Thesis advisor: Michael Russell / The growth of computer-based testing over the last two decades has motivated the creation of innovative item formats. It is often argued that technology-enhanced items (TEIs) provide better measurement of test-takers’ knowledge, skills, and abilities by increasing the authenticity of tasks presented to test-takers (Sireci & Zenisky, 2006). Despite the popularity of TEIs in operational assessments, there remains little psychometric research on these innovative item formats. Claims regarding their potential to provide better measurement are seldomly explored. This dissertation adds to this limited body of research by developing theory and proposing a methodology to compare TEIs to traditional item formats. This study investigated how to judge the comparative measurement value (CMV) of two drag-and-drop technology-enhanced formats (classification and rank-ordering) relative to stem-equivalent multiple-choice items. Items were administered to a sample of adults and results were calibrated using a 2-parameter logistic IRT model. Moreover, the utility of the TEIs was evaluated according to the TEI Utility Framework (Russell, 2016). Four indicators were identified as the most valuable characteristics to judge CMV and then combined into a hierarchical decision protocol. When applied, this protocol provides a CMV judgment and a recommendation of the preferred item format. Applying the protocol to the items revealed that most TEIs examined in this study showed decreased CMV, indicating that in a real-life scenario the multiple-choice format would be favored for most of these item pairs. Recommendations for the use of the CMV protocol and directions of future related research are discussed. / Thesis (PhD) — Boston College, 2021. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement and Evaluation.