retrieved from https://cran.r-project.org/web/packages/lpSolve/lpSolve.pdf.Google Scholar
Blatter, A., & Glynn, J. (2016, November). Recognizing distance traveled in selective college admissions. Presented at the annual meeting of the Association for the Study of Higher Education, Columbus, Ohio.Google Scholar
Cohen, D. (2004, February 13). In Malaysia, the end of quotas. Chronicle of Higher Education. Retrieved from www.chronicle.com/article/In-Malaysia-the-End-of-Quotas/10391.Google Scholar
Durán, G., & Wolf-Yadlin, R. (2011). A mathematical programming approach to applicant selection for a degree program based on affirmative action. Interfaces, 41, 278–288. https://doi.org/10.1287/inte.1100.0542.Google Scholar
Ingels, S., Planty, M., & Bozick, R. (2005). A profile of the American high school senior in 2004: A first look-initial results from the first follow-up of the education longitudinal study of 2002 (NCES 2006-348). Washington, DC: US Department of Education, NCES.Google Scholar
Koljatic, M., & Silva, M. (2013). Opening a side-gate: Engaging the excluded in Chilean higher education through test-blind admission. Studies in Higher Education, 38, 1427–1441. https://doi.org/10.1080/03075079.2011.623299.Google Scholar
Kolman, B., & Beck, R. E. (1995). Elementary linear programming with applications (2nd ed.). San Diego, CA: Academic Press.Google Scholar
Kreiter, C. D. (2002). The use of constrained optimization to facilitate admission decisions. Academic Medicine, 77, 148–151. https://doi.org/10.1097/00001888-200202000-00011.Google Scholar
Kreiter, C. D., Stansfield, B., James, P. A., & Solow, C. (2003). A model for diversity in admissions: A review of issues and methods and an experimental approach. Teaching and Learning in Medicine: An International Journal, 15, 116–122. https://doi.org/10.1207/S15328015TLM1502_08.Google Scholar
Lloyd, M. (2004, February 13). In Brazil, a new debate over color. Chronicle of Higher Education. Retrieved from www.chronicle.com/article/In-Brazil-a-New-Debate-Over/4343.Google Scholar
lp_solve reference guide. (n.d.). Retrieved from http://web.mit.edu/lpsolve/doc/.Google Scholar
McMurtrie, B. (2004, February 13). The quota quandary. Chronicle of Higher Education. Retrieved from www.chronicle.com/article/The-Quota-Quandary/35480.Google Scholar
Overland, M. A. (2004, February 13). In India, almost everyone wants to be special. Chronicle of Higher Education. Retrieved from www.chronicle.com/article/In-India-Almost-Everyone/3612.Google Scholar
Pashley, P. J., & Thornton, A. E. (1999). Crafting an Incoming law school class: Preliminary results (LSAC Research Report 99-01). Newtown, PA: Law School Admission Council.Google Scholar
Pashley, P. J., Thornton, A. E., & Duffy, J. R. (2005). Access and diversity in law school admissions. In Camara, W. J. & Kimmel, E. W. (Eds.). Choosing students: Higher education admissions tools for the 21st century (pp. 231–249). Mahwah, NJ: Erlbaum.Google Scholar
Sarafraz, Z., Sarafraz, H., Sayeh, M., & Nicklow, J. (2015). Student yield maximization using genetic algorithm on a predictive enrollment neural network model. Procedia Computer Science, 61, 341–348. https://doi.org/10.1016/j.procs.2015.09.154.Google Scholar
Schmitt, C. M. (2009). Documentation for the restricted-use NCES-Barron’s admissions competiveness index data files (NCES 2010-330). Washington, DC: NCES.Google Scholar
Somers, P., Morosini, M., Pan, M., & Cofer, J. E. (2013). Brazil’s radical approach to expanding access for underrepresented college students. In Meyer, H.-D., St. John, E. P., Chankseliani, M., & Uribe, L. (Eds.). Fairness in access to higher education in a global perspective, pp. 203–221. Rotterdam: Sense. https://doi.org/10.1007/978-94-6209-230-3_12.Google Scholar
Walczak, S., & Sincich, T. (1999). A comparative analysis of regression and neural networks for university admissions. Information Sciences, 119, 1–20. https://doi.org/10.1016/S0020-0255(99)00057-2.Google Scholar
