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学习分析系统(LAS)具有把不同的资源和服务整合来为教育提供最好的实践.学习分析引擎作为这一系统的核心组成部分,目前在功能上的限制,定义上的模糊,以及可扩展性差使其不能扩展到其他内容和机构.本文首先提出了引擎本体(角色、来源、时间和控制)来描述和独特的四种引擎功能:预测、反思、建议和适应,以建立一个共同的语言和实践学习分析引擎,从而改善不同的LA之间的互操作性应用.基于这些本体论的引擎,本研究进一步设计LAS引擎的机制和应用数学模型来解释其分解和重组技术.本文所阐述的学习分析系统引擎,预计可用于开发一个开放和集成的,能够扩大规模和扩展到任何环境中的LAS.
The Learning Analytics System (LAS) has the best practices for education by integrating different resources and services.Learning analytics engines, as a core component of the system, are currently limited in functionality, ambiguity in definitions, and extensible Sex differences make it impossible to extend to other content and institutions.This paper first presents engine ontology (role, source, time and control) to describe and unique four engine functions: prediction, reflection, advice and adaptation to establish a common language And practice learning analytics engine to improve the interoperability of different LA applications.Based on these ontology engines, this study further designs the mechanism of LAS engine and applied mathematical model to explain its decomposition and reorganization technology.In this paper, The Learning Analytics Engine is expected to be used to develop an open and integrated LAS that can scale and scale to any environment.