Defining the Key Components and Criteria Required for the Design and Development of a Learning Analytics Dashboard

The current study aims to identify the essential components and standards necessary for designing and developing Learning Analytics Dashboards (LADs), stemming from the importance of enhancing the role of learning analytics in supporting evidence-based educational decision-making, particularly amidst the rapid digital transformation of electronic learning environments.

The study adopted a descriptive-analytical methodology based on a comprehensive analysis of recent literature and relevant studies concerning learning analytics, LAD design, and educational models such as Self-Regulated Learning (SRL) models and User-Centered Design (UCD) theory. The research procedures involved several methodological steps, beginning with the construction of the theoretical framework, followed by the development of an initial set of standards through a literature review. These standards encompassed four main dimensions: pedagogical, technical, user experience, and ethical considerations, comprising 27 main standards and 135 sub-indicators.

The preliminary list was presented to a panel of experts and educational technology specialists for validation in terms of wording, accuracy, and relevance. Based on their feedback, revisions were made by merging some indicators and rephrasing others. The outcome was a comprehensive final list of validated standards that can be adopted for designing effective LADs, aimed at supporting educators and learners in making data-informed decisions and improving academic performance within digital learning environments.