Biography

Professor Chang's research has focused primarily on improving large scale assessments, specifically on issues emerged from the K-12 accountability testing. His research interests are broad, encompassing both theoretical development and applied methodologies, including Computerized Adaptive Testing, Differential Item Functioning, Cognitive Diagnosis, and asymptotic properties in IRT. Many of his manuscripts were published in top-tier journals, ranging from very theoretical, such as Annals of Statistics, to very applied, such as Journal of Educational Measurement. He is a past President of the Psychometric Society (2012-2013), a Fellow of American Educational Research Association, and a Fellow of American Statistical Association.

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Key Professional Appointments

Professor Educational Psychology, University of Illinois at Urbana-Champaign, 2009 - 2018

Professor Psychology, University of Illinois at Urbana-Champaign, 2009 - 2018

Professor (0-time) Statistics, University of Illinois at Urbana-Champaign, 2009 - 2018

Associate Professor Educational Pyschology, University of Illinois at Urbana-Champaign, 2005 - 2009

Associate Professor Psychology, University of Illinois at Urbana-Champaign, 2005 - 2009

Associate Professor (0-time) Statistics, University of Illinois at Urbana-Champaign, 2005 - 2009

Associate Professor Educational Pyschology, University of Texas, Austin, 2001 - 2005

Senior Psychometrician and Director Computerized Testing Technological Research, National Board of Medical Examiners, Philadelphia, PA, 1999 - 2001

Research Scientist Division of Statistics and Psychometrics Research, Educational Testing Service, Princeton, NJ, 1992 - 1999

Associate Professor Educational Psychology, The Chinese University of Hong Kong, 1997 - 1998

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Education

Ph.D., Statistics, University of Illinois at Urbana-Champaign, 1992

M.S., Statistics, University of Illinois at Urbana-Champaign, 1988

Diploma, Mathematics, East China Normal University, Shanghai, China, 1980

Research & Service

Professor Chang's research has focused primarily on improving large scale assessments, specifically on issues emerged from the K-12 accountability testing. His research interests are broad, encompassing both theoretical development and applied methodologies, including Computerized Adaptive Testing, Differential Item Functioning, Cognitive Diagnosis, and asymptotic properties in IRT.

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Publications

Chang, H., Wang, C., & Ying, Z. (2016). Information theory and its application to testing Handbook of item response theory, Volume Two, Statistical Tools (pp. 105-123) ( vol. 2, pp. 105-123). Boca Raton, FL, USA: CRC Press, Taylor & Francis Group.

Guo, R., Zheng, Y., & Chang, H. (2015). A stepwise test characteristic curve method to detect item parameter drift. Journal of Educational Measurement, 52 (3), 280-300.

Chang, H. (2015). Psychometrics behind computerized adaptive testing. Psychometrika, 80 (1), 1-20.  link >

Zheng, Y., & Chang, H. (2014). On-the-fly assembled multistage adaptive testing. Applied Psychological Measurement, DOI: 10.1177/0146621614544519.

Wang, S., Fellouris, G., & Chang, H. (2017). Computerized adaptive testing that allows for response revision: design and asymptotic Theory Satistica Sinica, 27 1987-2010.  link >

Kang, H., Lu, Y., & Chang, H. (2017). IRT item parameter scaling for developing new item pools Applied Measurement in Education, 30 (1), 1-15.

Zheng, C., & Chang, H. (2016). High-efficiency response distribution–based item selection algorithms for short-length cognitive diagnostic computerized adaptive testing. Applied Psychological Measurement, 40 (8), 608-624.

Kang, H., & Chang, H. (2016). Parameter drift detection in multidimensional computerized adaptive testing based on informational distance/divergence Measures. Applied Psychological Measurement, 40 (7), 534-550.

Zhang, S., & Chang, H. (2016). From Smart Testing to Smart Learning: How Testing Technology Can Assist the New Generation of Education International Journal of Smart Technology, 1 67-92.

Zheng, Y., & Chang, H. (2014). Multistage testing, on-the-fly multistage testing, and beyond Advanced methodologies to support both summative and formative assessments Charlotte, NC, USA: Information Age Publisher Inc.

