Professor DE LA TORRE, Jimmy
Professor DE LA TORRE, Jimmy
吳嘉揚
Unit HeadProfessor
Academic Unit of Human Communication, Development, and Information Sciences
Qualification
Ph.D., University of Illinois at Urbana-Champaign
[javascript protected email address]
Phone
(852) 2241 5979
Location
Room 804A, Meng Wah Complex
Research Expertise
Assessment, Testing and Measurement
Research Methods and Methodologies
Technology-enhanced Learning
Prospective PhD/ EdD/ MPhil Applications
I am available to supervise PhD/MPhil students and would welcome enquiries for supervision.
Awards
2014 – present: Chair Professor (National Taichung University of Education, Taiwan)
2012 – present: Honorary Professor (Universidad Autonoma de Madrid, Spain)
2017: Bradley Hanson Award for Contributions to Educational Measurement (National Council on Measurement in Education)
2009: Jason Millman Promising Measurement Scholar Award (National Council onMeasurement in Education)
2009: Presidential Early Career Award for Scientists and Engineers (White House)
2008: National Science Foundation Faculty Early Career Development Award
2006: National Academy of Education/Spencer Postdoctoral Fellowship
Projects
Hong Kong Research Grants Council. Optimizing the Diagnostic Value and Practicability of a Cognitive Diagnosis Modeling Framework for Multiple-choice Tests: Model Extensions and Practical Implementations. (Principal Investigator), October, 2020 – September, 2022.
Hong Kong Research Grants Council. Role of the Home and School in Children’s Early English Language and Literacy Development in Hong Kong. (Co-Investigator), January, 2020 – December, 2022.
Hong Kong Research Grants Council. Methodological Developments to Enhance Diagnostic Modeling and Scoring of Multicategory Skills. (Principal Investigator), October, 2018 – September, 2020.
University of Hong Kong Research Services. Adaptation, Calibration, and Invariance Evaluation of a Proportional Reasoning Assessment. (Principal Investigator), April, 2017 – September, 2018.
Hong Kong Research Grants Council. Learning and Assessment for Digital Citizenship. (Co-Principal Investigator), November, 2016 – October, 2021.
National Science Foundation. Validating Proof Comprehension Tests in Mathematics. (Co-Principal Investigator), September, 2013 – August, 2015.
National Institute on Alcohol Abuse and Alcoholism. Innovative Analyses of Alcohol Intervention Trials for College Students. (Co-Principal Investigator), August 2010 – July 2013.
National Science Foundation. Emerging Research-Empirical--Proving Styles in University Mathematics. (Co-Principal Investigator), August 2010 – July 2013.
U.S. Department of Education. Graduate Assistance in Areas of National Need Fellowship Program - Graduate Fellowships in Educational Assessment, Evaluation and Research. (Principal Investigator), July 2010 – June 2015.
National Science Foundation. CAREER: A Comprehensive Modeling Approach to Cognitively Diagnostic Assessment: Methodological Developments and Practical Implementations. (Principal Investigator), July 2008 – August 2015.
National Academy of Education/Spencer Postdoctoral Fellowship. Designing Assessment to Support Learning: A New Approach to Test Construction and Analysis (Principal Investigator), July 2006 – July 2008.
Institute of Education Sciences. Skill Profile Comparisons at the State Level: An Application and Extension of Cognitive Diagnosis Modeling in NAEP. (Principal Investigator), June 2005 – December 2006.
Contract Research Projects
Education Bureau, HKSAR. Research Project on the Development and Validation of Knowledge Structures and Assessment Questions for the Mathematics Subject for Student Adaptive Learning (SALS-2). (Co-Investigator), March 2019 – March 2020.
Education Bureau, HKSAR. The Development of a Student Adaptive Learning System for Mathematics for Primary Schools to Enhance Learning and Teaching. (Co-Investigator), October 2017 – September 2018.
UNESCO Institute for Statistics. Developing a Global Competency Framework of Reference on Digital Literacy Skills for Indicator 4.4.2. (Co-Investigator), October 2017 – April 2018.
