Aggarwal, R., Grantcharov, T., Krishna Moorthy, K., Hance, J., & Darzi, A. (2006). A competency-based virtual reality training curriculum for the acquisition of laparoscopic psychomotor skill. The American Journal of Surgery, 191(1), 128–133.CrossRefGoogle ScholarPubMed

Aguinis, H., Henle, C. A., & Beaty, J. C., Jr. (2001). Virtual reality technology: A new tool for personal selection. International Journal of Selection and Assessment, 9, 70–83.CrossRefGoogle Scholar

American Educational Research Association, American Psychological Association, National Council on Measurement in Education, & Joint Committee on Standards for Educational and Psychological Testing. (2014). Standards for educational and psychological testing. Washington, DC: AERA.Google Scholar

Arthur, W., Glaze, R. M., Villado, A. J., & Taylor, J. E. (2010). The magnitude and extent of cheating and response distortion effects on unproctored Internet-based tests of cognitive ability and personality. International Journal of Selection and Assessment, 18, 1–16.Google Scholar

Back, M. D., Stopfer, J. M., Vazire, S., Gaddis, S., Schmukle, S. C., Egloff, B., & Gosling, S. D. (2010). Facebook profiles reflect actual personality, not self-idealization. Psychological Science, 21, 372–374.CrossRefGoogle Scholar

Barrick, M. R., & Mount, M. K. (1991). The big five personality dimensions and job performance: A meta‐analysis. Personnel Psychology, 44, 1–26.CrossRefGoogle Scholar

Bartram, D. (2011a). Scalar equivalence of OPQ32: Big Five profiles of 31 countries. Journal of Cross-Cultural Psychology, 44(1), 61–83.Google Scholar

Bartram, D. (2011b). Contributions of the EFPA standing committee on tests and testing to standards and good practice. European Psychologist, 16, 149–159.CrossRefGoogle Scholar

Benartzi, S. (2015). The smarter screen. New York: Penguin Random House.Google Scholar

Bennett, G. K., Seashore, H. G., & Wesman, A. G. (1974). DAT: differential aptitude test. New York: The Psychological Corporation.Google Scholar

Bergman, M. E., & Jean, V. A. (2016). Where have all the “workers” gone? A critical analysis of the unrepresentativeness of our samples relative to the labor market in the industrial-organizational psychology literature. Industrial and Organizational Psychology, 9, 84–113.CrossRefGoogle Scholar

Bideau, B., Kulpa, R., Vignais, N., Brault, S., Multon, F., & Craig, C. (2010). Using virtual reality to analyze sports performance. IEEE Computer Graphics and Applications, 30(2), 14–21.Google Scholar

Bono, J. E., & Judge, T. A. (2004). Personality and transformational and transactional leadership: A meta-analysis. Journal of Applied Psychology, 89(5), 901–910.CrossRefGoogle ScholarPubMed

Boyce, T. S., Conway, J. S., & Caputo, P. M. (2014). ADEPT-15 technical documentation: Development and validation of Aon Hewitt’s Personality Model and Adaptive Employee Test (ADEPT-15). New York: Aon Hewitt.Google Scholar

Boyce, A. S., Corbet, C. E., & Adler, S. (2013). Simulations in the selection context: Considerations, challenges, and opportunities. In Fetzer, M. S. & Tuzinski, K. A. (Eds.), Simulations for employee selection. New York: Springer.Google Scholar

Bruk-Lee, V., Drew, E. N., & Hawkes, B. (2013). Candidate reactions to simulations and media-rich assessments in personnel selection. In Fetzer, M. S. & Tuzinski, K. A. (Eds.), Simulations for employee selection. New York: Springer.Google Scholar

Buhrmester, M., Kwang, T., & Gosling, S.D. (2011). Amazon’s Mechanical Turk: A new source of inexpensive, yet high-quality, data? Perspectives on Psychological Science, 6(1), 3–5.CrossRefGoogle Scholar