Cheng, Y., & Chang, H. (2014). Advanced methodologies to support both summative and formative assessments. Charlotte, NC. , USA: Information Age Publisher Inc.

Zheng, Y., Wang, C., Culbertson, M., & Chang, H. (2014). Test assembly in computerized multistage testing. In D. Yan, A. A. von Davier, & C. Lewis (Eds.), Computerized multistage testing: Theory and applications New York, NY, USA: CRC Press.

Wang, C., Zheng, Y., & Chang, H. (2014). Does standard deviation matter? Using standard deviation to quantify security of multistage testing Psychometrika, 79 (1), 99-122.

Liu, H., You, X., Wang, W., Ding, S., & Chang, H. (2013). The development of computerized adaptive testing with cognitive diagnosis for an English achievement test in China Journal of Classification, 30 144-168.

Wang, C., Chang, H., & Douglas, J. (2013). The linear transformation model with frailties for the analysis of item response times British Journal of Mathematical and Statistical Psychology, 66 144-168.

Wang, C., Fan, Z., Chang, H., & Douglas, J. (2013). A semiparametric model for jointly analyzing response times and accuracy in computerized testing. Journal of Educational and Behavioral Statistics, 38 (4), 381-417.

Chang, H. (2012). Making computerized adaptive testing diagnostic tools for schools. Computers and their impact on state assessment: Recent history and predictions for the future ( pp. 195-226). Charlotte, NC: Information Age Publisher.

Chen, P., Chang, H., & Wu, H. (2012). Item selection for the development of parallel forms from an IRT-based seed test using a sampling and classification approach. Educational and Psychological Measurement, 72 (6), 933-953.

Chen, P., Xin, T., Wang, C., & Chang, H. (2012). On-line calibration methods in cognitive diagnostic computerized adaptive testing. Psychometrika, 77 (2), 201-222.

Cui, Y., Gierl, M., & Chang, H. (2012). Evaluating Item Selection Algorithms in Computerized Adaptive Testing  for Cognitive Diagnosis: A Simulation Study. Juornal of Educational Measurement, 49 (1), 19-38.

Tao, J., Shi, N., & Chang, H. (2012). Item-weighted likelihood method for ability estimation in tests composed of both dichotomous and polytomous Items. Journal of Educational and Behavioral Statistics, 37 (2), 298-315.

Wang, C., Chang, H., Douglas, J., & Chang, H. (2012). Combining CAT with cognitive diagnosis: a weighted item selection approach. Behavior Research Methods, 44 95-109.

Chang, H. (2008). Psychometrics International Encyclopedia of the Social Sciences, 2nd addition ( vol. Vol 6, pp. 587-590). Detroit, MI: MacMillan Library Reference USA.

Chang, H., & Ying, Z. (2006). Computerized adaptive testing. Encyclopedia of measurement and statistics ( pp. 170-174). Thousand Oaks, CA: Sage.

Chang, H. (2004). Understanding computerized adaptive testing: From Rabins-Moron to Lord, and beyond. The sage handbook of quantitative methods for the social sciences ( pp. 117-133). Sage Publications.

Chang, H., & Zhang, J. (2002). Hypergeometric family and item overlap rates in computerized adaptive testing. Psychometrika, 67 387-398.

Hau, K., & Chang, H. (2001). Item selection in computerized adaptive testing: should more discriminating items be used first? Journal of Educational Measurement, 38 249-266.

Choe, E., Kern, J., & Chang, H. Optimizing the use of response times for item selection in computerized adaptive testing. Journal of Educational and Behavioral Statistics.  link >

Kang, H., Zhang, S., & Chang, H. Dual-objective item selection criteria in cognitive diagnostic computerized adaptive testing. Jounral of Educational Measurement.

Kang, H., Zhang, S., & Chang, H. Jensen-Shannon divergence as a dual-objective: item selection criterion in CD-CAT Hournal of Educational Measurement.

Wang, C., Chang, H., & Douglas, J. The linear transformation model with frailties for the analysis of item response times. British Journal of Mathematical and Statistical Psychology.