Publications
Refereed Articles
de la Torre, J., Que, X.-L., & Santos, K. C. (in press). An empirical q-matrix validation method for the polytomous G-DINA model. Psychometrika..
Liang, Q., de la Torre, J., & Law, N. (2021). Do background characteristics matter in children's mastery of digital literacy? A cognitive diagnosis model analysis. Computer in Human Behavior, 122, 106850.
Ma, W., Terzi, R., & de la Torre, J. (2021). Detecting differential item functioning using multiple-group cognitive diagnosis models. Applied Psychological Measurement, 45, 37-53.
Mehrazmay, R., Ghonsooly, B., & & de la Torre, J. (2021). Detecting differential item functioning using cognitive diagnosis models: Applications of the Wald test and likelihood ratio test in a university entrance. Applied Measurement in Education. Applied Measurement in Education.. doi.org/10.1080/**.2021.**
Najera, P., Sorrel, M. A., de la Torre, J., & Abad, F. J. (2021). Balancing fit and parsimony to improve Q-matrix validation.British Journal of Mathematical and Statistical Psychology, 74, 110-130.
Yakar, L., Dogan, N., & de la Torre, J. (2021). Retrofitting of polytomous cognitive diagnosis and multidimensional item response theory models. Journal of Measurement and Evaluation in Education and Psychology, 12, 97-111.
Akbay, L., & de la Torre, J. (2020). Estimation approaches in cognitive diagnosis modeling when attributes are hierarchically structured. Psicothema, 32, 122-129.
Finkelman, M., de la Torre, J., & Karp, J. (2020). Cognitive diagnosis models and automated test assembly: An approach incorporating response times. International Journal of Testing, 20, 299-320.
Hou, L., Terzi, R., & de la Torre, J. (2020). Wald test Formulations in DIF detection of CDM data with the proportional reasoning test. International Journal of Assessment Tools in Education, 7, 145-158.
Jin, K.-Y., Reichert, F., Cagasan, L. P., de la Torre, J., & Law, N. (2020). Measuring digital literacy across three age cohorts: Exploring test dimensionality and performance differences. Computers & Education, 157, 103968.
Kaplan, M., & Law, N. (2020). A blocked-CAT procedure for CD-CAT. Applied Psychological Measurement, 44, 49-64.
Ma, W., & de la Torre, J. (2020a). An empirical Q-matrix validation method for the sequential G-DINA model. British Journal of Mathematical and Statistical Psychology, 73, 142-163.
Ma, W., & de la Torre, J. (2020b). Cognitive diagnosis modeling using the GDINA R package. Journal of Statistical Software, 19(14), 1-26.
Ma, W., Michen, N., & de la Torre, J. (2021). Choosing between CDM and unidimensional IRT: The proportional reasoning test case. Measurement: Interdisciplinary Research and Perspectives, 18, Journal of Statistical Software, 18, 87-96.
Najera, P., Sorrel, M. A., de la Torre, J., & Abad, F. J. (2020). Improving robustness in Q-matrix validation using an iterative and dynamic Procedure. Applied Psychological Measurement, 44, 431-446.
Reichert, F., Zhang, J., Law, N., Wong, G., & de la Torre, J. (2020). Exploring the structure of digital literacy competence assessed using authentic software applications. Educational Technology Research & Development, 68, 2991-3013.
Santos, K., de la Torre, J., & von Davier, M. (2020). Adjusting person fit index for skewness in cognitive diagnosis modeling. Journal of Classification, 37, 399-420.
Sorrel, M. A., Barrada, J. R., de la Torre, J., & Abad, F. J. (2020). Adapting cognitive diagnosis computerized adaptive testing item selection rules to traditional item response theory. PLOS One. doi: 10.1371/journal.pone.**
Xu, X., de la Torre, J., Zhang, J., & Guo, J. (2020). Estimating CDMs using the slice-within-Gibbs sampler. Frontiers in Psychology. doi.org/10.3389/fpsyg.2020.02260
de la Torre, J., & Akbay, L. (2019). Implementation of cognitive diagnosis modeling using the GDINA R package. Eurasian Journal of Educational Research, 80, 171-192.
