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    Title: Personalized E-Learning System with Self-Regulated Learning Assisted Mechanisms for Promoting Learning Performance
    Authors: 陳志銘
    Chen, Chih-Ming;Huang, Ting-Chun;Li, Tai-Hung;Huang, Chia-Meng
    Date: 2007-01
    Issue Date: 2010-10-06 11:37:12 (UTC+8)
    Abstract: With the rapid development of Internet technologies, the conventional computer-assisted learning (CAL) is gradually moving toward to web-based learning. Additionally, instructors typically base their teaching methods to simultaneously interact with all learners in a class based on their professional disciplines in the traditional classroom learning. However, the requirements of individual learners are frequently ignored in the traditional classroom learning. Compared to the conventional classroom learning, individual learners are the focus in web-based learning environments and many web-based learning systems provide personalized learning mechanisms for individual learners. One key problem is that learners have to frequently interact with web-based learning systems even though they lack instructors to monitor their learning attitudes and behavior during learning processes. Hence, a learner’s ability to self-regulated learning is clearly an important factor affecting learning performance in a web-based learning environment. Self-regulated learning is a goal-oriented learning strategy that is very suited to self-managed learning to promote learning performance of individual learners in a web-based learning environment. However, how to assist learners in cultivating self-regulated learning abilities efficiently is an important research issue in the self-regulated learning field. This study presents a novel personalized e-learning system with self-regulated learning assisted mechanisms that help learners enhance their self-regulated learning abilities. The proposed self-regulated learning mechanisms assist learners in becoming lifelong learners who have autonomous self-regulated learning abilities. Additionally, four self-regulated learning types, based on a self-regulated learning competence index and self-regulated learning performance index, are also proposed. Experimental results demonstrate that the proposed self-regulated learning assisted mechanisms aid learners by speeding up their acquisition of self-regulated learning abilities in a personalized e-learning system, and help their learning performance.
    Relation: IEEE International Conference on Advanced Learning Technologies
    Data Type: conference
    Appears in Collections:[Graduate Institute of Library, Information and Archival Studies] Proceedings

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