Chamorro-Premuzik, T., Winsborough, D., Sherman, R. A., & Hogan, R. (2016). New talent signals: Shiny new objects or brave new world? Industrial-Organizational Psychology Perspectives, 9, 629–640.Google Scholar

Cianciolo, A. T., & Sternberg, R. J. (2004). Intelligence – a brief history. Malden, MA: Blackwell Publishin.Google Scholar

Cole, M. S., Field, H. S., & Stafford, J. O. (2005). Validity of résumé reviewers’ inferences concerning applicant personality based on résumé evaluation. International Journal of Selection and Assessment, 13(4), 321–324.Google Scholar

Cottrell, J. M., Newman, D. A., & Roisman, G. I. (2015). Explaining the black–white gap in cognitive test scores: Toward a theory of adverse impact. Journal of Applied Psychology, 100(6), 1713–1736.Google Scholar

Cucina, J. M., Caputo, P. M., Thibodeaux, H. F., & MacLane, C. N. (2012). Unlocking the key to biodata scoring: A comparison of empirical, rational and hybrid approaches at different sample sizes. Personnel Psychology, 65, 385–428.Google Scholar

Cucina, J. M., Caputo, P. M., Thibodeaux, H. F., MacLane, C. N., & Bayless, J. M. (2013). Scoring biodata: Is it rational to be quasi-rational? International Journal of Selection and Assessment, 21, 226–232.Google Scholar

Dalal, R. S., Meyer, R. D., Bradshaw, R. P., Green, J. P., Kelly, E. D., & Zhu, M. (2015). Personality strength and situational influences on behavior: A conceptual review and research agenda. Journal of Management, 41, 261–287.Google Scholar

Dunnette, M. D. (1962). Personnel management. Annual Review of Psychology, 13, 285–314.Google Scholar

Fallaw, S. S., Kantrowitz, T. M., & Dawson, C. R. (2012). 2012 Global Assessment Trends Report. SHL.Google Scholar

Fetzer, M., & Tuzinski, K. (2013). Simulations for personnel selection. New York: Springer.Google Scholar

Gatewood, R. D., Field, H. S., & Barrick, M. (2011). Human resources selection: 7th edition. Mason, OH: South-Western.Google Scholar

Ghiselli, E. E. (1973). The validity of aptitude tests in personnel selection. Personnel Psychology, 26, 461–477.Google Scholar

Gneezy, U., & List, J. A. (2013). The why axis: Hidden motives and the undiscovered economics of everyday life. New York: Public Affairs.Google Scholar

Goldberg, L. R. (1993). The structure of phenotypic personality traits. American Psychologist, 48, 26–34.CrossRefGoogle Scholar

Gowing, M. K., Morris, D. M., Adler, S., & Gold, M. (2008). The next generation of leadership assessments: Some case studies. Public Personnel Management, 37, 435–455.CrossRefGoogle Scholar

Greenwald, A. G., Banaji, M. R., & Nosek, B. A. (2015). Statistically small effects of the Implicit Association Test can have societally large effects. Journal of Personality and Social Psychology, 108, 553–561.Google Scholar

Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political Analysis, 21, 267–297.Google Scholar

Guion, R. M. (1997). Assessment, measurement, and prediction for personnel decisions. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.CrossRefGoogle Scholar

Hoffman, B. J., Kennedy, C. L., LoPilato, A. C., Monahan, E. L., & Lance, C. E. (2015). A review of the content, criterion-related, and construct-related validity of assessment center exercises. Journal of Applied Psychology, 100, 1143.CrossRefGoogle Scholar

Holland, J. L. (1973). Making vocational choices: A theory of careers. Englewood Cliffs, NJ: Prentice Hall.Google Scholar

James, L. R., & McIntyre, M. D. (2000). Conditional reasoning test of aggression test manual. Knoxville, TN: Innovative Assessment Technology.Google Scholar

Johnson, T., & Boyce, A. S. (2015). Selection testing: An updated look at trends in mobile device usage. Presented at the 30th Annual Meeting of the Society for Industrial and Organizational Psychology, Philadelphia, PA.Google Scholar