Ma, W., & de la Torre, J. (2019). Category-level model selection for the sequential G-DINA model. Journal of Educational and Behavioral Statistics, 44, 45-77.
Ma, W., & de la Torre, J. (2019). Digital module 05: Diagnostic measurement — The G‐DINA framework. Educational Measurement: Issues and Practice, 38, 114-115.
Skriner, L. C., Chu, B. C., Kaplan, M., Bodden, D. H. M., Bogels, S. M., Kendall, P. D., Nauta, M. H., Silverman, W. K., Wood, J. J., Barker, D. H., de la Torre, J., Saavedra, L., & Xie, M. (2019). Trajectories and predictors of response in youth anxiety CBT: Integrative data analysis. Journal of Consulting and Clinical Psychology, 87, 198-211.
Yigit, H., Sorrel, M. A., & de la Torre, J. (2019). Computerized adaptive testing for cognitively-based multiple-choice data. Applied Psychological Measurement, 43, 388-401.
Mun, E.-Y., Huo, Y., White, H. R., Suzuki, S., & de la Torre, J. (2019) Multivariate higher-order IRT model and MCMC algorithm for linking individual participant data from multiple studies. Frontiers in Psychology, 10:1328. doi: 10.3389/fpsyg.2019.01328
Chen, C.-H., Kuo, B.-C., & de la Torre, J. (2018). A cognitive diagnosis model for identifying coexisting skills and misconceptions. Applied Psychological Measurement, 42, 179-191.
Chen, J., & de la Torre, J. (2018). Introducing the general polytomous diagnosis modeling framework. Frontiers in Psychology. 9:1474. doi: 10.3389/fpsyg.2018.01474
de la Torre, J., van der Ark, L. A., & Rossi, G. (2018). Analysis of clinical data from a cognitive diagnosis modeling framework. Measurement and Evaluation in Counseling and Development, 51, 281-296.
Philipp, M., Strobl, C., de la Torre, J., & Zeileis, A. (2018). On the estimation of standard errors in cognitive diagnosis models. Journal of Educational and Behavioral Statistics, 43, 88-115.
Minchen, N., & de la Torre, J. (2018). A general cognitive diagnosis model for continuous-response data. Measurement: Interdisciplinary Research and Perspective, 16, 30-44.
Terzi, R., & de la Torre, J. (2018). An iterative method for empirically-based Q-matrix validation. International Journal of Assessment Tools in Education, 5, 248-262.
Mejía-Ramos, J. P., Lew, K., de la Torre, J., & Weber, K. (2017). Developing and validating proof comprehension tests in undergraduate mathematics. Research in Mathematics Education, 19, 130-146.
Minchen, N., de la Torre, J., & Liu, Y. (2017). A cognitive diagnosis model for continuous response. Journal of Educational and Behavioral Statistics, 42, 651-677.
Sorrel, M. A., Abad, F. J., Olea, J., de la Torre, J., & Barrada, J. R. (2017). Inferential item fit evaluation in cognitive diagnosis modeling. Applied Psychological Measurement, 41, 614-631.
Sorrel, M. A., de la Torre, J., Abad, F. J., & Olea, J. (2017). Two-step likelihood ratio test for model comparison in cognitive diagnosis models. Methodology, 13, 39-47.
de la Torre, J., Carmona, G., Kieftenbeld, V., Tjoe, H., & Lima, C. (2016). Diagnostic classification models and mathematics education research: Opportunities and Challenges. In A. Izsák, J. T. Remillard & J. Templin (Eds.), Psychometric methods in mathematics education: Opportunities, challenges, and interdisciplinary collaborations (pp. 53-72). Reston, VA: National Council of Teachers of Mathematics.
de la Torre, J., & Chiu, C.-Y. (2016). A general method of empirical Q-matrix validation. Psychometrika, 81, 253-273.
de la Torre, J., & Chiu, C.-Y. (2016). On the consistency of Q-matrix estimation: A rejoinder. Psychometrika, 82, 528-529.
