Personalized E-learning system with self-regulated learning assisted mechanisms for promoting learning performance

Chen, Chin‐Ming

doi:10.1016/j.eswa.2008.11.026

Cited by 128 publications

(76 citation statements)

References 14 publications

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“…Many of the publications in the past and present proceedings of the IEEE International Conference on Wireless, Mobile, and Ubiquitous Technologies (WMUTE) confirm these observations [11,12,13,14,15].…”

Section: Eliciting Similarities/differences Of Mlps Between Learners supporting

confidence: 64%

Proposal of a Mobile Learning Preferences Model

Yau

Joy

2010

Int. J. Interact. Mob. Technol.

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Abstract-A model consisting of five dimensions of mobile learning preferences -location, level of distractions, time of day, level of motivation and available time -is proposed in this paper. The aim of the model is to potentially increase the learning effectiveness of individuals or groups by appropriately matching and allocating mobile learning materials/applications according to each learner's type. Examples are given. Our current research investigations relating to this model are described.

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Section: Eliciting Similarities/differences Of Mlps Between Learners supporting

confidence: 64%

Proposal of a Mobile Learning Preferences Model

Yau

Joy

2010

Int. J. Interact. Mob. Technol.

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“…Deci, Vallerand, Pelletier, and Ryan (1991) pointed out that SRL and flow (Csikszentmihalyi, 1991) supports the experience of autonomy and selfdetermination. More recent studies concerning flexible and self-regulated learning indicated that hypermedia and new information technology plays an important role in SRL (Chen, 2009;Heiß, Eckhardt, & Schnotz, 2003;Tergan, 2002). Other researchers also observed that online learning environments enable students to experience autonomy (Barnard, Lan, To, Paton, & Lai, 2009) by allowing them to decide when, where, and what they can learn (Cunningham & Billingsley, 2003).…”

Section: • Learning Strategiesmentioning

confidence: 99%

The relationship between flexible and self-regulated learning in open and distance universities

Bergamin

Ziska

Werlen

et al. 2012

IRRODL

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<p>Flexibility in learning provides a student room for volitional control and an array of strategies and encourages persistence in the face of difficulties. Autonomy in and control over one’s learning process can be seen as a condition for self-regulated learning. There are a number of categories and dimensions for flexible learning; following professional publications, time, location, lesson content, pedagogy method, learning style, organization, and course requirements are all elements to consider. Using these categories and the dimensions of flexible learning, we developed and validated a questionnaire for an open and distance learning setting. This article reports on the results from a study investigating the relationship between flexible learning and self-regulated learning strategies. The results show the positive effects of flexible learning and its three factors, time management, teacher contact, and content, on self-regulated learning strategies (cognitive, metacognitive, and resource-based). Groups that have high flexibility in learning indicate that they use more learning strategies than groups with low flexibility.</p>

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“…Chih Ming Chang [16] gave personalized E-learning system with self regulated learning, to improve Performance of elearning system. It is based on Self regulating model given by Zimmerman et.…”

Section: Literature Reviewmentioning

confidence: 99%

“…System component of [16] include following Personalized self regulated learning agent:-it has four module namely self monitoring module, self evaluation module, self regulation learning competence indicator module and self regulated learning portfolio learning database. Self monitoring module is used for choosing best strategy for learning and work on how to improve learning.…”

Section: Literature Reviewmentioning

confidence: 99%

A Survey on Semantic Web based E-learning

KumarTiwari¹,

Chaudhary²,

Tomar³

2014

IJCA

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E-learning is method of distance learning using electronic media, in which learner and instructor interacts via learning content present on web. Semantic web is extension of current web. Semantic web attains importance now a day. For implementing the effective e-learning system, Semantic Web appears as a promising technology. Now, it becomes a need to use semantic nature of web in e-learning. Semantic web based e-learning is next generation of e-learning. This paper presents the different kind of e-learning models.

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Personalized E-learning system with self-regulated learning assisted mechanisms for promoting learning performance

Cited by 128 publications

References 14 publications

Proposal of a Mobile Learning Preferences Model

Proposal of a Mobile Learning Preferences Model

The relationship between flexible and self-regulated learning in open and distance universities

A Survey on Semantic Web based E-learning

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