Developments in Psychometric Population Models for Technology-Based Large-Scale Assessments: An Overview of Challenges and Opportunities
暂无分享,去创建一个
Hyo Jeong Shin | Qiwei He | Matthias von Davier | Lale Khorramdel | Haiwen Chen | Qiwei He | Lale Khorramdel | Matthias von Davier | H. Shin | Haiwen Chen
[1] Matthias von Davier,et al. A general diagnostic model applied to language testing data. , 2008, The British journal of mathematical and statistical psychology.
[2] Adrian E. Raftery,et al. Model-Based Clustering, Discriminant Analysis, and Density Estimation , 2002 .
[3] Wim J. van der Linden,et al. IRT Parameter Estimation With Response Times as Collateral Information , 2010 .
[4] G. Ohlin. The Organization for Economic Cooperation and Development , 1968, International Organization.
[5] Helene Fowkes,et al. A method based on the chi-square test for document classification , 2001, SIGIR '01.
[6] Steven L. Wise,et al. An Application of Item Response Time: The Effort‐Moderated IRT Model , 2006 .
[7] Sebastian Thrun,et al. Text Classification from Labeled and Unlabeled Documents using EM , 2000, Machine Learning.
[8] Trevor Hastie,et al. Statistical Learning with Sparsity: The Lasso and Generalizations , 2015 .
[9] Steven L. Wise,et al. Response Time Effort: A New Measure of Examinee Motivation in Computer-Based Tests , 2005 .
[10] Matthias von Davier,et al. Measuring Growth in a Longitudinal Large-Scale Assessment with a General Latent Variable Model , 2011 .
[11] Heiko Rölke,et al. The time on task effect in reading and problem solving is moderated by task difficulty and skill: Insights from a computer-based large-scale assessment. , 2014 .
[12] Leslie Rutkowski,et al. Handbook of International Large-Scale Assessment : Background, Technical Issues, and Methods of Data Analysis , 2013 .
[13] Jian Pei,et al. A brief survey on sequence classification , 2010, SKDD.
[14] Wim J. van der Linden,et al. Bayesian Procedures for Identifying Aberrant Response-Time Patterns in Adaptive Testing , 2008 .
[15] Eric Maris,et al. Additive and multiplicative models for gamma distributed random variables, and their application as psychometric models for response times , 1993 .
[16] Francis Tuerlinckx,et al. A Bivariate Generalized Linear Item Response Theory Modeling Framework to the Analysis of Responses and Response Times , 2015, Multivariate behavioral research.
[17] Matthias von Davier,et al. Analyzing Process Data from Problem-Solving Items with N-Grams: Insights from a Computer-Based Large-Scale Assessment , 2016 .
[18] Yi-Hsuan Lee,et al. A review of recent response-time analyses in educational testing , 2011 .
[19] J. P. Meyer,et al. A Mixture Rasch Model With Item Response Time Components , 2010 .
[20] J WIM,et al. A HIERARCHICAL FRAMEWORK FOR MODELING SPEED AND ACCURACY ON TEST ITEMS , 2007 .
[21] Matthias von Davier,et al. Identifying Feature Sequences from Process Data in Problem-Solving Items with N -Grams , 2015 .
[22] J. Fox,et al. Joint Modeling of Ability and Differential Speed Using Responses and Response Times , 2016, Multivariate behavioral research.
[23] Alan Agresti,et al. Categorical Data Analysis , 2003 .
[24] Matthias von Davier,et al. A UNIFIED APPROACH TO IRT SCALE LINKING AND SCALE TRANSFORMATIONS , 2004 .
[25] Hinrich Schütze,et al. Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.
[26] Paul De Boeck,et al. Can fast and slow intelligence be differentiated , 2012 .
[27] Norman Rose,et al. Modeling Omitted and Not-Reached Items in IRT Models , 2017, Psychometrika.
[28] George Forman,et al. An Extensive Empirical Study of Feature Selection Metrics for Text Classification , 2003, J. Mach. Learn. Res..
[29] Shelby J. Haberman,et al. A New Procedure for Detection of Students’ Rapid Guessing Responses Using Response Time , 2016 .
[30] C. Glas,et al. Nonignorable data in IRT models: Polytomous responses and response propensity models with covariates , 2015 .