Hontangas, P. M., V., Leenen, de la Torre, J., Ponsoda, I., Morillo, D., & Abad, F. J. (2016). Traditional scores versus IRT estimates on forced-choice tests based on a dominance model. Psicothema, 28, 76-82.
Kuo, B.-C., Pai, H.-S., & de la Torre, J. (2016). Modified cognitive diagnostic index and modified attribute-level discrimination index for test construction. Applied Psychological Measurement, 42 , 651-677.
Ma, W., & de la Torre, J. (2016) A sequential cognitive diagnosis model for polytomous responses. British Journal of Statistical and Mathematical Psychology, 69, 253-275.
Ma, W., Iaconangelo, C., & de la Torre, J.(2016). Model similarity, model selection, and attribute classification. Applied Psychological Measurement, 40, 200-217.
Morillo, D., Leenen, I., Abad, F. J., Hontangas, P., de la Torre, J., & Ponsoda, V. (2016). A dominance variant under the multi-unidimensional pairwise-preference framework: Model formulation and Markov chain Monte Carlo estimation. Applied Psychological Measurement, 40, 500-516.
Sorrel, M. A., Olea, J., Abad, F. J., de la Torre, J., Aguado, D., & Lievens, F. (2016). Validity and reliability of situational judgement test scores: A new approach based on cognitive diagnosis models. Organizational Research Methods, 19, 506-532.
Tatsuoka, C., Clements, D. H., Sarama, J., Izsák, A., Orrill, C. H., de la Torre, J., Tatsuoka, K., & Khasanova, E. (2016). Developing workable attributes for psychometric models based on the Q-matrix. In A. Izsák, J. T. Remillard & J. Templin (Eds.), Psychometric methods in mathematics education: Opportunities, challenges, and interdisciplinary collaborations (pp. 73-96). Reston, VA: National Council of Teachers of Mathematics.
Hontangas, P. M., de la Torre, J., Ponsoda, V., Leenen, I., Morillo, D., & Abad, F. J. (2015). Comparing traditional and IRT scoring of forced-choice tests. Applied Psychological Measurement, 39, 598-612.
Huo, Y., de la Torre, J., Mun, E. Y., Kim, S-Y., Ray, A. E., Jiao Y., & White H. R. (2015). A hierarchical multi-unidimensional IRT approach for analyzing sparse, multi-group data for integrative data analysis. Psychometrika, 80, 834-855.
Kaplan, M., de la Torre, J., & Barrada, J. R. (2015). New item selection methods for cognitive diagnosis computerized adaptive testing. Applied Psychological Measurement, 39, 167-188.
Mun, E.-Y., de la Torre, J., Atkins, D. C., White, H. R., Ray, A. E., Kim, S.-Y., Jiao, Y., Clarke, N., Huo, Y., Larimer, M. E., Huh, D., & The Project INTEGRATE Team (2015). Project INTEGRATE: An integrative study of brief alcohol interventions for college students. Psychology of Addictive Behaviors, 29, 34-48.
Chen, J., & de la Torre, J. (2014). A procedure for diagnostically modeling extant large-scale assessment data: The case of PISA reading assessment. Psychology, 5, 1967-1978.
de la Torre, J., & Minchen, N. (2014). Cognitively diagnostic assessments and the cognitive diagnosis model framework. Psicología Educativa, 20, 89-97.
Garcia, P., Olea, J., & de la Torre, J. (2014). Application of cognitive diagnosis models to competency-based situational judgment tests. Psichothema, 26, 372-377.
Hou, L., de la Torre, J., & Nandakumar, R. (2014). Differential Item Functioning Assessment in Cognitive Diagnosis Modeling: Application of the Wald Test to Investigate DIF in the DINA model. Journal of Educational Measurement, 51, 98-125.
