Maria Baez Cruz

Boston College Lynch School of Education

Maria Baez Cruz is a Ph.D. candidate in Measurement, Evaluation, Statistics, and Assessment department with interests in policy evaluation and survey methods, in particular, the assessment of hard-to-measure constructs and survey feedback for institutional change. Maria holds a Master’s in International Education Policy from Harvard University, a Master’s in Public Policy in Development from Paris School of Economics and L’École des Hautes Études en Sciences Sociales, and a bachelor’s in Economics from Pontificia Universidad Católica Madre y Maestra.

Dissertation Title: The Measurement of Sociocultural Integration in Schools with Racial/Ethnic, Cultural, and Linguistic Diversity: A Rasch Scale Development

Dissertation Abstract: The focus of Maria’s dissertation is sociocultural integration (SCI), defined as knowledge and acceptance of our identity, attaching value to the identity of others, and engaging with them in equitable relationships. SCI contributes to climate, as it relates to school’s students and staff exposure to messages, behaviors, and norms that influence identity formation and affirmation. She advances the discussion along two lines. First, proposing a definition of sociocultural integration that is inclusive of the existing literature in psychology, education, and sociology. The separation of research on SCI according to racial/ethnic and cultural/linguistic groups and school role, failing to capitalize on their shared features and thwarting efforts to assess interventions on SCI are segmented rather than systemic. Secondly, she operationalizes unified SCI definition, and design a measurement scale using innovative scenario items. Adopting Rasch-based scenario items (Ludlow et. al, 2014) will improve on existing surveys by combining rich item stems, a common anchor for response options to be comparable, and individual results that are linked to theoretical levels of sociocultural integration. These improvements are possible by Guttman’s facet theory (FT) (Guttman & Greenbaum, 1998) combined with sentence mapping to create rich construct-relevant vignette-like items. Having these complex representations of the theoretical levels of the SCI can increase the usability of scores, as well as allowing for the linking between scores on the instrument and professional development.