【摘要】：以用戶需求為中心的個性化學(xué)習(xí)環(huán)境構(gòu)建是e-Learning未來的發(fā)展趨勢,也是當(dāng)前遠(yuǎn)程教育及智慧教育領(lǐng)域研究的熱點。針對個性化e-Learning學(xué)習(xí)環(huán)境的"適應(yīng)性"問題,從用戶認(rèn)知水平維度切入,利用鄰近區(qū)用戶群(鄰居用戶)相似性規(guī)則提出了一種Web環(huán)境下個性化學(xué)習(xí)路徑生成的協(xié)同推薦機(jī)制,并通過架構(gòu)設(shè)計、系統(tǒng)建模、路徑提取及算法設(shè)計四個方面重點剖析了自適應(yīng)學(xué)習(xí)系統(tǒng)(Adaptive Learning System,ALS)協(xié)同推薦機(jī)制的技術(shù)解決方案,通過系列實驗設(shè)計、實施以及數(shù)據(jù)分析對其有效性進(jìn)行了驗證。結(jié)果表明,本研究成果在一定程度上能夠向目標(biāo)用戶推薦較理想的學(xué)習(xí)路徑,有效改善推薦資源的精準(zhǔn)度,進(jìn)而提高用戶學(xué)習(xí)質(zhì)量和學(xué)習(xí)效果。
[Abstract]:The construction of personalized learning environment centered on user needs is the development trend of e-Learning in the future, and it is also a hot spot in the field of distance education and intelligent education. Aiming at the problem of "adaptability" in the personalized e-Learning learning environment, we cut into the dimension of user's cognitive level, This paper proposes a collaborative recommendation mechanism for personalized learning path generation in Web environment by using the similarity rules of adjacent user groups (neighborhood users), and models the system through architecture design. The technical solution of cooperative recommendation mechanism of adaptive learning system (Adaptive Learning System,ALS) is analyzed in four aspects of path extraction and algorithm design, and its validity is verified by a series of experiments, implementation and data analysis. The results show that to some extent, the research results can recommend the ideal learning path to the target users, improve the accuracy of the recommended resources effectively, and then improve the learning quality and learning effect of the users.
【作者單位】： 廣西教育學(xué)院教育技術(shù)與信息管理中心;華南師范大學(xué)教育信息技術(shù)學(xué)院;
【基金】：廣西教育教學(xué)改革省級重點項目“面向移動終端設(shè)備的自適應(yīng)網(wǎng)絡(luò)學(xué)習(xí)平臺關(guān)鍵技術(shù)研究與實踐”(項目編號:2014JGZ151) 廣西教育科學(xué)“十二五”規(guī)劃教育信息化專項課題“基于混合式培訓(xùn)模式的廣西中小學(xué)教師信息技術(shù)應(yīng)用能力培訓(xùn)資源建設(shè)與應(yīng)用研究”(項目編號:2015ZXY22)的研究成果
【分類號】：G434
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本文編號：2429824