A Framework for Adaptive e-Learning Systems in Higher Education with Information Visualization

Sasakura, Mariko; Yamasaki, Susumu

doi:10.1109/iv.2007.11

Cited by 11 publications

(7 citation statements)

References 9 publications

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“…; representing the widely recognised alternative to the one size fits all approach [23]. Several proposals can be found in literature [24][25][26][27][28][29][30], where adaptivity ranges from simple resource sharing and reusing of the definition of a learning path tailored on student profile; among these, an interesting project is endorsed by the Ariadne [22] foundation, which proposes the Knowledge Pool System to manage and reuse learning resources [31,32].…”

Section: Related Workmentioning

confidence: 99%

Reliable peers and useful resources: Searching for the best personalised learning path in a trust- and recommendation-aware environment

Carchiolo

Longheu

Malgeri

2010

Information Sciences

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Section: Related Workmentioning

confidence: 99%

Reliable peers and useful resources: Searching for the best personalised learning path in a trust- and recommendation-aware environment

Carchiolo

Longheu

Malgeri

2010

Information Sciences

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“…Furthermore, although adaptive techniques may support the achievement of specific educational goals, these goals are restricted for the majority of existing systems to the domain scope of the available content (Brusilovsky et al, 2007;Meccawy et al, 2007). In addition, authoring tools help to create specific content alternatives (Sasakura & Yamasaki, 2007), but it is practically impossible to take the aforementioned complex situation of learner characteristics into consideration.…”

Section: Content-based Aspectsmentioning

confidence: 99%

The DEKOR System

Guetl

Garcia-Barrios

2009

Cognitive and Emotional Processes in Web-Based Education

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Due to the wide diversity of learning styles and learner characteristics, delivering learning material from modern ICT-based learning must also be conducted in a diverse manner rather than with a “one-fitsall” approach. By focusing on content aspects, the majority of adaptive Web-based educational systems are only able to deal with closed repositories and therefore only pre-defined content alternatives for limited learner characteristics are manageable. One possible solution is to enable and technologically support students’ freedom to select appropriate learning content of their own choice. The WWW as an extensive repository of diverse content has gained considerable interest as an open-ended learning environment, but most students cannot cope well with such open accessibility. To overcome this, the authors have started research towards a system of personalized access to open repositories. In this book chapter, they introduce the evolution of their linked approaches and discuss the findings in the context of learner characteristics.

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“…E-learning systems are now widely accepted because it has the flexibility to adjust content, which will be up to date, provides an opportunity for everyone to learn and gives freedom of research without restrictions of time and location [1]. In addition, e-learning systems are also used as a communication tool between teacher and learner by using modern communication tools such as e-mail, web-board, chat, etc [2]. However, although e-learning is very useful, some e-learning systems are a self-learning system with no influence of achievement for the learner.…”

Section: Introductionmentioning

confidence: 99%

“…And traditional e-learning systems tend to lead to boredom, slow down of learning and underachieving. Therefore, the solution for an effective e-learning system is the development of an adaptive e-learning system [2] by focusing on the learner's learning style. Learning style means the physical characteristic, thought and feeling that individual uses to perceive, responsiveness and interaction with a stable environment.…”

Section: Introductionmentioning

confidence: 99%

Conceptual Framework of a Synthesized Adaptive e-Learning and e-Mentoring System Using VARK Learning Styles with Data Mining Methodology

Pantho¹,

Tiantong²

2015

IJCTE

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Abstract-Currently, e-learning systems are becoming more popular. This is because e-learning systems provide learners freedom to study with unlimited time and at any location. But, most of the e-learning systems present the same learning content without regard to different learning styles of learners. Many learners have to adapt to different learning styles such as learning content from images which is not specifically targeted at their needs. Meanwhile, other learners may have aptitude in reading or from listening, etc. Therefore, learning and teaching processes are important issues that teachers need to adjust their teaching according to individual learners. If each learner obtains content that aligns with their own learning style, it will lead to more achievement.The purpose of this research is to synthesize the learning model of adaptive e-learning and e-mentoring system in order to recommend learners and analyze the VARK learning style (VARK is an acronym for visual, aural, read/write, and kinesthetic) by using data mining methodology. The synthesized model consists of four modules which are 1) esaB eluR KRAV eludoM2) VARK Learner Module 3) Content Module and 4) Learning Module.Index Terms-E-learning, adaptive learning, learning style, VARK learning style. I. INTRODUCTIONLearning and teaching by using the e-learning system is a way to enhance learning and teaching capacity. The E-learning system is an evolution of information technology, network technology and multimedia technology to achieve maximum efficiency in education. E-learning systems are now widely accepted because it has the flexibility to adjust content, which will be up to date, provides an opportunity for everyone to learn and gives freedom of research without restrictions of time and location [1]. In addition, e-learning systems are also used as a communication tool between teacher and learner by using modern communication tools such as e-mail, web-board, chat, etc [2]. However, although e-learning is very useful, some e-learning systems are a self-learning system with no influence of achievement for the learner. Some learners may take more time than others to study contents as each learner has different ability to gain knowledge. The recognition of learner depends on individual factors, including experience, interest, aptitude, knowledge, wisdom, and learning plan. These factors influence the learning speed. In traditional e-learning systems, the focus was on the development of presentation rather than the consideration of individuality [3]. And traditional e-learning systems tend to lead to boredom, slow down of learning and underachieving. Therefore, the solution for an effective e-learning system is the development of an adaptive e-learning system [2] by focusing on the learner's learning style. Learning style means the physical characteristic, thought and feeling that individual uses to perceive, responsiveness and interaction with a stable environment. The learning style is one element that will help to enhance the learning process, pro...

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A Framework for Adaptive e-Learning Systems in Higher Education with Information Visualization

Cited by 11 publications

References 9 publications

Reliable peers and useful resources: Searching for the best personalised learning path in a trust- and recommendation-aware environment

Reliable peers and useful resources: Searching for the best personalised learning path in a trust- and recommendation-aware environment

The DEKOR System

Conceptual Framework of a Synthesized Adaptive e-Learning and e-Mentoring System Using VARK Learning Styles with Data Mining Methodology

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