Susan Embretson

susan.embretson@psych.gatech.edu

Professor of Psychology

404-894-2680

My interests span modern psychometric methods (e.g., item response theory), cognitive and intelligence, and quantitative methods. My main research program has been to integrate cognitive theory into psychometric models and test design. To this goal, I have been developing new item response theory models and conducting empirical research on the cognitive basis of an individual's responses. Recently, this effort has lead to the exciting possibility of "tests without items". That is, items are automatically generated by artificial intelligence to target levels and cognitive sources of difficulty to optimally measure each individual examinee during testing. The measurement areas have included fluid reasoning, spatial ability, mathematical reasoning and verbal comprehension.

Quantitative Lab URL: http://cml.gatech.edu/ lab name: Cognitive Measurement Lab person_type: Faculty Education:

Ph.D. (1973) Psychology University of Minnesota

Selected Publications:
  • Embretson, S. E.  (in press).  The impact of cognitively based item and test development on validity and reliability.  In A. Rupp and J. Leighton (Eds.).  The Handbook of Cognition and Assessment.  New York: Wiley-Blackwell.  
  • Embretson, S. E.  (2015).  The multicomponent latent trait model for diagnosis: Applications to heterogeneous test domains.  Invited paper for Applied Psychological Measurement, 6-30.
  • Morrison, K. & Embretson, S. E. (2014).  Using cognitive complexity to measure psychometric properties of mathematics assessment items.  Multivariate Behavior Research, 49, 1-2. (Abstract).
  • Hayes, H. & Embretson, S. E. (2013). The Impact of Personality and Test Conditions on Mathematical Test Performance. Applied Measurement in Education, 26, 6, 77-88.
  • Embretson, S. E. & Yang, X.  (2013).  A multicomponent latent trait model for diagnosis.  Psychometrika, 78, 14-36.   

  • Embretson, S. E. (2016). Understanding examinees’ responses to items:  Implications for measurement.  Educational Measurement: Issues and Practice, 35, pp.6-22.  

  • Embretson, S. E., Morrison, K. & Jun, H. W. (2015).  Reliability of diagnosing broad and narrow skills with the multicomponent latent trait model: A study of middle school mathematics.   In L.  Andries van der Ark, Daniel M. Bolt, Wen-Chung Wang, Jeffrey M. Douglas, Sy-Miin Chow (Eds).  Quantitative Psychology Research.   New York: Springer.

  • Morrison, K. & Embretson, S. E. (2015).  Item generation.  In P. Irwing, T. Booth & D. Hughes (Eds.), The Wiley Handbook of Psychometric Testing. London: John Wiley & Sons.

  • Gillmor, S. C., Poggio, J. & Embretson, S. E. (2015).  Effects of reducing the cognitive load of mathematics items on student performance. Numeracy, 8, Article 4 .  

  • Morrison, K. & Embretson, S. E. (2014).  Using cognitive complexity to measure psychometric properties of mathematics assessment items.  Multivariate Behavior Research, 49, 1-2. 

  • Embretson, S. E. & Poggio, J.  (2012). The impact of scaling and measurement methods on  individual differences in growth.    In L. Laursen, T. Little n& N. Card (Eds).  Handbook of Developmental Research Methods.  New York: Guilford Press.