开放教育研究
開放教育研究
개방교육연구
OPEN EDUCATION RESEARCH
2014年
5期
67-74
,共8页
学习分析%个性化学习%学习支持系统%智能代理
學習分析%箇性化學習%學習支持繫統%智能代理
학습분석%개성화학습%학습지지계통%지능대리
learning analytics%personalized learning%learning management system%intelligent agents
个性化学习平台是实现“智慧学习”的前提，而依托大数据的学习分析技术则是构建实用性强的个性化学习平台的重要保障。然而，目前学习分析技术仍处在发展阶段，相关文献表明现有研究主要集中于理论综述和应用分析，多侧重于基于学习管理系统的数据采集与分析，面向基础教育的成熟应用案例稀少。本研究以基础教育中的智慧学习为应用背景，尝试基于学习分析的动态采集、精确分析、可视化反馈等构建个性化学习平台，以实现信息技术支持下的“因材施教”。文章从个性化学习的实施要素和学习分析的过程出发，探讨了基础教育中基于学习分析实现个性化学习的思路，即在传统的“一对多”课堂传播环境中采用教师引导的基于分层的群组个性化学习，在“一对一”的泛在自主学习环境下采用智能Agent伴学的个性化学习，两种方式可无缝切换，并通过层的粒度设置实现统一；进而阐述了平台的框架、学习路径推送策略、功能模块与智能Agent设计；并结合案例介绍了平台的应用情况。数据表明，引入学习分析技术有助于教师量化掌控学情及动态调整教学过程，对学习困难生和优异生的学习动机激发与保持有较显著的积极作用。
箇性化學習平檯是實現“智慧學習”的前提，而依託大數據的學習分析技術則是構建實用性彊的箇性化學習平檯的重要保障。然而，目前學習分析技術仍處在髮展階段，相關文獻錶明現有研究主要集中于理論綜述和應用分析，多側重于基于學習管理繫統的數據採集與分析，麵嚮基礎教育的成熟應用案例稀少。本研究以基礎教育中的智慧學習為應用揹景，嘗試基于學習分析的動態採集、精確分析、可視化反饋等構建箇性化學習平檯，以實現信息技術支持下的“因材施教”。文章從箇性化學習的實施要素和學習分析的過程齣髮，探討瞭基礎教育中基于學習分析實現箇性化學習的思路，即在傳統的“一對多”課堂傳播環境中採用教師引導的基于分層的群組箇性化學習，在“一對一”的汎在自主學習環境下採用智能Agent伴學的箇性化學習，兩種方式可無縫切換，併通過層的粒度設置實現統一；進而闡述瞭平檯的框架、學習路徑推送策略、功能模塊與智能Agent設計；併結閤案例介紹瞭平檯的應用情況。數據錶明，引入學習分析技術有助于教師量化掌控學情及動態調整教學過程，對學習睏難生和優異生的學習動機激髮與保持有較顯著的積極作用。
개성화학습평태시실현“지혜학습”적전제，이의탁대수거적학습분석기술칙시구건실용성강적개성화학습평태적중요보장。연이，목전학습분석기술잉처재발전계단，상관문헌표명현유연구주요집중우이론종술화응용분석，다측중우기우학습관리계통적수거채집여분석，면향기출교육적성숙응용안례희소。본연구이기출교육중적지혜학습위응용배경，상시기우학습분석적동태채집、정학분석、가시화반궤등구건개성화학습평태，이실현신식기술지지하적“인재시교”。문장종개성화학습적실시요소화학습분석적과정출발，탐토료기출교육중기우학습분석실현개성화학습적사로，즉재전통적“일대다”과당전파배경중채용교사인도적기우분층적군조개성화학습，재“일대일”적범재자주학습배경하채용지능Agent반학적개성화학습，량충방식가무봉절환，병통과층적립도설치실현통일；진이천술료평태적광가、학습로경추송책략、공능모괴여지능Agent설계；병결합안례개소료평태적응용정황。수거표명，인입학습분석기술유조우교사양화장공학정급동태조정교학과정，대학습곤난생화우이생적학습동궤격발여보지유교현저적적겁작용。
With the popularity of mobile devices, cloud computing and other new technologies, the information tech-nology ecological changes of primary and secondary schools are taking place. Creating a smart learning environment is the most direct way to embrace the changes. A personalized learning platform is a prerequisite to achieve “smart learning”. The technology of learning analytics based on big data is an important solution to build practical personal-ized learning platform because it provides a blueprint for the realization of personalized learning. In the development stage of learning analytics, the literature survey shows the existing research papers mainly focus on the review and a-nalysis of the application . The typical case is mainly focusing on the dynamic acquisition and analysis of an LMS platform. Related application cases in K-12 education is rare. Meanwhile, due to the complex nature of education it-self, the early"intelligent expert systems" experience has shown that teaching which relies entirely on"expert systems"or a "machine mentor" has its deficiencies. Currently, when we try to construct a personalized learning platform, "smart" and"practicality" is still a pair of mutual support and mutual restraints associated variables, and the focus of our work is to find the balance of them. For this reason, we adopted a dynamic granularity group approach to realize personalization. We can control the degree of personalization learning by the granularity. When the granularity is lar-ger than one,the teaching mode is group learning. Otherwise, the teaching model is individualized learning.
