Many educational institutions use a large number of information systems to automate their activities for different stakeholders’ groups – learning management systems, student diary, library system, digital repositories, management system, etc. This leads to a significant increase in the volume and variety of data that can be captured, stored, and harnessed to improve student learning and school effectiveness. Educational institutions are realising that, with the help of technology, they are collecting data that could be very valuable when properly analysed, aligned with learning outcomes, and integrated into a tighter feedback loop with stakeholders. In addition, the analysis of data can help their managers to take data-driven decision making at all levels of educational institutions. The paper presents a comprehensive approach to Learning Analytics in the field of Secondary Education from the perspective of all different stakeholders, which aims to improve its methods of approaching and analysing learning data. On the basis of a literature review in the field and an investigation of requirements for quality evaluation of learning in school education, the corresponding stakeholder groups are identified - students, teachers, class teachers, managers, parents, inspectors and 6 models (1 model per each stakeholder group) for data collection and personalized and meaningful analysis are proposed for the needs of Learning Analytics. Each model consists of measurable indicators allowing the relevant stakeholder to track data for students’ learning or training for different purposes, e.g. monitoring, analysis, forecast, intervention, recommendations, etc., but finally to improve the quality of learning and teaching processes. The proposed models are evaluated by the representatives of 4 stakeholder groups – students, teachers, class teachers, parents.

许多教育机构使用大量的信息系统来自动化针对不同利益相关者群体的活动-学习管理系统，学生日记，图书馆系统，数字存储库，管理系统等。这导致数量和种类的显着增加。可以捕获，存储和利用的数据，以改善学生的学习和学校效率。教育机构意识到，在技术的帮助下，它们正在收集数据，这些数据在经过适当分析，与学习成果保持一致并与利益相关者紧密联系后，可能非常有价值。此外，数据分析可以帮助他们的管理者在各级教育机构中进行以数据为依据的决策。本文从所有不同利益相关者的角度提出了一种中学教育领域的学习分析的综合方法，旨在改进其处理和分析学习数据的方法。根据该领域的文献综述和对学校教育学习质量评估要求的调查，确定了相应的利益相关者群体-学生，教师，班主任，经理，父母，检查员和6个模型（每个模型1个模型）针对学习分析的需求，提出了用于数据收集以及个性化有意义的分析的每个利益相关者群体）。每个模型均由可衡量的指标组成，这些指标使相关的利益相关者可以跟踪数据，以供学生学习或用于不同目的的培训，例如监测，分析，预测，干预，建议等，但最终提高了学与教过程的质量。提议的模型由4个利益相关者团体（学生，老师，班主任，父母）的代表进行评估。