Development of an open education resources (OER) system: a comparative analysis and implementation approach

• URL: http://arxiv.org/abs/2405.16442v1
• Date: Sun, 26 May 2024 05:58:45 GMT
• Title: Development of an open education resources (OER) system: a comparative analysis and implementation approach
• Authors: Nimol Thuon, Wangrui Zhang,
• Abstract summary: The project includes a comparative analysis of the top five open-source Learning Management Systems (LMS) The primary objective is to create a web-based system that facilitates the sharing of educational resources for non-commercial users.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Several institutions are collaborating on the development of a new web-based Open Education Resources (OER) system designed exclusively for non-commercial educational purposes. This initiative is underpinned by meticulous research aimed at constructing an OER system that optimizes user experiences across diverse user profiles. A significant emphasis is placed on utilizing open-source tools, frameworks, and technologies. The project includes a comparative analysis of the top five open-source Learning Management Systems (LMS), providing critical insights to inform the development process. The primary objective is to create a web-based system that facilitates the sharing of educational resources for non-commercial users, leveraging information and communication technologies. The project is structured around two key teams: a research team and a development team. This comprehensive approach is intended to establish a robust, user-centric OER system, informed by insights from existing platforms and the latest advancements in open education resource development.

Related papers

• Private Knowledge Sharing in Distributed Learning: A Survey [50.51431815732716]
  The rise of Artificial Intelligence has revolutionized numerous industries and transformed the way society operates. It is crucial to utilize information in learning processes that are either distributed or owned by different entities. Modern data-driven services have been developed to integrate distributed knowledge entities into their outcomes.
  arXiv  Detail & Related papers  (2024-02-08T07:18:23Z)
• Institutional Platform for Secure Self-Service Large Language Model Exploration [0.0]
  The paper outlines the system's architecture and key features, encompassing dataset curation, model training, secure inference, and text-based feature extraction. The platform strives to deliver secure LLM services, emphasizing process and data isolation, end-to-end encryption, and role-based resource authentication.
  arXiv  Detail & Related papers  (2024-02-01T10:58:10Z)
• Lessons Learned from Designing an Open-Source Automated Feedback System for STEM Education [5.326069675013602]
  We present RATsApp, an open-source automated feedback system (AFS) that incorporates research-based features such as formative feedback. The system focuses on core STEM competencies such as mathematical competence, representational competence, and data literacy. As an open-source platform, RATsApp encourages public contributions to its ongoing development, fostering a collaborative approach to improve educational tools.
  arXiv  Detail & Related papers  (2024-01-19T07:13:07Z)
• Uncertainty Estimation in Multi-Agent Distributed Learning [0.0]
  KDT NEUROKIT2E project aims to establish a new open-source framework to facilitate AI applications on edge devices. Our research focuses on the mechanisms and methodologies that allow edge network-enabled agents to engage in collaborative learning in distributed environments.
  arXiv  Detail & Related papers  (2023-11-22T12:48:20Z)
• Learnersourcing in the Age of AI: Student, Educator and Machine Partnerships for Content Creation [2.8074364079901013]
  Engaging students in creating novel content, also referred to as learnersourcing, is increasingly recognised as an effective approach to promoting higher-order learning. This paper presents a framework that considers the existing learnersourcing literature, the latest insights from the learning sciences and advances in AI to offer promising future directions for developing learnersourcing systems.
  arXiv  Detail & Related papers  (2023-06-10T09:17:45Z)
• Flashlight: Enabling Innovation in Tools for Machine Learning [50.63188263773778]
  We introduce Flashlight, an open-source library built to spur innovation in machine learning tools and systems. We see Flashlight as a tool enabling research that can benefit widely used libraries downstream and bring machine learning and systems researchers closer together.
  arXiv  Detail & Related papers  (2022-01-29T01:03:29Z)
• YMIR: A Rapid Data-centric Development Platform for Vision Applications [82.67319997259622]
  This paper introduces an open source platform for rapid development of computer vision applications. The platform puts the efficient data development at the center of the machine learning development process.
  arXiv  Detail & Related papers  (2021-11-19T05:02:55Z)
• An Enterprise Architecture Framework for E-learning [0.0]
  Building an Enterprise Architecture (EA) undoubtedly serves as a fundamental concept to accomplish this goal. The presented framework helps developers to design and justify completely integrated learning and teaching processes and information systems.
  arXiv  Detail & Related papers  (2021-05-07T15:16:22Z)
• From Distributed Machine Learning to Federated Learning: A Survey [49.7569746460225]
  Federated learning emerges as an efficient approach to exploit distributed data and computing resources. We propose a functional architecture of federated learning systems and a taxonomy of related techniques. We present the distributed training, data communication, and security of FL systems.
  arXiv  Detail & Related papers  (2021-04-29T14:15:11Z)
• Toward Multiple Federated Learning Services Resource Sharing in Mobile Edge Networks [88.15736037284408]
  We study a new model of multiple federated learning services at the multi-access edge computing server. We propose a joint resource optimization and hyper-learning rate control problem, namely MS-FEDL. Our simulation results demonstrate the convergence performance of our proposed algorithms.
  arXiv  Detail & Related papers  (2020-11-25T01:29:41Z)
• Knowledge Integration of Collaborative Product Design Using Cloud Computing Infrastructure [65.2157099438235]
  The main focus of this paper is the concept of ongoing research in providing the knowledge integration service for collaborative product design and development using cloud computing infrastructure. Proposed knowledge integration services support users by giving real-time access to knowledge resources.
  arXiv  Detail & Related papers  (2020-01-16T18:44:27Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.