Huo, Y., & de la Torre, J. (2014). An EM algorithm for the multiple-strategy DINA model. Applied Psychological Measurement, 38, 464-485.
Tjoe, H., & de la Torre, J. (2014). On recognizing proportionality: Does the ability to solve missing value proportional problems presuppose the conception of proportional reasoning? Journal of Mathematical Behavior, 33, 1-7.
Chen, J., & de la Torre, J. (2013). A general cognitive diagnosis model for expert-defined polytomous attributes. Applied Psychological Measurement, 37, 419-437.
Chen, J., de la Torre, J., & Zhang, Z.(2013). Relative and absolute fit evaluation in cognitive diagnosis modeling. Journal of Educational Measurement, 50, 123-140.
de la Torre, J., & Lee, Y.-S. (2013). Evaluating the Wald test for item-level comparison of saturated and reduced models in cognitive diagnosis. Journal of Educational Measurement, 50, 355-373.
de la Torre, J., Tjoe, H., Rhoads, K., & Lam, D. (2013). Conceptual and theoretical issues in proportional reasoning. International Journal for Studies in Mathematics Education, 6, 21-38.
Sun, J., Xin, T., Zhang, S., & de la Torre, J. (2013). A polytomous extension of the generalized distance discriminating method. Applied Psychological Measurement, 37, 503-521.
Tjoe, H., & de la Torre, J. (2013a). Designing cognitively-based proportional reasoning problems as an application of modern psychological measurement models. Journal of Mathematics Education, 16, 17-23.
Tjoe, H., & de la Torre, J. (2013b). The identification and validation process of proportional reasoning attributes: An application of a cognitive diagnosis modeling framework. Mathematics Education Research Journal, 26, 237-255.
Lee, Y.-S., de la Torre, J., & Park, Y. S. (2012). Cognitive diagnosticity of IRT-constructed assessment: An empirical investigation. Asia Pacific Education Review, 13, 333-345.
de la Torre, J. (2011). The generalized DINA model framework. Psychometrika, 76, 179-199.
de la Torre, J., Song, H., & Hong, Y. (2011). A comparison of four methods of subscoring. Applied Psychological Measurement, 35, 296-316.
Camilli, G., de la Torre, J., & Chiu, C-Y. (2010). A non-central t regression model for meta-analysis. Journal of Educational and Behavioral Statistics, 35, 125-153.
de la Torre, J., & Hong, Y. (2010). Parameter estimation with small sample size: A higher-order IRT model approach. Applied Psychological Measurement, 34, 267-285.
de la Torre, J., Hong, Y., & Deng, W. (2010). Factors affecting the item parameter estimation and classification accuracy of the DINA model. Journal of Educational Measurement, 47, 227-249.
de la Torre, J., & Lee, Y. S. (2010). A note on the invariance of the DINA model parameters. Journal of Educational Measurement, 47, 115-127.
de la Torre, J. (2009). A cognitive diagnosis model for cognitively-based multiple-choice options. Applied Psychological Measurement, 33, 163-183.
de la Torre, J. (2009). DINA model and parameter estimation: A didactic. Journal of Educational and Behavioral Statistics, 34, 115-130.
de la Torre, J. (2009). Improving the quality of ability estimates through multidimensional scoring and incorporation of ancillary variables. Applied Psychological Measurement, 33, 465-485.
de la Torre, J., & Karelitz, T. (2009). Impact of diagnosticity on the adequacy of models for cognitive diagnosis under a linear attribute structure. Journal of Educational Measurement, 46, 450-469.
de la Torre, J., & Song, H. (2009). Simultaneous estimation of overall and domain abilities: A higher-order IRT model approach. Applied Psychological Measurement, 33, 620-639.
