Various instruments exist in the computer science education landscape to measure student attitudes about themselves or the field. We recognize the importance to reevaluate an instrument for a new sample, particularly when that sample oversamples women, and students from historically marginalized groups in computer science. We adapted two instruments from the CS education literature on identity and sense of belonging as part of a larger study exploring undergraduate student pathways and experiences in computer science and tech programs. Several changes were made to these instruments to improve generalizability towards our audience and interpretability of our results. After analyzing the reliability and how well the survey items align with their theorized constructs, we analyzed the difference in computer science identity and belonging by binary gender and race/ethnicity. We found significant differences by binary gender for both identity and belonging, but only found significant differences by race/ethnicity for identity. Our alterations in the instruments have implications for diverse populations.