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Immersive Intelligent Tutoring System for Remedial Learning Using Virtual Learning Environment R. Rasim; Yusep Rosmansyah; Armein Z.R. Langi; M. Munir
Indonesian Journal of Science and Technology Vol 6, No 3 (2021): IJOST: VOLUME 6, ISSUE 3, December 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i3.38954

Abstract

Intelligent Tutoring System (ITS) has been widely used in supporting personal learning.  However, there is an aspects that have not become focus in ITS, namely immersive. This research proposes an Immersive Intelligent Tutoring (IIT) model based on Bayesian Knowledge Tracing (BKT) for determining the learner’s characteristics and learning content delivery strategies using genetic algorithms. The model uses remedial learning with a faded worked-out example. This study uses a 3-Dimensional Virtual Learning Environment (3DMUVLE) that implements immersive features to increase intrinsic motivation. This model was built using a client / server architecture. The server side component uses the MOODLE, the client side component uses OpenSim and its viewers, and the middleware component uses the Simulation Linked Object Oriented Dynamic Learning Environment (SLOODLE). Model testing is performed on user acceptance using a combination of Technology Acceptance Model (TAM) and Hedonic-Motivation System Adoption Model (HMSAM) and the impact of the model in learning using statistical test. The results showed 83% of the learners felt happy with the learning. Meanwhile, the evaluation of the impact on learning outcomes shows that the use of this model is significantly different from traditional learning.
Pengembangan Mobile Collaborative Learning System Menggunakan Kerangka Kerja Zachman dan DICE M Husni Syahbani; Yusep Rosmansyah
Jurnal Informatika: Jurnal Pengembangan IT Vol 2, No 2 (2017): JPIT, Juli 2017
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v2i2.515

Abstract

Mobile Learning adalah proses pembelajaran yang menggunakan teknologi perangkat mobile dan jaringan nirkabel, Ada banyak media yang bisa digunakan untuk membuat proses belajar lebih mudah dan menyenangkan, salah satunya adalah dengan menggunakan perangkat mobile seperti telepon seluler, tablet dan komputer desktop, dengan Teknologi ini setiap materi pembelajaran dapat hadir dalam banyak format seperti yang video, suara dll. Kombinasi antara teknologi perangkat mobile dan jaringan nirkabel dapat memecahkan masalah dalam proses belajar, banyak pelajar merasa sulit untuk mengelola materi pembelajaran yang sesuai dengan kebutuhan mereka dan bagaimana belajar dengan efektif dan efisien. Jadi penelitian ini mencoba untuk mengembangkan sistem yang berupa kombinasi antara teknologi perangkat mobile dan jaringan nirkabel yang disebut Mobile Collaboration Learning System (MCLs). Dalam pengembangan MCLs menggunakan kerangka pendekatan Zachman untuk mengidentifikasi kegiatan dan proses dalam pembelajaran yang dapat membantu studi pelajar dengan mudah dan interaktif dan berkolaborasi. Dengan kerangka pendekatan Zachman membuat MCLs menyelaraskan dengan kebutuhan peserta didik dan dosen di sekolah. Pendekatan ini menghasilkan sistem persyaratan yang dianalisis menggunakan kerangka DICE untuk mengetahui bagaimana risiko pengembangan sistem ini untuk direalisasikan.
A Systematic Literature Review of Gamification for Children: Game Elements, Purposes, and Technologies Nia Semartiana; Atina Putri; Yusep Rosmansyah
Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) Vol. 1 No. 1 (2022): Proceeding of International Conference on Information Science and Technology In
Publisher : Universitas Respati Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/icostec.v1i1.16

Abstract

Technology continues to develop tools and applications to help students learning, especially in early childhood education. This innovation has an impact on children's learning behavior and activities since children are familiar with and enjoy playing with digital games. Previous research has attempted to combine the fun aspects of games with the learning aspects of games to create child-friendly activities. Gamification helps to create an effective educational environment in order to increase children's motivation, engagement, and learning performance. However, there are few studies that discuss the impact of gamification on children's learning, as well as the types of game elements and technology that are acceptable for them. This study presents a systematic literature review on gamification in order to identify the types of goals, game elements, and trends in gamification technology for the younger generation. In this study, 20 research articles were selected to be reviewed from four database sources (IEEE Xplore, ScienceDirect, Scopus and ACM) from 2017 to 2021. The results showed that the primary goal of gamification for children were to increase motivation and engagement. Several elements, such as points, levels, and leaderboards, were frequently used in the game. Finally, mobile applications were commonly used for gamification in the learning process of children.
Feedback System in Educational Games: A Systematic Literature Review Aditya Sudyana; Atina Putri; Yusep Rosmansyah
Jurnal Pendidikan Indonesia Vol. 5 No. 7 (2024): Jurnal Pendidikan Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/japendi.v5i7.3059

