  Prior work has argued for a more justice-centered approach to postsecondary
computing education by emphasizing ethics, identity, and political vision. In
this experience report, we examine how postsecondary students of diverse gender
and racial identities experience a justice-centered Data Structures and
Algorithms designed for undergraduate non-computer science majors. Through a
quantitative and qualitative analysis of two quarters of student survey data
collected at the start and end of each quarter, we report on student attitudes
and expectations.
  Across the class, we found a significant increase in the following attitudes:
computing confidence and sense of belonging. While women, non-binary, and other
students not identifying as men (WNB+) also increased in these areas, they
still reported significantly lower confidence and sense of belonging than men
at the end of the quarter. Black, Latinx, Middle Eastern and North African,
Native American, and Pacific Islander (BLMNPI) students had no significant
differences compared to white and Asian students.
  We also analyzed end-of-quarter student self-reflections on their fulfillment
of expectations prior to taking the course. While the majority of students
reported a positive overall sentiment about the course and many students
specifically appreciated the justice-centered approach, some desired more
practice with program implementation and interview preparation. We discuss
implications for practice and articulate a political vision for holding both
appreciation for computing ethics and a desire for professional preparation
together through iterative design.
