Actionable Insights of Learning Analytics:Connotation Understanding and Conceptual Structure
Mainstream learning analytics focuses on instrumental rationality,such as data collection,analysis and mining,and algorithmic modeling,while the value rationality research on how to use learning analytics has been overlooked.As a result,there is a significant imbalance between instrumental rationality and value rational-ity on the development and utilization of educational data elements.Therefore,this study conceptualizes the val-ue rationality goal of learning analytics,which is referred to as"actionable insights".Then,the connotation of actionable insights is clarified,the conceptual structure of actionable insights is constructed,the narrative fea-tures of actionable insights are characterized,and the analytical reasoning processes and design strategies that support the generation of actionable insights are proposed.The study argues that actionable insights represent meaningful knowledge or information that can be acted upon by end-users from learning analytics,including four hierarchical components:factual,interpretive,reflective and actionable insights.To effectively support the generation of actionable insights,it is recommended to adopt user-centered participatory design methods,incorpo-rate the design concept of data storytelling,and integrate educational theories or learning constructs when de-signing and developing learning analytics systems.
NETL
NSTL
万方数据