[31] Daniel L. Oberski,et al. Markov Response Models 1 RUNNING HEAD : Markov Response Models Hidden Markov IRT Models for Responses and Response Times , 2016 .
[32] R. Tibshirani,et al. Forward stagewise regression and the monotone lasso , 2007, 0705.0269.
[33] Johannes Naumann,et al. More is not Always Better: The Relation between Item Response and Item Response Time in Raven's Matrices , 2015 .
[34] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[35] Sunita Sarawagi,et al. Sequence Data Mining , 2005 .
[36] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[37] R. Tibshirani,et al. Least angle regression , 2004, math/0406456.
[38] W. Meredith. Measurement invariance, factor analysis and factorial invariance , 1993 .
[39] Malik Beshir Malik,et al. Applied Linear Regression , 2005, Technometrics.
[40] H. Bozdogan. Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions , 1987 .
[41] Matthias von Davier,et al. Analytics in International Large-Scale Assessments: Item Response Theory and Population Models , 2013 .
[42] Yulia Dodonova,et al. Faster on easy items, more accurate on difficult ones: Cognitive ability and performance on a task of varying difficulty , 2013 .
[43] Stephen G. Sireci,et al. ON THE RELIABILITY OF TESTLET‐BASED TESTS , 1991 .
[44] N. Thomas,et al. The role of secondary covariates when estimating latent trait population distributions , 2002 .
[45] Samuel Greiff,et al. Computer-generated log-file analyses as a window into students' minds? A showcase study based on the PISA 2012 assessment of problem solving , 2015, Comput. Educ..
[46] Eunike Wetzel,et al. An Alternative Way to Model Population Ability Distributions in Large-Scale Educational Surveys , 2015, Educational and psychological measurement.
[47] Jonathan P. Weeks,et al. Using Response Time Data to Inform the Coding of Omitted Responses , 2016 .
[48] Thomas G. Dietterich. An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization , 2000, Machine Learning.
[49] Eric T. Bradlow,et al. Testlet Response Theory and Its Applications , 2007 .
[50] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[51] Jeffrey N. Rouder,et al. A hierarchical bayesian statistical framework for response time distributions , 2003 .
[52] Daniel Kudenko,et al. Feature Generation for Sequence Categorization , 1998, AAAI/IAAI.
[53] Georg Rasch,et al. Probabilistic Models for Some Intelligence and Attainment Tests , 1981, The SAGE Encyclopedia of Research Design.
[54] Robert J. Mislevy,et al. Randomization-based inference about latent variables from complex samples , 1991 .
[55] H. Akaike. A new look at the statistical model identification , 1974 .
[56] Ana I. González Acuña. An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, Boosting, and Randomization , 2012 .
[57] Bernard P. Veldkamp,et al. Predicting self-monitoring skills using textual posts on Facebook , 2014, Comput. Hum. Behav..
[58] Qiwei He,et al. Screening for posttraumatic stress disorder using verbal features in self narratives: A text mining approach , 2012, Psychiatry Research.
[59] van der Linden,et al. A hierarchical framework for modeling speed and accuracy on test items , 2007 .
[60] Krista Breithaupt,et al. Detecting Differential Speededness in Multistage Testing , 2007 .
[61] Matthias von Davier,et al. Imputing Proficiency Data under Planned Missingness in Population Models , 2013 .
[62] J. Fox,et al. Bayesian tests of measurement invariance. , 2012, The British journal of mathematical and statistical psychology.
[63] Yi-Hsuan Lee,et al. Using response time to investigate students' test-taking behaviors in a NAEP computer-based study , 2014, Large-scale Assessments in Education.
[64] Qiwei He,et al. Automated Assessment of Patients’ Self-Narratives for Posttraumatic Stress Disorder Screening Using Natural Language Processing and Text Mining , 2017, Assessment.
[65] Anja S. Göritz,et al. Sometimes More Is Better, and Sometimes Less Is Better: Task Complexity Moderates the Response Time Accuracy Correlation , 2016 .
[66] Matthias von Davier,et al. Investigation of model fit and score scale comparability in international assessments , 2011 .
[67] John Mazzeo. The Use of Collateral Information in Proficiency Estimation for the Trial State Assessment. , 1992 .
[68] R. Millsap. Testing Measurement Invariance Using Item Response Theory in Longitudinal Data: An Introduction , 2010 .