Judge, T. A., & Bono, J. E. (2001). Relationship of core self-evaluations traits – self-esteem, generalized self-efficacy, locus of control, and emotional stability – with job satisfaction and job performance: A meta-analysis. Journal of Applied Psychology, 86, 80.Google Scholar

Kosinski, M., Matz, S. C., Gosling, S. D., Popov, V., & Stillwell, D. (2015). Facebook as a research tool for the social sciences: Opportunities, challenges, ethical considerations, and practical guidelines. American Psychologist, 70(6), 543–556.Google Scholar

Kosinski, M., Stillwell, D. J., & Graepel, T. (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences of the United States of America, 110(15), 5802–5805.CrossRefGoogle ScholarPubMed

Kristof-Brown, A., & Ryan, A. M. (2003). Focusing on personality in person-organization fit research: Unaddressed issues. In Barrick, M. R. & Ryan, A. M. (Eds.), Personality and work: Reconsidering the role of personality in organizations (pp. 262–288). San Francisco: Jossey-Bass.Google Scholar

Lievens, F., & Burke, E. (2011). Dealing with the threats inherent in unproctored Internet testing of cognitive ability: Results from a large-scale operational test program. Journal of Occupational and Organizational Psychology, 84, 817–824.Google Scholar

Lilienfeld, S. O., Wood, J. M., & Garb, H. N. (2000). The scientific status of projective techniques. Psychological Science in the Public Interest, 1, 27–66.Google Scholar

McDaniel, M. A., Whetzel, D. L., Schmidt, F. L. & Maurer, S. D. (1994). The validity of employment interviews: A comprehensive review and meta-analysis. Journal of Applied Psychology, 79(4), 599–616.Google Scholar

McNelly, T., Ruggeberg, B. J., & Hall, C. R. (2011). Web‐based management simulations: Technology‐enhanced assessment for executive‐level selection and development. In N. T. Tippins & S. Adler (Eds.), Technology-enhanced assessment of talent. Hoboken, NJ: John Wiley & Sons.Google Scholar

Motowidlo, S., Dunnette, M. D., & Carter, G. W. (1990). An alternative selection procedure: The low-fidelity simulation. Journal of Applied Psychology, 75, 640–647.Google Scholar

Nye, C. D., Do, B., Drasgow, F., & Fine, S. (2008). Two-step testing in employee selection: Is score inflation a problem? International Journal of Selection and Assessment, 16, 112–120.CrossRefGoogle Scholar

Park, G., Schwartz, H. A., Eichstaedt, J. C., Kern, M. L., Kosinski, M., Stillwell, D. J., Ungar, L. H., & Seligman, M. E. P. (2015). Automatic personality assessment through social media language. Journal of Personality and Social Psychology, 108, 934–952.Google Scholar

Prinsloo, M., & Prinsloo, R. (2001). The Cognitive Process Profile (CPP) user’s manual. Johannesburg, South Africa: Cognadev.Google Scholar

Provost, F., & Fawcett, T. (2013). Data science for business. Sebastopol, CA: O’Reilly Media.Google Scholar

Ree, M. J., & Earles, J. A. (1994). Predicting training success: Not much more than g. Personnel Psychology, 44, 321–332.CrossRefGoogle Scholar

Ree, M. J., Carretta, T. R., & Teachout, M. S. (2015). Pervasiveness of dominant general factors in organizational measurement. Industrial and Organizational Psychology 8(3), 409–427.Google Scholar

Ruggs, E. N., Walker, S. S., Blanchard, A., & Gur, S. (2016). Online exclusion: Biases that may arise when using social media in talent acquisition. In Landers, R. N. & Schmidt, G. B. (Eds.), Social media in employee selection and recruitment. Switzerland: Springer.Google Scholar

Ryan, A. M., & Tippins, N. (2009). Designing and implementing global selection systems. Chichester, UK: John Wiley.Google Scholar

