基于境脈感知的同伴推薦研究

內(nèi)容概要

　　This book is organized as follows. Chapter 1 introduces the research background and purposes of this study. Chapter 2 recognizes the theoretical foundations for this study. Chapter 3 explores the e-learning context.Chapter 4 discusses peer interaction in the e-learning context， and suggests that effective peer interaction should be built on the considerations of knowledge relevance， social proximity and technical access between participants. Chapter 5 proposes a three-dimensional CA model for peer recommendation. Chapter 6 describes a CA-supported peer recommendation mechanism， which is based on mining learners activity contexts in e-learning spaces. Chapter 7 presents a prototype case study （PeerFinder）， which implements CA in a weblog system. Further discussion is provided in Chapter 8.

作者簡(jiǎn)介

　　鄭燕林，女，1974年10月15日生，1997年獲東北師范大學(xué)理學(xué)士，2000年獲東北師范大學(xué)教育學(xué)碩士學(xué)位，2002年獲日本文部省獎(jiǎng)學(xué)金公派留學(xué)日本，于2006年獲得日本國(guó)立德島大學(xué)信息系統(tǒng)工學(xué)博士學(xué)位。自2000年在東北師范大學(xué)任教?，F(xiàn)為東北師范大學(xué)傳媒科學(xué)學(xué)院教育技術(shù)學(xué)系副教授、副系主任、碩士生導(dǎo)師?！　∧壳爸饕獜氖翪SCL、泛在學(xué)習(xí)（ubiquitous learning）系統(tǒng)設(shè)計(jì)與開(kāi)發(fā)、網(wǎng)絡(luò)環(huán)境下知識(shí)管理能力發(fā)展相關(guān)研究。近年來(lái)，共發(fā)表中英文學(xué)術(shù)論文50余篇，其中包括SSCI、EI、ISTP、CSSCI檢索論文。

書(shū)籍目錄

Chapter 1 Introduction1.1 Research Background1.2 Purpose of this Study1.3 Book OverviewChapter 2 Theoretical Foundation of this Study2.1 Social Constructivism Theory2.2 Social Information Processing Theory2.3 Activity TheoryChapter 3 The e-Learning Context3.1 Two Concepts3.1.1 Context3.1.2 e-Learning3.2 Framework Description of the e-Learning Context3.2.1 Key Elements in e-Learning3.2.2 Learning Process based on Knowledge Transfer3.2.3 Knowledge Goals of e-Learning3.3 Knowledge Context3.4 Social Context3.5 Technical Context3.6 Mediator： Activity Context3.7 Modeling Knowledge, Social, Technical ContextsChapter 4 Peer Interaction in the e-Learning Context4.1 Interaction4.2 Peer Interaction4.3 Computer-Mediated Communication4.4 Computer-supported Collaborative Learning4.5 Virtual Learning Community4.6 Support Potential Online Peer Interaction4.6.1 Knowledge Relevance4.6.2 Social Proximity4.6.3 Technical Mediation4.7 Motivation and Engagement in Peer InteractionChapter 5 Three-dimensional Context-awareness Model for Peer Recommendation5.1 Literatures on Awareness5.1.1 The Concept of Awareness5.1.2 Classifications of Awareness5.1.3 Awareness Models5.1.4 Awareness Technology5.1.5 Knowledge Awareness5.1.6 Context-awareness and its Applications5.2 Three-dimensional Context-awareness Model for Peer Recommendation5.2.1 CA to Knowledge Relevance5.2.2 CA to Social Proximity5.2.3 CA to Technical Access5.3 A Case Study of Learners Percepti9ns toward the CA Model5.3.1 Methodology5.3.2 Results of Questionnaires5.3.3 FindingsChapter 6 Context-awareness Supported Peer Recommendation Mechanism based on Mining Activity Context6.1 Literacy Review on Recommender Systems6.1.1 Information Filtering6.1.2 Content-based Approach for Recommendation6.1.3 Collaborative Filtering Approach for Recommendation6.1.4 SNA-based Approach for Recommendation6.1.5 Cold-start Problem in Recommender Systems6.1.6 Recommender System Assessment6.2 Context Management6.3 Activity Context6.3.1 Classifications of Activity Contexts6.3.2 Modeling Learning Activity Context6.3.3 Content Analysis of Learning Activity6.4 Framework Description of CA-supported Peer Recommendation Mechanism6.5 User Modeling6.6 Context Monitoring6.7 Context Filtering6.8 CA Visualization6.8.1 Information Visualization6.8.2 Social Visualization6.8.3 CA VisualizationChapter 7 A Case Study： PeerFinder7.1 Social Media7.2 Weblogs as the Test-bed7.3 The Design Space for Helping Learners Find Suitable Helpers7.4 System Configuration of PeerFinder7.5 Learning Activity Contexts in Weblogs7.6 Content Analysis in PeerFinder7.7 Recommendation Flow of PeerFinder7.8 Basis Strategies for Context Filtering in PeerFinder7.9 Mining Technical Context7.10 Indicators for CA Filtering7.11 Computing the Similarity among LearnersChapter 8 Discussions8.1 The Extensibility and Flexibility of the CA Model8.2 The Feasibility and Validity of the CA-supported Peer Recommendation Mechanism8.3 More Than Peer Recommendation8.3.1 Inspiration for the Construction of Learning Resources8.3.2 Decreasing the Learning Curve of New Learners8.3.3 Motivating Active and Potential Peer Interaction8.3.4 Inspirations for the Cultivation and hnprovement of Online Learners Learning AbilityChapter 9 Conclusions and Future Research9.1 Conclusions9.2 Future ResearchBibliography

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