Multimodal Learning Analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements in MMLA have shown its capability to generate insights into diverse learning behaviours across various learning settings, little research has been conducted to evaluate these systems in authentic learning contexts, particularly regarding students' perceived fairness, accountability, transparency, and ethics (FATE). Understanding these perceptions is essential to using MMLA effectively without introducing ethical complications or negatively affecting how students learn. This study aimed to address this gap by assessing the FATE of MMLA in an authentic, collaborative learning context. We conducted semi-structured interviews with 14 undergraduate students who used MMLA visualisations for post-activity reflection. The findings highlighted the significance of accurate and comprehensive data representation to ensure visualisation fairness, the need for different levels of data access to foster accountability, the imperative of measuring and cultivating transparency with students, and the necessity of transforming informed consent from dichotomous to continuous and measurable scales. While students value the benefits of MMLA, they also emphasise the importance of ethical considerations, highlighting a pressing need for the LA and MMLA community to investigate and address FATE issues actively.

翻译：多模态学习分析（MMLA）融合了新型传感技术与人工智能算法，为增强学生在复杂协作学习过程中的反思能力提供了机遇。尽管近年MMLA研究已展现出其在多样化学习场景中洞察多元学习行为的潜力，但鲜有研究在真实学习情境中评估这些系统，特别是在学生对公平性、问责性、透明性与伦理性（FATE）的感知方面。理解这些感知对于在避免引入伦理问题或影响学生学习效果的前提下有效使用MMLA至关重要。本研究旨在通过评估真实协作学习情境中MMLA的FATE来填补这一空白。我们对14名使用MMLA可视化工具进行活动后反思的本科生开展了半结构化访谈。研究结果揭示了以下关键要素：确保可视化公平性需要准确且全面的数据表征；促进问责性需要不同层级的数据访问权限；必须测量并培养学生对透明性的感知；同时需将知情同意从二元选择转变为连续可测量的量表。尽管学生认可MMLA的益处，但他们同样强调伦理考量至关重要，这凸显了学习分析（LA）与MMLA社区亟需主动研究并解决FATE相关问题。