Abstract

The presence of a feedback system is a key factor in maintaining individuals' engagement in educational games. This system aims to enhance player motivation and active participation in educational games. In addition, the feedback system can improve the players' learning outcomes by augmenting their knowledge. Nevertheless, there remains a lack of comprehensive research in the field of feedback systems in educational games, leading to an inadequate comprehension of how to construct a proficient feedback system that can more effectively accomplish the objectives of educational games. The overview of feedback systems in educational games is frequently scattered and fragmented, making it challenging to figure out which educational games incorporate such systems. This research not only improves the comprehension of the feedback system in educational games but also addresses an important gap in the existing literature. The aim of this study is to conduct an extensive and systematic review of the existing literature on feedback systems in educational games. This review is based on 36 relevant journal articles published from 2019 to 2023. This research examines the patterns in the utilization of feedback systems in educational games, including the technologies employed to build these systems, the educational domains studied, and the types of products developed through the creation of educational games. In this study, the discussion also includes the design techniques and methods for feedback systems. This text discusses the utilization feedback types as well as the algorithms used to analyze the feedback systems. The text thoroughly discusses the comprehensive selection of feedback components to be delivered as mediums for player feedback. In this paper, we will clarify the impact of using feedback systems in educational games on the players. This study greatly contributes to the progress of learning conducted through educational games.
Quantum Machine Learning Untuk Prediksi Emisi Gas Rumah Kaca dalam Perspektif Filsafat Sains : Quantum Machine Learning for Predicting Greenhouse Gas Emissions from a Philosophy of Science Perspective Hidayat, Wahyu; Surendro, Kridanto; Mahayana, Dimitri; Rosmansyah, Yusep
Jurnal Filsafat Indonesia Vol. 7 No. 2 (2024)
Publisher : Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jfi.v7i2.72236

Abstract

The climate change issues due to greenhouse gas emissions and the emergence of Quantum Machine Learning technology have sparked various studies in utilizing quantum machine learning (QML) to predict greenhouse gas emissions (GHG). This article aims to illustrate research related to the implementation of QML for GHG emission prediction from the perspective of the philosophy of science, particularly in terms of the scientific revolution from Thomas Kuhn's perspective, research program analysis from Imre Lakatos' perspective, pseudoscience pitfalls, potential biases of injustice, ethical and moral aspects, and their impact on society. The article is structured using a qualitative descriptive method. Reference sources include original articles and review articles from journals collected from the Scopus database with topics related to GHG emission prediction. Based on the review of the articles, it can be outlined that research on QML for GHG emission prediction is a progressive science currently in the phase of intensive exploration and development, where the research paradigm in this area is dominated by logical positivism and pragmatism. However, over time and with the development of the research context, new paradigms may emerge as additions or even replace existing research paradigms. The article also identifies the potential biases of injustice, ethical and moral aspects, and the impact of research in this field on society, recommending five strategies to avoid pseudoscience pitfalls related to research on QML for GHG emission prediction.
Keamanan Data Internet of Things dalam Perspektif Pseudosains Mario Bunge: Internet of Things Data Security in Mario Bunge's Pseudoscience Perspective Pradana, Aditya; Bandung, Yoanes; Mahayana, Dimitri; Rosmansyah, Yusep
Jurnal Filsafat Indonesia Vol. 7 No. 2 (2024)
Publisher : Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jfi.v7i2.72435

Abstract

Data security is a major concern in the rapidly growing Internet of Things (IoT). This paper investigates the data security aspects of IoT with a pseudoscience perspective inspired by Mario Bunge. The purpose of this research is to understand and address data security challenges in IoT environments. First, researcher identify and evaluate potential vulnerabilities and threats to data, hacking risks, and data encryption needs. Then, researcher analyze commonly used security methods and strategies, including blockchain, fog computing, edge computing, and machine learning. Bunge's pseudoscience approach helps in comprehensively understanding and analyzing IoT data security. The results show a deeper understanding of the data security challenges in IoT, as well as detailed recommendations for risk mitigation. This research highlights the importance of a holistic approach that blends technical and philosophical aspects to address data security issues in IoT. The pseudoscience perspective helps in developing a solid conceptual framework and encourages critical thinking in formulating effective security strategies. In conclusion, this paper makes an important contribution in understanding and addressing the complexities of data security in IoT.