Personalisasi Dan Platform Pengajaran Digital (Blended Learning, Online Learning, Adaptive Learning)

Abstract: Personalize And Digital Teaching Platform (Mixed Learning, Online Learning, Adaptive Learning)This paper, entitled Personalization and Digital Teaching Platforms (Blended Learning, Online Learning, Adaptive Learning, etc.) has problems (1) How important is personalization in digital learning, (2) How is the relationship between personalization and various important elements in digital learning? The purposes of this paper are (1) To find out how important personalization is in digital learning, (2) To find out how personalization is related to various important elements in digital learning. The writing method used is descriptive qualitative method. Data collection techniques are documentation techniques and data processing techniques using qualitative descriptive techniques. The results show that personalization in digital learning is very important because it is a change in teaching methods and methods in accordance with advances in science and technology. Personalization is closely related to an important element in learning, namely the use of the internet as the main media in the e-learning model. Furthermore, the personalization system is carried out to increase the ability or absorption of students in the use of technology. Approaches that can be taken in personalizing digital learning include: Blended learning (a model or strategy which is basically a combination of the advantages of face-to-face and virtual learning), Online learning (Online learning is the result of learning delivered electronically with using computers and computer-based media), Adaptive learning (adaptive learning), adaptive mobile learning is a multi-media learning program that presents learning media with mobile devices and has the ability to adapt to the characteristics of user learning styles (student learning styles). Abstrak: Personalisasi Dan Platform Pengajaran Digital (Blended Learning, Online Learning, Adaptive Learning)Tulisan yang berjudul Personalisasi dan Platform Pengajaran Digital (Blended Learning, Online Learning, Adaptive Learning, dll) ini memiliki masalah (1) Bagaimana pentingnya personalisasi dalam pembelajaran digital, (2) Bagaimana keterkaitan antara personalisasi dengan berbagai elemen penting dalam pembelajaran digital? Tujuan tulisan ini adalah (1) Untuk mengetahui Bagaimana pentingnya personalisasi dalam pembelajaran digital, (2) Untuk mengetahui Bagaimana keterkaitan antara personalisasi dengan berbagai elemen penting dalam pembeljaran digital. Metode penulisan yang digunakan adalah metode deskritif kualitatif. Teknik pengumpulan datanya adalah teknik dokumentasi dan teknik pengolahan data menggunakan teknik deskriptif kualitatif. Hasil penelitian menunjukan bahwa personalisasi dalam pembelajaran digital sangat penting karena merupakan suatu perubahan dalam metode dan cara mengajar sesuai dengan kemajuan ilmu pengetahuan dan ilmu teknologi. Personalisasi sangat terkait dengan elemen penting dalam pembelajaran, yaitu pada pemanfaatan internet sebagai media utama dalam model pembelajaran e-learning. Selanjutnya, system personalisasi dilakukan untuk meningkatkan kemampuan atau daya serap siswa dalam penggunaan teknologi. Pendekatan yang dapat dilakukan dalam personalisasi pembelajaran digital antara lain seperti: Blended learning ( Model ataupun srategi yang pada dasarnya merupakan gabungan keunggulan pembelajaran yang dilakukan secara tatap muka dan  secara virtual), Online learning (Pembelajaran online merupakan hasil dari suatu pembelajaran yang disampaikan sacara elektronik dengan menggunakan computer dan media berbasis computer), Adaptive learning (pembelajaran adaptive), adaptive mobile learning adalah program multi media pembelajaran yang menyajikan media pembelajaran dengan perangkat bergerak dan memiliki kemampuan untuk menyesuaikan dengan karakteristik gaya belajar pengguna(student learning styles)

Theoretical perspectives on mobile language learning diaries and noticing for learners,teachers and researchers

This paper considers the issue of 'noticing' in second language acquisition, and argues for the potential of handheld devices to: (i) support language learners in noticing and recording noticed features 'on the spot', to help them develop their second language system; (ii) help language teachers better understand the specific difficulties of individuals or those from a particular language background; and (iii) facilitate data collection by applied linguistics researchers, which can be fed back into educational applications for language learning. We consider: theoretical perspectives drawn from the second language acquisition literature, relating these to the practice of writing language learning diaries; and the potential for learner modelling to facilitate recording and prompting noticing in mobile assisted language learning contexts. We then offer guidelines for developers of mobile language learning solutions to support the development of language awareness in learners

Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure