1,739 research outputs found

    Integrating serious games in adaptive hypermedia applications for personalised learning experiences

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    Game-based approaches to learning are increasingly recognized for their potential to stimulate intrinsic motivation amongst learners. While a range of examples of effective serious games exist, creating high-fidelity content with which to populate games is resource-intensive task. To reduce this resource requirement, research is increasingly exploring means to reuse and repurpose existing games. Education has proven a popular application area for Adaptive Hypermedia (AH), as adaptation can offer enriched learning experiences. Whilst content has mainly been in the form of rich text, various efforts have been made to integrate serious games into AH. However, there is little in the way of effective integrated authoring and user modeling support. This paper explores avenues for effectively integrating serious games into AH. In particular, we consider authoring and user modeling aspects in addition to integration into run-time adaptation engines, thereby enabling authors to create AH that includes an adaptive game, thus going beyond mere selection of a suitable game and towards an approach with the capability to adapt and respond to the needs of learners and educators

    A Competence-Based Course Authoring Concept for Learning Platforms with Legacy Assignment Tools

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    This paper is concerned with several of the most important aspects of Competence-Based Learning (CBL): course authoring, assignments, and categorization of learning content. The latter is part of the so-called Bologna Process (BP) and can effectively be supported by integrating knowledge resources like, e.g., standardized skill and competence taxonomies into the target implementation approach, aiming at making effective use of an open integration architecture while fostering the interoperability of hybrid knowledge-based e-learning solutions. Modern scenarios ask for interoperable software solutions to seamlessly integrate existing e-learning infrastructures and legacy tools with innovative technologies while being cognitively efficient to handle. In this way, prospective users are enabled to use them without learning overheads. At the same time, methods of Learning Design (LD) in combination with CBL are getting more and more important for production and maintenance of easy to facilitate solutions. We present our approach of developing a competence-based course-authoring and assignment support software. It is bridging the gaps between contemporary Learning Management Systems (LMS) and established legacy learning infrastructures by embedding existing resources via Learning Tools Interoperability (LTI). Furthermore, the underlying conceptual architecture for this integration approach will be explained. In addition, a competence management structure based on knowledge technologies supporting standardized skill and competence taxonomies will be introduced. The overall goal is to develop a software solution which will not only flawlessly merge into a legacy platform and several other learning environments, but also remain intuitively usable. As a proof of concept, the so-called platform independent conceptual architecture model will be validated by a concrete use case scenario

    Multimedia Annotation Interoperability Framework

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    Multimedia systems typically contain digital documents of mixed media types, which are indexed on the basis of strongly divergent metadata standards. This severely hamplers the inter-operation of such systems. Therefore, machine understanding of metadata comming from different applications is a basic requirement for the inter-operation of distributed Multimedia systems. In this document, we present how interoperability among metadata, vocabularies/ontologies and services is enhanced using Semantic Web technologies. In addition, it provides guidelines for semantic interoperability, illustrated by use cases. Finally, it presents an overview of the most commonly used metadata standards and tools, and provides the general research direction for semantic interoperability using Semantic Web technologies

    Degree of Scaffolding: Learning Objective Metadata: A Prototype Leaning System Design for Integrating GIS into a Civil Engineering Curriculum

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    Digital media and networking offer great potential as tools for enhancing classroom learning environments, both local and distant. One concept and related technological tool that can facilitate the effective application and distribution of digital educational resources is learning objects in combination with the SCORM (sharable content objects reference model) compliance framework. Progressive scaffolding is a learning design approach for educational systems that provides flexible guidance to students. We are in the process of utilizing this approach within a SCORM framework in the form of a multi-level instructional design. The associated metadata required by SCORM will describe the degree of scaffolding. This paper will discuss progressive scaffolding as it relates to SCORM compliant learning objects, within the context of the design of an application for integrating Geographic Information Systems (GIS) into the civil engineering curriculum at the University of Missouri - Rolla

    Document Automation Architectures: Updated Survey in Light of Large Language Models

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    This paper surveys the current state of the art in document automation (DA). The objective of DA is to reduce the manual effort during the generation of documents by automatically creating and integrating input from different sources and assembling documents conforming to defined templates. There have been reviews of commercial solutions of DA, particularly in the legal domain, but to date there has been no comprehensive review of the academic research on DA architectures and technologies. The current survey of DA reviews the academic literature and provides a clearer definition and characterization of DA and its features, identifies state-of-the-art DA architectures and technologies in academic research, and provides ideas that can lead to new research opportunities within the DA field in light of recent advances in generative AI and large language models.Comment: The current paper is the updated version of an earlier survey on document automation [Ahmadi Achachlouei et al. 2021]. Updates in the current paper are as follows: We shortened almost all sections to reduce the size of the main paper (without references) from 28 pages to 10 pages, added a review of selected papers on large language models, removed certain sections and most of diagrams. arXiv admin note: substantial text overlap with arXiv:2109.1160
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