Zhang, R. (2010). Media, litigation, and regional discrimination in college admission in China. Chinese Education and Society, 43(4), 60–74. https://doi.org/10.2753/CED1061-1932430406Google Scholar
Zwick, R. (2017). Who gets in? Strategies for fair and effective college admissions. Cambridge, MA: Harvard University Press. https://doi.org/10.4159/9780674977648Google Scholar
Zwick, R., Blatter, A., Ye, L., & Isham, S. (2018). Using constrained optimization with an index of admission obstacles to increase the diversity of college classes. Manuscript submitted for publication.Google Scholar
Zwick, R., Ye, L., & Isham, S. (2016). Crafting a college class using constrained optimization. Paper presented at the annual meeting of the Association for the Study of Higher Education, Columbus, Ohio.Google Scholar
Zwick, R., Ye, L., & Isham, S. (2019). Using constrained optimization to increase the representation of students from low-income neighborhoods. Applied Measurement in Education, 281–297, https://doi.org/10.1080/08957347.2019.1660346.Google Scholar

References

Altbach, P. G., Reisberg, L., & Rumbley, L. E. (2009). Trends in global higher education: Tracking an academic revolution. Report prepared for the UNESCO 2009 World Conference on Higher Education. Paris: United Nations Educational, Scientific and Culture Organization. Retrieved from http://unesdoc.unesco.org/images/0018/001831/183168e.pdf.Google Scholar
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (2014). Standards for educational and psychological testing. Washington, DC: American Educational Research Association.Google Scholar
Bachman, L. F., & Palmer, A. S. (2010). Language assessment in practice: Developing language assessments and justifying their use the real world. Oxford: Oxford University Press.Google Scholar
Bennett, R. E. (2010). Cognitively based assessment of, for, and as learning: A preliminary theory of action for summative and formative assessment. Measurement: Interdisciplinary Research and Perspectives, 8, 70–91. https://doi.org/10.1080/15366367.2010.508686.Google Scholar
Bereiter, C., & Scardamalia, M. (2012). What will it mean to be an educated person in mid-21st century? Princeton, NJ: The Gordon Commission on the Future of Assessment in Education. Retrieved from https://gordoncommissionblog.wordpress.com/commissioned-papers/what-will-it-mean-to-be-an-educated-person-in-mid-21st-century/.Google Scholar
Braun, H. I., & Jones, D. H. (1984). Use of empirical Bayes methods in the study of the validity of academic predictors of graduate school performance (ETS RR-84-48). Princeton, NJ: Educational Testing Service. https://doi.org/10.1002/j.2330-8516.1984.tb00074.x.Google Scholar
Breland, H. M., Maxey, J., Gernand, R., Cumming, T., & Trapani, C. (2002). Trends in college admission 2000: A report of a national survey of undergraduate admissions policies, practices, and procedures. Princeton, NJ: ACT, Inc.; Association for Institutional Research; The College Board; Educational Testing Service; and National Association for College Admission Counseling. Retrieved from www.ets.org/research/policy_research_reports/publications/report/2002/cnrr.Google Scholar
Burstein, J., Chodorow, M., & Leacock, C. (2004). Automated essay evaluation: The Criterion Online service. AI Magazine, 25(3), 27–36.Google Scholar
Burstein, J., Elliot, N., Beigman Klebanov, B., Madnani, M., Napolitano, D., Schwartz, M., Houghton, P., & Molloy, H. (2018). Writing Mentor™: Writing progress using self-regulated writing support. Journal of Writing Analytics, 2, 285–313. Retrieved from https://wac.colostate.edu/docs/jwa/vol2/bursteinetal.pdf.Google Scholar
Chen, X. (2016). Remedial coursetaking at U.S. public 2- and 4-year institutions: Scope, experiences, and outcomes (NCES Report No. 2016-405). Washington, DC: National Center for Education Statistics. Retrieved from https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2016405.Google Scholar
Cisco Systems Inc. (2010). Cisco packet tracer data sheet. Retrieved from www.cisco.com/c/dam/en_us/training-events/netacad/course_catalog/docs/Cisco_PacketTracer_DS.pdf.Google Scholar
