This dissertation builds upon a systematic literature review conducted by my supervisors (Topali, P., Ortega-Arranz, A., Rodríguez-Trianaet al. Designing human-centered learning analytics and artificial intelligence in education solutions: a systematic literature review. 2024), which focused on empirical studies involving the design, development, and implementation of human-centered learning analytics and artificial intelligence tools in education. From the articles included in that review, a subset of relevant tools was identified through an initial screening process. These tools were then analyzed to better understand their features and provide stakeholders with a structured overview of available systems that align with human-centered principles in Learning Analytics. The methodology adopted for this work was inspired by DESMET, enabling a systematic and structured evaluation of tool characteristics. The process involved iterative reading of associated literature, hands-on exploration of the tools, and direct communication with the authors or developers to validate the extracted information. A deductive, top-down classification approach was initially used to define broad categories covering both qualitative and quantitative aspects of the tools. These categories were progressively refined through multiple iterations, following an inductive, bottom-up strategy to enhance internal coherence and thematic clarity. Two rounds of outreach were conducted to validate the collected data, with several authors providing valuable feedback that was incorporated into the final analysis. The outcome is a categorised, feature-based overview of HCLA and HCAI tools, offering practical insights for researchers and practitioners seeking to adopt or further explore human-centered approaches in educational technology. Keywords: Human-Centered Learning Analytics, Human-Centered Artificial Intelligence, Learning Analytics, Human-Centered Design, DESMET, Systematic Analysis, Feature Analysis We defined a number of categories that capture the most important characteristics of each tool. For clarity, we organised the categories into five main groups: Tool Basis - Includes fundamental information about the tool, such as its name, purpose, pedagogical context, and technological aspects. Human-Centered Approach - Focuses on how stakeholders (e.g., students, teachers, researchers) are involved in the tool's development, use, and feedback processes. Data Management - Covers aspects related to data collection, storage, processing, and privacy considerations. Tool Evaluation - Examines how the tool's effectiveness, usability, and impact are assessed. Tool Adoption - Explores the extent to which the tool is used, its sustainability, and its integration into educational settings. Te data is organized into four groups of tabs, each one is formed by the 5 groups mentioned before, to facilitate the management and analysis of the information collectedduring the methodological process (20 in total).1. The first 5 sheets, contain the information collected directly by myself after completingthe iterations described in the methodology process; that is, the raw data.2. The next 5, include tabs with comments and feedback provided by the authors.3. The next 5, comprise tabs where the authors’ contributions have been integratedinto the original data mentioned in point 1, thus combining both sources.4. The last 5 contain normalized or standardized data prepared for thequantitative and qualitative analyses carried out in this study.