Wang, C., Chang, H., Boughton, K., & Chang, H. Deriving stopping rules for multidimensional computerized adaptive testing. Applied Psychological Measurement.

Zheng, Y., Chang, C., Chang, H., & Chang, H. Content-balancing strategy in bifactor computerized adaptive patient-reported outcome measurement. Quality of Life Research.

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Presentations

A new index to measure test security for online testing (2012).: Lincoln, Nebraska.

Aggregate ranked information method (ARI) for CD-CAT in a large scale assessment (2012).: Lincoln, Nebraska.

Deriving the reliability measures for multistage testing (2012).: Lincoln, Nebraska.

Exploring the mutual information and Bayesian d-optimality item selection methods in multidimensional adaptive testing (2012).: Lincoln, Nebraska.

Making multistage testing more secure --- an analysis under the item theft scenario (2012).: Lincoln, Nebraska.

The item-weighted likelihood method for mixed item type computerized adaptive testing (2012).: Lincoln, Nebraska.

Computerized adaptive testing and multistage testing: in which direction should on-line testing go? (2012).: Vancouver, Canada.

Item selection methods in multidimensional computerized adaptive testing adopting polytomously scored items under multidimensional generalized partial credit model (2012).: Vancouver, Canada.

Multistage adaptive testing for a large-scale classification test: the design, heuristic assembly, and comparison with other testing modes (2012).: Vancouver, Canada.

Reducing bias in MIRT trait estimation (2012).: Vancouver, Canada.

The effect of multiple item pools for the possibly compromised items in computerized adaptive testing (2012).: Vancouver, Canada.

The 2011 International Association of Computerized Adaptive Testing Conference (2011). The 2011 International Association of Computerized Adaptive Testing Conference.: Pacific Grove, CA.

Media and Information Literacy Indicators and Government Action Recommendation (2011).: Hato Rey, Puerto Rico.

Building affordable CD-CAT systems for schools to address today's challenges in assessment (2011).: Hong Kong, China.

Modeling response time in computerized testing using semi-parametric linear transformation model (2011).: Hong Kong, China.

Adaptive pretest approaches and online calibration methods for linear fixed-length computer-based tests (2011).: New Orleans, LA.

An enhanced approach to combine item response theory with cognitive diagnosis in adaptive tests (2011).: New Orleans, LA.

Automatic on-the-fly assembly for computer adaptive multistage testing Paper presented at the Annual Meeting of National Council on Measurement in Education (2011).: New Orleans, LA.

Item replenishing in cognitive diagnostic computerized adaptive testing (2011).: New Orleans, LA.

Making computerized adaptive testing a diagnostic tool (2011).: New Orleans, LA.

Computerized testing, E-rater, and generic algorithm: Psychometrics to support emerging technologies (2004).: Beijing, China.

Adjustment of BIB data for DIF Testing (2004).: Pacific Grove, CA.

Two-phase item selection with realistic content balancing constraints in computerized adaptive testing (2004).: Pacific Grove, CA.

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Service

Editor in Chief Applied Psychological Measurement, 2012 - 2018

President Psychometric Society, 2012 - 2013

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Courses

Theories of Measurement II (EPSY 586) Provides a conceptual framework of Item Response Theory (IRT) and its applications. Students will learn the techniques and theory of IRT and apply the methods to educational and psychological assessments. Topics covered include both dichotomous and polytomous IRT modelling, item structure and latent traits estimation, modeling and detecting Differential Item Functioning, linking and equating, computer adaptive testing, dimensionality testing, and cognitive diagnosis. Same as PSYC 596.

Computerized Adaptive Testing (EPSY 590) Seminar in educational psychology; topics relate to the areas of specialization represented by the various divisions within the department. 0 to 4 graduate hours. No professional credit. Approved for Letter and S/U grading. May be repeated to a maximum of 8 hours in the same or separate semesters, if topics vary.

Chang, Hua-Hua

Professor Emeritus, Educational Psychology

Contact

Office

Education Building
1310 S. Sixth St.
Champaign, IL 61820

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