Cleary, T. A. (1968). Test bias: Prediction of grades of Negro and White students in integrated colleges. Journal of Educational Measurement, 5, 115–124. https://doi.org/10.1111/j.1745-3984.1968.tb00613.x.Google Scholar
Coley, R. J., Goodman, M. J., & Sands, A. M. (2015). America’s skills challenge: Millennials and the future. Princeton, NJ: Educational Testing Service. Retrieved from www.ets.org/s/research/30079/asc-millennials-and-the-future.pdf.Google Scholar
College Board. (n.d.). AP central. Retrieved from https://apcentral.collegeboard.org/.Google Scholar
Council of Writing Program Administrators, National Council of Teachers of English, & National Writing Project. (2011). Framework for success in postsecondary writing. Retrieved from www.nwp.org/img/resources/framework_for_success.pdf.Google Scholar
Dorans, N. J., & Cook, L. L. (Eds.). (2016). Fairness in educational assessment and measurement. New York, NY: Routledge. https://doi.org/10.4324/9781315774527.Google Scholar
Elliot, N. (2016). A theory of ethics for writing assessment. Journal of Writing Assessment, 9(1). Retrieved from http://journalofwritingassessment.org/article.php?article=98.Google Scholar
Ercikan, K., & Pellegrino, J. W. (Eds.). (2017). Validation of score meaning for the next generation of assessments: The use of response processes. New York, NY: Taylor & Francis. https://doi.org/10.4324/9781315708591.Google Scholar
Feuer, M. (2013). Validity issues in international large-scale assessments: “Truth” and “consequences.” In Chatterji, M. (Ed.). Validity and test use: An international dialogue on educational assessment, accountability and equity (pp. 197–216). Bingley: Emerald Group.Google Scholar
Frezzo, D. C., Behrens, J. T., & Mislevy, R. J. (2009). Design patterns for learning and assessment: Facilitating the introduction of a complex simulation-based learning environment into a community of instructors. Journal of Science Education and Technology, 19, 105–114. https://doi.org/10.1007/s10956–009-9192-0.Google Scholar
Glaser, R., & Nitko, A. (1970). Measurement in learning and instruction. Pittsburgh, PA: Learning Research and Development Center, University of Pittsburgh.Google Scholar
Haertel, E. H., & Herman, J. L. (2005). A historical perspective on validity arguments for accountability testing. In Herman, J. L. & Haertel, E. H. (Eds.). Uses and misuses of data for educational accountability and improvement. The 104th Yearbook of the National Society for the Study of Education, Part II (pp. 1–34). Malden, MA: Blackwell. https://doi.org/10.1111/j.1744-7984.2005.00023.x.Google Scholar
Harackiewicz, J. M., Canning, E. A., Tibbetts, Y., Priniski, S. J., & Hyde, J. S. (2016). Closing achievement gaps with a utility-value intervention: Disentangling race and social class. Journal of Personality and Social Psychology, 111, 745-765. http://dx.doi.org/10.1037/pspp0000075.Google Scholar
Hart Research Associates. (2010). Raising the bar: Employers’ views on college learning in the wake of the economic downturn. Washington, DC: Association of American Colleges and Universities. Retrieved from www.aacu.org/sites/default/files/files/LEAP/2009_EmployerSurvey.pdf.Google Scholar
Hart-Davidson, B., & Meeks, R. (forthcoming). Behavioral indicators of writing improvement: Feedback analytics for peer learning. In Kelly-Riley, D. and Elliot, N. (Eds.). Improving outcomes: Disciplinary Writing, local assessment, and the aim of fairness. New York, NY: Modern Language Association.Google Scholar
Hesse, F., Care, E., Buder, J., Sassenberg, K., & Griffin, P. (2015). A framework for teachable collaborative problem solving skills. In Griffin, P. & Care, E. (Eds.). Assessment and teaching of 21st century skills: Methods and approach. Dordrecht: Springer.Google Scholar
Holland, P. W. (2008, March). The first four generations of test theory. Paper presented at the Association of Test Publishers on Innovations in Testing, Dallas, Texas.Google Scholar
