Learning Analytics (LA) is nowadays ubiquitous in many educational systems, providing the ability to collect and analyze student data in order to understand and optimize learning and the environments in which it occurs. On the other hand, the collection of data requires to comply with the growing demand regarding privacy legislation. In this paper, we use the Student Expectation of Learning Analytics Questionnaire (SELAQ) to analyze the expectations and confidence of students from different faculties regarding the processing of their data for Learning Analytics purposes. This allows us to identify four clusters of students through clustering algorithms: Enthusiasts, Realists, Cautious and Indifferents. This structured analysis provides valuable insights into the acceptance and criticism of Learning Analytics among students.

翻译：学习分析（LA）技术如今已广泛存在于众多教育系统中，其通过收集与分析学生数据来理解并优化学习过程及其发生的环境。另一方面，数据收集活动必须符合日益严格的隐私法规要求。本文采用“学生对学习分析的期望问卷”（SELAQ），分析了来自不同院系的学生对于将其数据用于学习分析目的的处理方式所持的期望与信心。通过聚类算法，我们识别出四类学生群体：热情支持者、现实主义者、谨慎观望者和漠不关心者。这一结构化分析为理解学生群体对学习分析技术的接受程度与批评意见提供了有价值的见解。