Human-Centered learning analytics (HCLA) is an approach that emphasizes the human factors in learning analytics and truly meets user needs. User involvement in all stages of the design, analysis, and evaluation of learning analytics is the key to increase value and drive forward the acceptance and adoption of learning analytics. Visual analytics is a multidisciplinary data science research field that follows a human-centered approach and thus has the potential to foster the acceptance of learning analytics. Although various domains have already made use of visual analytics, it has not been considered much with respect to learning analytics. This paper explores the benefits of incorporating visual analytics concepts into the learning analytics process by (a) proposing the Learning Analytics and Visual Analytics (LAVA) model as enhancement of the learning analytics process with human in the loop, (b) applying the LAVA model in the Open Learning Analytics Platform (OpenLAP) to support humancentered indicator design, and (c) evaluating how blending learning analytics and visual analytics can enhance the acceptance and adoption of learning analytics, based on the technology acceptance model (TAM).

翻译：人本学习分析（HCLA）是一种强调学习分析中人为因素并真正满足用户需求的方法。用户参与学习分析设计、分析和评估的各个阶段是提升价值、推动学习分析接受与采纳的关键。可视化分析是一门遵循人本方法的多学科数据科学研究领域，因此具有促进学习分析接受的潜力。尽管多个领域已应用可视化分析，但它在学习分析中的研究尚不充分。本文通过以下方式探讨将可视化分析概念融入学习分析过程的益处：（a）提出学习分析与可视化分析（LAVA）模型，作为引入人机协同环节的学习分析过程增强方案；（b）在开放学习分析平台（OpenLAP）中应用LAVA模型，支持人本化指标设计；（c）基于技术接受模型（TAM）评估学习分析与可视化分析的融合如何提升学习分析的接受度与采纳率。