This work presents a study investigating social and curricular factors that lead to student retention and attrition in introductory Computer Science at UC Berkeley. CS10 and CS61A are identified as critical gateway classes in the curricula pipeline. To address the impedance match between the performance of CS10 students in CS61A, a new curricula Data Science unit, with a culturally-relevant learning experience, has been created for CS10. Prelimi- nary results show agreement with theoretical predictions and significant improvement over previous efforts. The central argument of this work is the belief that historically under- represented students in Computer Science increase their affinity for and ability to persist in Computer Science classes
when they feel like what they are learning has some relevance outside the Computer Science classroom. This work introduces a learning framework for the computational exploration of data, within the context of an introductory Computer Science class. The work presented here has profound implications for future studies of how culturally resonant curriculum may one day help solve the problem of low-representation of female and
ethnic minority students in the field of Computer Science.