Hussar, W. J., & Bailey, T. M. (2017). Projections of education statistics to 2025 (NCES Report No. 2017-019). Washington, DC: U.S. Department of Education, National Center for Education Statistics. Retrieved from https://files.eric.ed.gov/fulltext/ED576296.pdf.Google Scholar
Idaho State Board of Education. (2015). Governing policies and procedures: Section III: postsecondary affairs, subsection S: Remedial education. Retrieved from https://boardofed.idaho.gov/board-policies-rules/board-policies/higher-education-affairs-section-iii/iii-s-development-and-remedial-education/.Google Scholar
International Test Commission. (2018). ITC guidelines for the large-scale assessment of linguistically and culturally diverse populations. Retrieved from www.intestcom.org/files/guideline_diverse_populations.pdf.Google Scholar
Kane, M. T. (2006). Validation. In Brennan, R. J. (Ed.). Educational measurement (4th ed.) ( pp. 18–64). Westport, CT: Praeger.Google Scholar
Kane, M. T., & Mislevy, R. J. (2017). Validating score interpretation based on response processes. In Ercikan, K. & Pellegrino, J. W. (Eds.). Validation of score meaning for the next generation of assessments: The use of response processes (pp. 11–24). New York, NY: Routledge. https://doi.org/10.4324/9781315708591-2.Google Scholar
Kelly, P., Moores, J., & Moogan, Y. (2012). Culture shock and higher education performance: Implications for teaching. Higher Education Quarterly, 66, 24–46. https://doi.org/10.1111/j.1468-2273.2011.00505.x.Google Scholar
Klobucar, A., Elliot, N., Deess, P., Rudniy, O., & Joshi, K. (2013). Automated scoring in context: Rapid assessment for placed students. Assessing Writing, 18(1), 62–84. https://doi.org/10.1016/j.asw.2012.10.001.Google Scholar
Mislevy, R. J. (2018). Sociocognitive foundations of educational measurement. London: Routledge. https://doi.org/10.4324/9781315871691.Google Scholar
Mislevy, R. J., Almond, R. G., & Lukas, J. (2004). A brief introduction to evidence-centered design (CSE Technical Report No. 632). Los Angeles, CA: The National Center for Research on Evaluation, Standards, and Student Testing (CRESST), Center for Studies in Education, UCLA.Google Scholar
Mislevy, R. J., & Elliot, N. (forthcoming). Ethics, psychometrics, and writing assessment: A conceptual model. In Duffy, J. & Agnew, L. P. (Eds.). Rewriting Plato’s legacy: Ethics, rhetoric, and writing studies. Logan, UT: Utah State University Press.Google Scholar
Mislevy, R. J., & Haertel, G. D. (2006). Implications of evidence‐centered design for educational testing. Educational Measurement: Issues and Practice, 25(4), 6–20. https://doi.org/10.1111/j.1745-3992.2006.00075.x.Google Scholar
Myford, C. M., & Mislevy, R. J. (1995). Monitoring and improving a portfolio assessment system (CSE Technical Report No. 402). Los Angeles, CA: The National Center for Research on Evaluation, Standards, and Student Testing (CRESST), Center for Studies in Education, UCLA.Google Scholar
National Research Council. 2012. Education for life and work: Developing transferable knowledge and skills in the 21st century. Washington, DC: The National Academies Press. https://doi.org/10.17226/13398.Google Scholar
Novick, M. R., & Petersen, N. S. (1976). Towards equalizing educational and employment opportunity. Journal of Educational Measurement, 13, 77–88. https://doi.org/10.1111/j.1745-3984.1976.tb00183.x.Google Scholar
The Occupational Information Network Resource Center. (2017). O*NET 22.2 Database [Data file and code book]. Retrieved from www.onetcenter.org/database.html.Google Scholar
Oliveri, M. E. (2018, April). Kitchen Design: A research prototype to assess communication at work. In Troitschanskaia, O. (Chair), Assessing student learning outcomes in higher education. Symposium conducted at the meeting of the American Educational Research Association, New York, NY.Google Scholar
Oliveri, M. E., & Lawless, R. R. (2018). The validity of inferences from locally developed assessments administered globally. (ETS RR-18-35). Princeton, NJ: Educational Testing Service. https://doi.org/10.1002/ets2.12221.Google Scholar
