Justice-centered approaches to equitable computer science (CS) education prioritize the development of students' CS disciplinary identities toward social justice rather than corporations, industry, empire, and militarism by emphasizing ethics, identity, and political vision. However, most research in justice-centered approaches to equitable CS education focus on K-12 learning environments. In this position paper, we problematize the lack of attention to justice-centered approaches to CS in higher education and then describe a justice-centered approach for undergraduate Data Structures and Algorithms that (1) critiques sociopolitical values of data structure and algorithm design and dominant computing epistemologies that approach social good without design justice; (2) centers students in culturally responsive-sustaining pedagogies to resist dominant computing culture and value Indigenous ways of living in nature; and (3) ensures the rightful presence of political struggles through reauthoring rights and problematizing the political power of computing. 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 students not only critique the ethical implications of nominally technical concepts, but also develop greater respect for diverse epistemologies, cultures, and narratives around computing that can help all of us realize the socially-just worlds we need.
翻译:公平计算机科学(CS)教育以公正为中心,将学生的学科特性发展成为社会公正而非公司、工业、帝国和军国主义的学科特征,强调道德、身份和政治远见;然而,对公平计算机教育的以公正为中心的研究大多侧重于K-12学习环境;在本立场文件中,我们对在高等教育中对以公正为中心对待计算机科学的做法缺乏重视感到困惑,然后描述了以公正为中心对待本科生数据结构和算法教学方法,该方法:(1) 批评数据结构和算法设计的社会政治价值观,以及在没有设计公正的情况下对待社会公益的主要计算机学派;(2) 将学生集中在文化上响应性强的以文化为中心,抵制主导计算机文化,重视自然中的土著生活方式;(3) 通过重新授权权利和解决计算机政治权力问题,确保政治斗争的正当存在。 通过对临界比较数据结构的个案研究,以及算术教学方法,我们说,以司法为中心的教育方法不仅有助于学生在文化设计上求得公正,而且有助于他们更深刻地认识世界的伦理学影响。