Camilli, G., Prowker, A., Dossey, J. A., Lindquist, M. M., Chiu, T. W., Vargas, S., & de la Torre, J. (2008). Summarizing Item Difficulty Variation with Parcel Scores. Journal of Educational Measurement, 45, 363-390.
de la Torre, J. (2008). An empirically-based method of Q-matrix validation for the DINA model: Development and applications. Journal of Educational Measurement, 45, 343-362.
de la Torre, J. (2008). Multidimensional scoring of abilities: The ordered polytomous response case. Applied Psychological Measurement, 32, 355-370.
de la Torre, J., & Deng, W. (2008). Improving person fit assessment by correcting the ability estimate and its reference distribution. Journal of Educational Measurement, 45, 159-177.
de la Torre, J., & Douglas, J. (2008). Model evaluation and multiple strategies in cognitive diagnosis: An analysis of fraction subtraction data. Psychometrika, 73, 595-624.
de la Torre, J., Camilli, G., Vargas, S., & Vernon, R. F. (2007). Illustration of a multilevel model for meta-analysis. Measurement and Evaluation in Counseling and Development, 40, 169-180.
de la Torre, J., Stark, S., & Chernyshenko, O. (2006). Markov chain Monte Carlo estimation of item parameters for the generalized graded unfolding model. Applied Psychological Measurement, 30, 216-232.
de la Torre, J., & Patz, R. J. (2005). Making the most of what we have: A practical application of MCMC in test scoring. Journal of Educational and Behavioral Statistics, 30, 295-311.
de la Torre, J., & Douglas, J. (2004). Higher-order latent trait models for cognitive diagnosis. Psychometrika, 69, 333-353.
Book Chapters
de la Torre, J., & Sorrel, M. A. (in press). Cognitive diagnosis modeling. In H. Colonius, E. Dzhafarov & G. Ashby (Eds.), New Handbook of Mathematical Psychology: Volume 3.
Sun, Y., & de la Torre, J. (2020). Improving attribute classification accuracy in high dimensional data: A four-step latent regression approach. In H. Jiao & R. W. Lissitz (Eds.), Innovative Psychometric Modeling and Methods (pp. 17-44). Charlotte, NC: Information Age Publishing.
de la Torre, J., & Minchen, N. D. (2019). The G-DINA model framework. In M. von Davier & Y.-S. Lee (Eds.), Handbook of diagnostic classification models (pp. 155-169). New York: Springer.
Deonovic, B., Chopade, P., Yudelson, M., de la Torre, J., & von Davier, A. (2019). Application of cognitive diagnostic models to learning and assessment systems. In M. von Davier & Y.-S. Lee (Eds.), Handbook of diagnostic classification models (pp. 437-460). New York: Springer.
Santos, K. C., & de la Torre, J. (2018). Cognitive diagnosis modeling: An overview and illustration. In C. Magno & A. David (Eds.), Philippine and global perspectives on educational assessment (pp. 88-110). Manila: Philippine Educational Measurement and Evaluation Association.
Thummaphan, P., Li, M., & de la Torre, J. (2016). Models for cognitive diagnostic modeling. In V. Kijtorntham (Ed.), Methodological and theoretical articles for behavioral science research in community and school. Bangkok: Behavioral Science Research Institute.
de la Torre, J. (2012). Application of the DINA model framework to enhance assessment and learning. In M. Mok (Ed.), Self-directed learning oriented assessments in the Asia-Pacific (pp. 92-110). New York: Springer.
Professional Community Services
Associate Editor, Applied Psychological Measurement (2012– present)
Associate Editor, Frontiers in Education (2020 – present)
Editorial Board Member, Applied Measurement in Education (2019 – present)
Editorial Board Member, International Journal of Testing (2019 – present)
Editorial Board Member, Measurement: Interdisciplinary Research and Perspectives (2019 – present)
Consulting Editor, Educational Psychology: International Journal of Experimental Educational Psychology (2016 – present)
Editor-in-Chief, Journal of Educational Measurement (2014– 2016)
Member, Psychometric Society Board of Trustees (2016– 2018; 2021– 2023)
Chair, AERA SIG Cognition and Assessment (2021 – 2024)
