中国电化教育
中國電化教育
중국전화교육
CET CHINA EDUCATIONAL TECHNOLOGY
2015年
5期
84-89
,共6页
赵蔚%姜强%王朋娇%王丽萍
趙蔚%薑彊%王朋嬌%王麗萍
조위%강강%왕붕교%왕려평
本体%个性化%e-Learning%基于知识推荐%知识资源
本體%箇性化%e-Learning%基于知識推薦%知識資源
본체%개성화%e-Learning%기우지식추천%지식자원
Ontology%Individuation%e-Learning%Knowledge Based Recommender Technique%Knowledge Resource
e-Learning重要特点就是能够根据学习者特性、需求,适应性呈现学习资源和学习路径,实现个性化学习,有效促进学习目标达成。为实现e-Learning知识资源个性化推荐,该文采用基于知识推荐技术,同时基于本体技术创建学习者知识和知识资源,在教学模式的指导下实现知识资源个性化推荐。实验结果表明:学生能够很好理解本体概念,愿意学习本体知识,同时认为本体驱动的知识资源个性化推荐很有用,能够满足个性化学习需求、激发学习者学习动机、增强网络自主学习能力及优化学习过程。本文研究的意义:一是基于学习者特征讨论了合适的推荐技术;二是设计了学习者知识和学习资源的通用本体;三是为知识资源个性化推荐设计了有效指导教学模式。
e-Learning重要特點就是能夠根據學習者特性、需求,適應性呈現學習資源和學習路徑,實現箇性化學習,有效促進學習目標達成。為實現e-Learning知識資源箇性化推薦,該文採用基于知識推薦技術,同時基于本體技術創建學習者知識和知識資源,在教學模式的指導下實現知識資源箇性化推薦。實驗結果錶明:學生能夠很好理解本體概唸,願意學習本體知識,同時認為本體驅動的知識資源箇性化推薦很有用,能夠滿足箇性化學習需求、激髮學習者學習動機、增彊網絡自主學習能力及優化學習過程。本文研究的意義:一是基于學習者特徵討論瞭閤適的推薦技術;二是設計瞭學習者知識和學習資源的通用本體;三是為知識資源箇性化推薦設計瞭有效指導教學模式。
e-Learning중요특점취시능구근거학습자특성、수구,괄응성정현학습자원화학습로경,실현개성화학습,유효촉진학습목표체성。위실현e-Learning지식자원개성화추천,해문채용기우지식추천기술,동시기우본체기술창건학습자지식화지식자원,재교학모식적지도하실현지식자원개성화추천。실험결과표명:학생능구흔호리해본체개념,원의학습본체지식,동시인위본체구동적지식자원개성화추천흔유용,능구만족개성화학습수구、격발학습자학습동궤、증강망락자주학습능력급우화학습과정。본문연구적의의:일시기우학습자특정토론료합괄적추천기술;이시설계료학습자지식화학습자원적통용본체;삼시위지식자원개성화추천설계료유효지도교학모식。
According to learner characteristics and requirements, adaptive learning resources and learning path may enhance individual learning in e-Learning. Knowledge based recommender technique and ontological approach are used in this paper for the personal knowledge resources push. The results show that students can understand ontology and think that ontology-driven personalized recommendation of knowledge resource which may satisfy individual learning requirements, stimulate learning motivations, promote learner autonomy and optimize study process is very useful. The first significant property of this study is discussing the appropriate recommendation technology based on learner characteristics. The second property is designing the common ontology of the learner and knowledge resources. The third property is building the effective teaching mode for knowledge resource personalized recommendation.