An Automatic Approach for Identifying Triple-Factor in e-Learning Process

Sfenrianto, Sfenrianto; Hasibuan, Zainal A.; Suhartanto, Heru

doi:10.7763/ijcte.2013.v5.712

Cited by 14 publications

(8 citation statements)

References 9 publications

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“…Learning style of the learner determined level of learning material that suitable with the learner preferences. Based on [8], learning style of learner calculated based on mean in frequent table of the group as a threshold. Learning style divide into 3 categories, they are seldom access category for number of access learning materials below the threshold, discipline catgeory for number of access equal with the range of threshold, and diligent access category for number of access greater or equal than the threshold.…”

Section: Methodsmentioning

confidence: 99%

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Personalization in e-Learning

2012

Encyclopedia of the Sciences of Learning

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Indonesia is a developing country that began to utilize information technology in education. A form of its implementation is the use of e-learning. However, in practice there are still some obstacles, such as learning resources are not evenly distributed, limited access to services provided, qualified educators resources are concentrated in specific areas. This led to the emergence of disparities educational process, and technology gap due to differences in ICT infrastructure owned by any educational institution. Therefore this study propose an architecture of cloud-based open learning to solve these problems. The term open learning is used in order to encouraging the development of the concept of Indonesia Open Educational Resources (IOER) and as well as the adoption of concept of cloud computing. This research through several phases of research including analysis, design, implementation, testing and evaluation. The design of the proposed architecture consists of six layers: (1) Infrastructure, (2) Platform, (3) Application, (4) Service, (5) Access, (6) User. As a results of the implementation from this architecture is a prototype of Indonesia-Virtual Open Learning System (iVOLS). In experiment, personalization e-learning runs as a service that need large storage and other shared facilities to conduct the program so the system can delivered different learning materials to different learners. The personalization e-learning in cloud environment successed when the learners got the best performance on learning and it shown by their evaluation score. Based on the test results and evaluation showed that the availability on Cloud-Based Open Learning further meet user needs. This is indicated by the presence of a simple infrastructure services, application services with just one stage and the availability of a wider range of data and the resource sharing. In accessibility, Cloud-Based Open Learning provides easy access to the user. By economically, the result of evaluation showed that Cloud-Based Open Learning has an investment of 35.61% efficiency, increase return on investment (ROI) of 60.95% and an increase in benefits (NPV) of 81.97% from the user's perspective. While from the provider's perspective, Cloud-Based Open Learning has an investment of 200% efficiency, increase return on investment (RoI) of 220.4% and an increase in benefits (NPV) of 109.55%.

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Section: Methodsmentioning

confidence: 99%

“…The newer trend that is often used today is the semantic web technology where the resources was formed in the semantic description [7]. Other researchers also are using P2P technology combined with semantic web technologies and formed a super-peer P2P semantic grid where the semantic metadata retrieved from many educational sources [8].…”

Section: Cloud Computingmentioning

confidence: 99%

Personalization in e-Learning

2012

Encyclopedia of the Sciences of Learning

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“…Salah satu karakteristik yang paling menonjol adalah gaya belajar. Gaya belajar atau learning style berperan sebagai salah satu faktor karakteristik yang mempengaruhi keberhasilan siswa sehingga dapat meningkatkan proses belajar dan outcome pada pembelajaran yang bersifat individual (Sfenrianto & Suhartanto, 2013). Dalam implementasinya di kelas guru tidak memiliki kesempatan untuk menyajikan media yang mendukung gaya belajar siswa karena keterbatasan waktu pembelajaran.…”

Section: Pendahuluanunclassified

Pengembangan Adaptive E-Learning Sistem Berbasis Vark Learning Style Pada Materi IP Address

Kusworo

Soepriyanto

Husna

2021

JKTP

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Sistem pembelajaran di SMK menargetkan 25% materi dan 75% praktik. Waktu siswa selama di sekolah akan habis dengan praktik dan sedikit waktu dalam mendalami materi. Diperlukan alternatif sehingga siswa dapat mengoptimalkan pemahaman materi tanpa perlu memotong waktu praktik di sekolah. Adaptive E-Learning System (AES) menerapkan pembelajaran yang mengacu pada perbedaan karakteristik siswa berupa gaya belajar. Gaya belajar merupakan cara dan kondisi dimana siswa secara efisien dan efektif memahami, mengolah, menyimpan dan mengingat kembali apa yang mereka pelajari. Model pengembangan yang diterapkan dalam penelitian ini adalah model multimedia instructional design oleh Lee & Owens. Untuk mengetahui kelayakan program AES maka diperlukan uji kelayakan dari ahli media dan ahli materi dengan menggunakan angket dengan skala 1-5. Hasil review dari ahli media dan ahli materi menunjukkan nilai positif dengan mayoritas nilai adalah 5 dan 4 sehingga program aplikasi dikategorikan layak digunakan. Hasil pengembangan ini merupakan program Adaptive e-learning system yang dapat mengidentifikasi gaya belajar siswa dan memberikan materi sesuai dengan gaya belajarnya.

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“…Some studies also state that some of the characteristics that influence student success in learning are motivation, knowledge ability and learning style so that the elearning content developed is adaptive according to the characteristics of the students (Esichaikul, Lamnoi, & Bechter, 2011;Sfenrianto, Hasibuan, & Suhartanto, 2013;Surjono, 2011;Suryani & Nasuha, 2014).…”

Section: Introductionmentioning

confidence: 99%

The effectiveness of content based on dynamic intellectual learning with visual modality in vocational school

Agustini

Sindu

Kusuma

2019

jpv

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E-learning generally presented the same learning material because it considered the characteristics of all users to be homogeneous. In fact, every student had different characteristics in the learning process. The objectives of this study were: (1) To produce a simulation content and digital communication based on Dynamic Intellectual Learning with Visual Modality for the tenth grade at SMK Negeri 1 Seririt, (2) To find out the teacher's response and the tenth grade students at SMK Negeri 1 Seririt on Simulation Content and Digital Communication based on DIL with Visual Modality that had been generated. The method of this study was a research and development referred to the plomp model. The subjects of this study were the tenth grade of accounting program at SMK Negeri 1 Seririt in the academic year 2017/2018. There were various try out had been carried out, namely: validity testing by experts and effectiveness testing by using the Hake formula. The results showed that the simulation content and digital communication based on DIL with Visual Modality was valid and practically use: the effectiveness testing produced N-gain of 0.74 included in the effective category and the data analysis of the teacher and the students respond showed that it was categorized in the positive category. It showed that the output was valid, practical and effective to be used.

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An Automatic Approach for Identifying Triple-Factor in e-Learning Process

Cited by 14 publications

References 9 publications

Personalization in e-Learning

Personalization in e-Learning

Pengembangan Adaptive E-Learning Sistem Berbasis Vark Learning Style Pada Materi IP Address

The effectiveness of content based on dynamic intellectual learning with visual modality in vocational school

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