Sackett, P. R., & Lievens, F. (2008). Personnel selection. Annual Review of Psychology, 59, 419–445.Google Scholar

Salgado, J. F. (1997). The five factor model of personality and job performance in the European community. Journal of Applied Psychology, 82, 30–43.Google Scholar

Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection procedures in personnel psychology: Practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124(2), 262–274.Google Scholar

Seibert, M., Williams, K., & Raymark, P. (2010). Résumé screening: A policy capturing study of recruiter judgments. Paper presented at 25th Annual Conference of the Society for Industrial & Organizational Psychology, Atlanta, GA.Google Scholar

Seligman, M. E., & Schulman, P. (1986). Explanatory style as a predictor of productivity and quitting among life insurance sales agents. Journal of Personality and Social psychology, 50, 832–838.Google Scholar

Seymour, N. E., Gallagher, A. G., Roman, S. A., O’Brien, M. K., Bansal, V. K., Andersen, D. K., & Satava, R. M. (2002). Virtual reality training improves operating room performance: Results of a randomized, double-blinded study. Annuals of Surgery, 236(4): 458–464.Google Scholar

Smith, D. B. (Ed.). (2008). The people make the place: Dynamic linkages between individuals and organizations. New York: Lawrence Erlbaum Associates.Google Scholar

Stahl, M. J. (1983). Achievement, power and managerial motivation: Selecting managerial talent with the job choice exercise. Personnel Psychology, 36(4), 775–789.CrossRefGoogle Scholar

Stark, S., Chernyshenko, O. S., Drasgow, F., & White, L. A. (2012). Adaptive testing with multidimensional pairwise preference items: Improving the efficiency of personality and other noncognitive assessments. Organizational Research Methods, 15(3), 463–487.Google Scholar

Stoughton, J. W. (2016). Applicant reactions to social media in selection: Early returns and future directions. In Landers, R. N. & Schmidt, G. B. (Eds.), Social media in employee selection and recruitment. Switzerland: Springer.Google Scholar

Tippins, N. T., Beatty, J., Drasgow, F., Gibson, W. M., Pearlman, K., Segall, D. O., & Shepherd, W. (2006). Unproctored Internet testing in employment settings. Personnel Psychology, 59, 189–225.CrossRefGoogle 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, 96(1), 13–33.Google Scholar

Weekley, J. A., & Ployhart, R. E. (Eds.). (2006). Situational judgment tests: Theory, measurement and application. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar

Weiner, J. (2010). Verification testing models, values, and considerations. Presented at the 25th Annual Meeting of the Society for Industrial and Organizational Psychology, Atlanta, GA.Google Scholar

Werbach, K., & Hunter, D. (2015). The gamification toolkit: Dynamics, mechanics, and components for the win. Philadelphia: Wharton Digital Press.Google Scholar

Zeidner, M., Matthews, G., & Roberts, R. D. (2004). Emotional intelligence in the workplace: A critical review. Applied Psychology: An International Journal, 53, 371–399.Google Scholar

American Educational Research Association, American Psychological Association, & National Council on Measurement in Education (2014). Standards for educational and psychological testing. Washington, DC: AERA.Google Scholar

Allen, M. J., & Yen, W. M. (1979). Introduction to measurement theory. Long Grove, IL: Waveland Press.Google Scholar

Americans with Disabilities Act of 1990. Pub. L. 101–336. 26 July 1990. 104 Stat. 328.Google Scholar

Baker, & McKenzie, (2006). Worldwide guide to termination, employment discrimination, and workplace harassment laws. Ithaca, NY: Cornell ILR School Digital Commons.Google Scholar

Bennett, R. E., & Zhang, M. (2016). Validity and automated scoring. In Drasgow, F. (Ed.), Technology and testing. New York: Routledge.Google Scholar

Bloom, B. S. (Ed.). Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956). Taxonomy of educational objectives, handbook I: The cognitive domain. New York: David McKay Co.Google Scholar

Cizek, G. J. (Ed.). (2001). Setting performance standards: Concepts, methods and perspectives. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar

Conradt, C. (2012). The game of work. Layton, UT: Gibbs Smith.Google Scholar

Davey, T., & Nering, M. (2002). Controlling item exposure and maintaining item security. In Mills, C. N., Potenza, M. T., Fremer, J. J., & Ward, W. C. (Eds.), Computer-based testing: Building the foundations for future assessments (pp. 165–191). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar

Feinberg, R. A., Raymond, M. R., & Haist, S. A. (2015). Repeat testing effects on credentialing exams: Are repeaters misinformed or uninformed? Educational Measurement Issues and Practice, 34(1), 34–39.Google Scholar

Foster, D., & Miller, H. L., Jr. (2009). A new format for multiple-choice testing: Discrete-Option Multiple-Choice. Results from early studies. Psychology Science Quarterly, 51(4), 355–369.Google Scholar

Foster, D. F., & Zervos, C. (2006). The big Internet heist. Poster presented at the Association of Test Publishers annual conference, Orlando, FL.Google Scholar

Gibson, W. M., & Weiner, J. A. (1998). Generating random parallel test forms using CTT in a computer-based environment. Journal of Educational Measurement, 25, 4.Google Scholar

Gierl, M., & Lai, H. (2013). Educational measurement: Issues and practice: Instructional topics in educational measurement (ITEMS). Module: Using automated processes to generate test items.Google Scholar

The International Standards Organization (ISO) (2012). International Standard ISO/IEC Standard 17024:2012 ISO.Google Scholar

Kolen, M. J., & Brennan, R. L. (1995). Test equating. New York: Springer.Google Scholar

Krogue, K. (2012, September 18). 5 gamification rules from the grandfather of gamification. Forbes.Google Scholar

Lord, F., & Novick, M. (1968). Statistical theories of mental test scores. Reading, MA: Addison-Wesley.Google Scholar

Mehrens, W. A. (1995). Licensure testing: Purposes, procedures, and practices. Paper 6.Google Scholar

Moore, G. (circa 1970). Retrieved from https://en.wikipedia.org/wiki/Moore%27s_law (accessed May 21, 2016).Google Scholar

National Commission for Certifying Agencies (2016). Standards for the accreditation of certification programs. Washington DC: Institute for Credentialling Excellence.Google Scholar

Peng, C. J., & Subkoviak, M. J. (1980). A note on Huynh’s normal approximation procedure for estimating criterion-referenced reliability. Journal of Educational Measurement, 17(4), 359–368.Google Scholar

Segall, D. O., & Moreno, K. E. (1999). Development of the computerized adaptive testing version of the Armed Services Vocational Batter. In Drasgow, F. & Olson-Buchanan, J. B. (Eds.), Innovations in cauterized assessments. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar

Sergeant, (2012). Verification and validation of simulation models. Journal of Simulation, 7, 12–14.Google Scholar

Shapiro, J. (2015). How a law to protect disabled Americans became imitated around the world. Retrieved from www.npr.org/sections/goatsandsoda/2015/07/24/425607389/how-a-law-to-protect-disabled-americans-became-imitated-around-the-world.Google Scholar

US Copyright Office, Library of Congress (2000). Copyright basics. Washington, DC: Author.Google Scholar

US Copyright Office, Library of Congress (2015). Circular 38a.0915. Washington, DC: Author.Google Scholar

US Equal Employment Opportunity Commission, Department of Labor, Department of Justice, & Civil Service Commission (1978). Section 60–3, Uniform guidelines on employee selection procedures. 43 FR 38295.Google Scholar

Weller, J., Henderson, R., Webster, C., Shulruf, B., Torrie, J., Davies, E., Frampton, C., & Merry, A. (2014). Building the evidence on simulation validity: Comparison of anesthesiologists’ communication patterns in real and simulated cases. Anesthesiology, 120, 1.CrossRefGoogle ScholarPubMed

Werbach, K., & Hunter, D. (2015). For the win: How game thinking can revolutionize your business. Wharton Digital Press.Google Scholar