Because non-cognitive constructs can influence student success in education beyond academic achievement, it is essential that they are reliably conceptualized and measured. Within this context, there are several gaps in the literature related to correctly interpreting the meaning of scale scores when a non-standard response option like I do not know (DK) is offered. These include how adolescents utilize and interpret this type of response option and how nominal response models can be used to determine the placement, scoring, and utility of DK response options. The purpose of this dissertation is to add to the limited literature in these areas by analyzing item responses from 5,238 high school students collected during the 2021-2022 academic year. These students, who attend 35 different schools within a large learning network, responded to a Culture Survey that included informational and demographic questions as well as 79 items corresponding to 10 different latent constructs situated within a context of problem-based learning, culturally responsive teaching, and equity pedagogy. The response format continuum provided to participants included a DK response option which makes this data set ideal to investigate not only how adolescents use DK responses but also the efficacy of the nominal response model in determining placement, scoring, and utility of a DK response option. To that end, the data pertaining to three latent constructs--a nine-item scale related to learning environment, a seven-item scale related to learning experiences, and an eight-item scale related to problem-based learning--were examined. Trends in DK response option selection when compared to missing data suggest that participants used the DK response to convey information. This finding provides rationale for the remainder of the study which uses the nominal response model to determine appropriate order and scoring of the DK option so that student scores for these three latent constructs can be properly tallied. Finally, through comparison of fit statistics as well as total information curves for all three constructs, I show that the nominal response model provides a better fit than the more parsimonious graded partial credit model. Results highlight the need to empirically assess the function of all response categories so that latent traits, which can influence student success beyond academic achievement, are accurately assessed. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]