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