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Relevant bibliographies by topics / 3DMUVLE

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Journal articles

Academic literature on the topic '3DMUVLE'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "3DMUVLE"

1

Rosmansyah, Yusep, Mohamad Achiruzaman, and Ariq Bani Hardi. "A 3D Multiuser Virtual Learning Environment for Online Training of Agriculture Surveyors." Journal of Information Technology Education: Research 18 (2019): 481–507. http://dx.doi.org/10.28945/4455.

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Aim/Purpose: This research proposed a 3D multiuser virtual learning environment (3DMUVLE) educational game design framework by combining ATMSG, ADDIE, E-Simulation, and 3D Open Simulator Technology Architecture. This paper focused on a case study of online training for food crops productivity data surveys. Background: The conventional online training still lacks engagement, immersion, and curiosity aspects, which decreases learners’ learning seriousness because the instructors and participants do not meet directly. Integration of 3DMUVLE and gamification in online training has a good potential

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2

Rasim, Rosmansyah Yusep, Z.R Langi Armein, and Munir. "Selection of Learning Materials Based on Students' Behaviors in 3DMUVLE." TELKOMNIKA Telecommunication, Computing, Electronics and Control 16, no. 5 (2018): 2127–36. https://doi.org/10.12928/TELKOMNIKA.v16i5.7994.

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Learning in 3-dimensional virtual environments has been widely used as a complement to traditional learning. Multi User Virtual Learning Environment in 3 Dimensions (3DMUVLE) provides many benefits and can support lifelong learning. In its implementation, this learning has not supported personal learning. This study aims to build a 3DMUVLE with personalized materials based on students' models. The system development model uses the Linear Sequence model by integrating MOODLE, SLOODLE and OPENSIM. Student's model in this research is Myer Briggs Type Indicator (MBTI) and determination of

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3

Rasim, Rasim, Yusep Rosmansyah, Armein Z. R. Langi, and Munir Munir. "Selection of Learning Materials Based on Students’ Behaviors in 3DMUVLE." TELKOMNIKA (Telecommunication Computing Electronics and Control) 16, no. 5 (2018): 2127. http://dx.doi.org/10.12928/telkomnika.v16i5.7994.

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4

Rasim, Munir, Y. Rosmansyah, and A. Z. R. Langi. "Digital learning model based on intelligent tutoring system in 3DMUVLE." Journal of Physics: Conference Series 1280 (November 2019): 032037. http://dx.doi.org/10.1088/1742-6596/1280/3/032037.

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5

Rasim, R., Yusep Rosmansyah, Armein Z. R. Langi, and M. Munir. "Immersive Intelligent Tutoring System for Remedial Learning Using Virtual Learning Environment." Indonesian Journal of Science and Technology 6, no. 3 (2021): 507–22. http://dx.doi.org/10.17509/ijost.v6i3.38954.

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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.

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