• Research Interests

  • I am fascinated by human learning.  Today, nearly every educator inherently understands that different students seem to learn at different rates, or that different domains are better taught using differing instructional methods. But how do these profound differences come to be? How can we best leverage instructional resources to support the academic development of all students?

    In order to begin to address these questions, I apply advanced quantitative methodologies to educational data in an effort to scientifically understand the learning process: including when, how, and in whom learning occurs. Recently, I have worked to co-develop a novel methodical paradigm, called Dynamic Measurement Modeling (DMM) that may be used to quantify students’ learning capacity in a more valid way than previously used methods.

    Moreover, I have closely studied two higher-order cognitive functions that allow individuals to flexibly adapt to shifting demands, and innovate around constraints and challenges: relational reasoning and creativity. In particular, I am interested in the reliable and valid measurement of these constructs, as well as the role they play in student success, especially in STEM fields. For example, I have studied how medical students and residents use relational reasoning to arrive at clinical diagnoses, as well as how engineering students creatively solve mechanical problems.

  • Selected Recent Papers

  • Dynamic Measurement Modeling

    McNeish, D., & Dumas, D. (in press). Calculating the conditional reliability of dynamic measurement modeling capacity estimates. Journal of Educational Measurement.

    Dumas, D., & McNeish, D. (2018). Increasing the consequential validity of reading assessment using dynamic measurement modeling. Educational Researcher.

    DumasD., McNeish, D., (2017). Dynamic measurement modeling: Using nonlinear growth models to estimate student learning capacity. Educational Researcher, 46(6), 284-292. DOI: 10.3102/0013189X17725747

    McNeish, D., & DumasD. (2017). Non-linear growth models as psychometric models: A second-order growth curve model for measuring potential. Multivariate Behavioral Research, 52, 61-85. https://doi.org/10.1080/00273171.2016.1253451

  • Dumas&McNeish2018.pdf

  • Dumas & McNeish 2017.pdf

  • McNeish & Dumas (2017) MBR.pdf

  • Creativity

    Dumas, D. & Runco, M. (in press). Objectively scoring divergent thinking tests for originality: A re-analysis and extension. Creativity Research Journal.

    Dumas, D., Strickland, A. (in press). From book to bludgeon: A closer look at malevolent responses on the Alternate Uses Task. Creativity Research Journal.

    Dumas, D. (2018). Understanding high-school students’ perceptions of their learning opportunities: A doubly latent approach. Frontiers in Education: Educational Psychology.

    Dumas, D. (2018). Relational reasoning and divergent thinking: An examination of the threshold hypothesis using quantile regression. Contemporary Educational Psychology, 53, 1-196.

    Dumas, D., Schmidt, L. C., & Alexander, P. A. (2016). Predicting creative problem solving in engineering design. Thinking Skills and Creativity21, 50–66. http://doi.org/10.1016/j.tsc.2016.05.002

    Dumas, D., & Dunbar, K. N. (2016).  The creative stereotype effect. PLOS ONE. DOI: 10.1371/journal.pone.0142567

    Dumas, D., & Dunbar, K. N. (2014). Understanding fluency and originality: A latent variable perspective. Thinking Skills and Creativity, 14, 56-67.

  • Dumas2018b.pdf

  • Dumas2018.pdf

  • Dumas, Schmidt, & Alexander, 2016.pdf

  • Dumas&Dunbar2016.PDF

  • Dumas&Dunbar2014.pdf

  • Relational Reasoning

    Dumas, D., Alexander, P.A. (2018). Assessing differential-item-functioning on the Test of Relational Reasoning. Frontiers in Education: Testing and Applied Measurement. https://doi.org/10.3389/feduc.2018.00014

    Dumas, D., Torre, D.M., Durning, S.J. (2018).  Using relational reasoning strategies to help improve clinical reasoning practice.  Academic Medicine. 93(5):709-714. doi: 10.1097/ACM.0000000000002114.

    Dumas, D. (2017).  Relational reasoning in science, medicine, and engineering. Educational Psychology Review. http://doi.org/10.1007/s10648-016-9370-6

    Grossnickle, E. M., Dumas, D., Alexander, P. A., & Baggetta, P. (2016). Individual differences in the process of relational reasoning. Learning and Instruction42, 141–159. http://doi.org/10.1016/j.learninstruc.2016.01.013

    Dumas, D., Alexander, P. A. (2016). Calibration of the Test of Relational Reasoning. Psychological Assessment, 28(10), 1303-1318. http://doi.org/10.1037/pas0000267

    Jablansky, S., Alexander, P.A., Dumas, D., & Compton, V. (2015). Development of relational reasoning in primary and secondary school students.  Journal of Educational Psychology, 108(4), 592-608http://doi.org/10.1037/edu000007

    Dumas, D., & Schmidt, L. (2015). Relational reasoning as predictor for engineering ideation success using TRIZ. Journal of Engineering Design. 26(3), 74–88

    Alexander, P. A., Dumas, D., Grossnickle, E. M., List, A., & Firetto, C. (2015). Measuring relational reasoning. Journal of Experimental Education, 83, 1-33.

    Dumas, D., Alexander, P. A., Baker, L. M., Jablansky, S., & Dunbar, K. N. (2014). Relational reasoning in medical education: Patterns in discourse and diagnosis. Journal of Educational Psychology, 106, 1021-1035. doi: 10.1037/a003677

    Dumas, D., Alexander, P. A., & Grossnickle, E. M. (2013). Relational reasoning and its manifestations in the educational context: A systematic review of the literature. Educational Psychology Review, 25, 391-427.

  • Dumas, Durning, & Torre, 2018.pdf

  • Dumas&Alexander2018.pdf

  • Dumas2016.pdf

  • Grossnickleetal2016.pdf

  • Dumas&Alexander2016.pdf

  • Jablansky et al 2015.pdf

  • Dumas&Schmidt2015.pdf

  • Alexander et al. 2015.pdf

  • Dumas, Alexander, Baker, Jablansky, Dunbar, 2014

  • Dumas, Alexander, Grossnickle, 2013.pdf

This portfolio last updated: 28-Nov-2018 11:38 AM