Justice-centered approaches to equitable computer science (CS) education frame CS learning as a means for advancing peace, antiracism, and social justice rather than war, empire, and corporations. However, most research in justice-centered approaches in CS education focus on K-12 learning environments. In this position paper, we review justice-centered approaches to CS education, problematize the lack of justice-centered approaches to CS in higher education in particular, and describe a justice-centered approach for undergraduate Data Structures and Algorithms. Our approach emphasizes three components: (1) ethics: critiques the sociopolitical values of data structure and algorithm design as well as the underlying logics of dominant computing culture; (2) identity: draws on culturally responsive-sustaining pedagogies to emphasize student identity as rooted in resistance to the dominant computing culture; and (3) political vision: ensures the rightful presence of political struggles by reauthoring rights to frame CS learning as a force for social justice. Through a case study of this Critical Comparative Data Structures and Algorithms pedagogy, we argue that justice-centered approaches to higher CS education can help all computing students not only learn about the ethical implications of nominally technical concepts, but also develop greater respect for diverse epistemologies, cultures, and experiences surrounding computing that are essential to creating the socially-just worlds we need.
翻译:公平计算机科学(CS)教育的公正方针(CS) 公平计算机科学(CS)教育的公正方针(CS) 将CS 学习作为促进和平、反种族主义和社会正义而不是战争、帝国和公司的手段。然而,CS 教育中的大多数以司法为中心的方法研究侧重于K-12学习环境。在本立场文件中,我们审查了以司法为中心的教育方法(CS),特别是高等教育中缺乏以司法为中心的方法(CS),并介绍了本科本科数据结构和阿尔戈里希姆的以司法为中心的方法(CS) 。我们的方法强调三个组成部分:(1) 道德:批评数据结构和算法设计的社会政治价值观以及主导计算文化的基本逻辑;(2) 身份:利用文化上适应和可维持的教学方法强调学生的认同,因为学生对主导计算文化文化的抵制;(3) 政治愿景:通过重新授权CS 学习成为社会公正的力量,确保政治斗争的正当存在。通过对这个临界比较数据结构和算术的案例研究,强调三个组成部分:(1) 道德结构和算法设计,以及主导计算计算机文化的基本逻辑,我们只能学习更深刻的CS 。