Oliveri, M. E., Lawless, R. R., & Mislevy, R. J. (2019). Using evidence-centered design to support the development of culturally and linguistically sensitive collaborative problem-solving assessments. International Journal of Testing, 19(1), 1–31. https://doi: 10.1080/15305058.2018.1543308.Google Scholar
Oliveri, M. E., Lawless, R. R., Molloy, H. (2017). A literature review of collaborative problem solving for college and workforce readiness. (ETS RR-17-06; ETS GRE RR-17-03). Princeton, NJ: Educational Testing Service. https://doi.org/10.1002/ets2.12133.Google Scholar
Oliveri, M. E., & Markle, R. (2017). Continuing a culture of evidence: Expanding skills in higher education (ETS RR-17-09). Princeton, NJ: Educational Testing Service. https://onlinelibrary.wiley.com/doi/pdf/10.1002/ets2.12137.Google Scholar
Oliveri, M. E., McCaffrey, D., Ezzo, C., & Holtzman, S. (2017). A multilevel factor analysis of third-party evaluations of noncognitive constructs used in admissions decision-making. Applied Measurement in Education, 30, 297–313. http://dx.doi.org/10.1080/08957347.2017.1353989.CrossRefGoogle Scholar
Oliveri, M. E., & McCulla, L. (forthcoming). Using the occupational network database to assess and improve English language communication for the workplace (Research Report Series). Princeton, NJ: Educational Testing Service.Google Scholar
Oliveri, M. E., Rutkowski, D., & Rutkowski, L. (2018). Bridging validity and evaluation to match international large-scale assessment claims and country aims (ETS RR-18-27). Princeton, NJ: Educational Testing Service. https://doi.org/10.1002/ets2.12214.Google Scholar
Oliveri, M. E. & Wendler, C. (2017, April). Enhancing the validity argument of assessments: Identifying, understanding, and mitigating unintended consequences of test use. Professional development workshop presented at American Educational Research Association, San Antonio, Texas.Google Scholar
O’Sullivan, B., & Weir, C. J. (2011). Test development and validation. In O’Sullivan, B. (Ed.). Language testing: Theories and practices (pp. 13–32). Basingstoke: Palgrave Macmillan.Google Scholar
Pane, J. F., Steiner, E. D., Baird, M. D., Hamilton, L. S., & Pane, J. D. (2017). Informing progress: Insights on personalized learning implementation and effects. Santa Monica, CA: RAND Corporation. Retrieved from http://rand.org/t/RR2042.Google Scholar
Riconscente, M. M., Mislevy, R. J., & Corrigan, S. (2016). Evidence-centered design. In Lane, S., Raymond, M. R., & Haladyna, T. M. (Eds.). Handbook of test development (2nd ed.) (pp. 40–63). New York, NY: Routledge.Google Scholar
Shermis, M. D., & Burstein, J. (Eds.). (2013). Handbook of automated essay evaluation: Current applications and new directions. New York, NY: Routledge. https://doi.org/10.4324/9780203122761.Google Scholar
Shermis, M. D., Burstein, J., Elliot, N., Miel, S., & Foltz, P. W. (2016). Automated writing evaluation: An expanding body of knowledge. In McArthur, C. A., Graham, S., & Fitzgerald, J. (Eds.). Handbook of writing research (2nd ed.) (pp. 395–409). New York, NY: Guilford.Google Scholar
Snyder, T. D., de Brey, C., & Dillow, S. A. (2019). Digest of education statistics 2017 (NCES 2018-070). Washington, DC: National Center for Education Statistics, Institute of Education Sciences, US Department of Education. Retrieved from https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2018070.Google Scholar
Toulmin, S. E. (2003). The uses of argument. Cambridge: Cambridge University Press. (Original work published 1958). Retrieved from https://doi.org/10.1017/CBO9780511840005.Google Scholar
Weir, C. (2005). Language testing and validation: An evidence-based approach. Basingstoke: Palgrave Macmillan. https://doi.org/10.1057/9780230514577.Google Scholar
Zwick, R. (2017). Who gets in? Strategies for fair and effective college admissions. Cambridge, MA: Harvard University Press. https://doi.org/10.4159/9780674977648.Google Scholar

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