Learning object metadata interchange mechanism : a thesis presented in partial fulfillment of the requirements for the degree of Master of Information Science at Massey University, Palmerston North, New Zealand

In spite of the current lack of conceptual clarity in the multiple definitions and uses, the term learning objects is still frequently used in content creation and aggregation in the online-learning field. In the mean time, considerable efforts have been initiated in the past few years for the standardization of metadata elements for consistent description of learning objects, so that learning objects can be identified, searched and retrieved effectively and efficiently across multiple contexts. However, there are currently a large number of standardization bodies and an even much larger number of ongoing standard initiatives in the learning field, and different learning objects repositories are likely to apply different metadata schemas to meet the specific needs of their intended communities. An interchange mechanism for the conversion between various metadata schemas, therefore, becomes necessary for intensive interoperability. In this thesis, we first make a brief introduction to the concept learning objects, then the term metadata, followed by a description of the functional requirements of learning objects. the purposes of metadata, and the importance of metadata for learning objects. After that, this thesis investigates metadata schemas in various fields in general, focused on several mainstream metadata specifications developed for learning objects in particular. The differences among these metadata schemas for learning objects are analyzed and a mapping between their elements is identified. On the basis of literature review, a framework for interchange of metadata schemas is proposed and a prototype to demonstrate the functionalities of the framework is developed. For the high scalability and the high accuracy of the developed system, a so-called LOM-intermediated approach is suggested, and a so-called dynamic-database methodology is adopted. The LOM- intermediated approach significantly simplifies the metadata mapping issues by undertaking the schema-schema mapping in a way of schema-LOM-schema mapping, while the dynamic-database methodology effectively prevents any data-loss resulting as a by-product from the use of LOM-intermediated approach. The prototype currently generates and outputs XML metadata in IMS, EdNA, Dublin Core and LOM. It is a web- based three-tier architecture, using Java technologies for implementation, MySQL as the database server and JDBC for database access

Enriching e-learning metadata through digital library usage analysis

Purpose: In this paper we propose an evaluation framework for analyzing learning objects usage, with the aim of extracting useful information for improving the quality of the metadata used to describe the learning objects, but also for personalization purposes, including user models and adaptive itineraries. Methodology: We present experimental results from the log usage analysis during one academic semester of two different subjects, 350 students. The experiment looks into raw server log data generated from the interactions of the students with the classroom learning objects, in order to find relevant information that can be used to improve the metadata used for describing both the learning objects and the learning process. Findings: Preliminary studies have been carried out in order to obtain an initial picture of the interactions between learners and the virtual campus, including both services and resources usage. These studies try to establish elationships between user profiles and their information and navigational behavior in the virtual campus, with the aim of promoting personalization and improving the understanding of what learning in virtual environments means. Research limitations: During the formal learning process, students use learning resources from the virtual classroom provided by the academic library, but they also search for information outside the virtual campus. Not all of these usage data are considered in the model we propose. Further research needs to be done in order to get a complete view of the information search behavior of students for improving the users’ profile and creating better personalized services. Practical implications: In this paper we suggest how a selection of fields used in the LOM standard could be used for enriching the description of learning objects, automatically in some cases, from the learning objects usage performed by an academic community. Originality: Ever since the beginnings of libraries, they have been a “quiet storage place”. With the development of digital libraries, they become a meeting place where explicit and implicit recommendations about information sources can be shared among users. Social and learning process interactions, therefore, can be considered another knowledge source

A generic framework for the development of standardised learning objects within the discipline of construction management

E-learning has occurred in the academic world in different forms since the early 1990s. Its use varies from interactive multimedia tools and simulation environments to static resources within learning management systems. E-learning tools and environments are no longer criticised for their lack of use in higher education in general and within the construction domain in particular. The main criticism, however, is that of reinventing the wheel in order to create new learning environments that cater for different educational needs. Therefore, sharing educational content has become the focus of current research, taking e-learning into a whole new era of developments. This era is enabled by the emergence of new technologies (online and wireless) and the development of educational standards, such as SCORM (Sharable Content Object Reference Model) and LOM (Learning Object Metadata) for example. Accordingly, the broad definition of the construction domain and the interlocking nature of subjects taught within this domain, makes the concept of sharing content most appealing. This paper proposes a framework developed to describe the various steps required in order to enable the application of e-learning metadata standards and ontology for sharable learning objects to serve the construction discipline. The paper further describes the application of the proposed framework to a case study for developing an online environment for learning objects that are standardised, sharable, transparent and that cater for the needs of learners, educators and curricula developers in Construction Management. Based on the framework, a learning objects repository is developed incorporating educational and web standards. The repository manages objects as well as metadata using ontology and offers a set of services such as storing, retrieving and searching of learning objects using Semantic Web technologies. Thus, it increases the reusability, sharability and interoperability of learning objects

Learning objects and learning designs: an integrated system for reusable, adaptive and shareable learning content

This paper proposes a system, the Smart Learning Design Framework, designed to support the development of pedagogically sound learning material within an integrated, platform-independent data structure. The system supports sharing, reuse and adaptation of learning material via a metadata-driven philosophy that enables the technicalities of the system to be imperceptible to the author and consumer. The system proposes the use of pedagogically focused metadata to support and guide the author and to adapt and deliver the content to the targeted consumer. A prototype of the proposed system, which provides proof of concept for the novel processes involved, has been developed. The paper describes the Smart Learning Design Framework and places it within the context of alternative learning object models and frameworks to highlight similarities, differences and advantages of the proposed system

Towards a re-engineering method for web services architectures

Recent developments in Web technologies – in particular through the Web services framework – have greatly enhanced the flexible and interoperable implementation of service-oriented software architectures. Many older Web-based and other distributed software systems will be re-engineered to a Web services-oriented platform. Using an advanced e-learning system as our case study, we investigate central aspects of a re-engineering approach for the Web services platform. Since our aim is to provide components of the legacy system also as services in the new platform, re-engineering to suit the new development paradigm is as important as re-engineering to suit the new architectural requirements

Using Schema-based Metadata for Image Labels accessed with FAIR Digital Objects

Scientific image data sets can be continuously enriched by labels describing new features which are relevant for some specific task. This process can be automated by means of Machine Learning (ML) techniques. Although such an approach shows clear advantages, especially when it is applied to large datasets, it also poses an important challenge: Relabeling image data sets curated by different scientists, in order to collectively use them for ML, requires a common agreement on the labels which can be used. This can be achieved thanks to the use of a standardized way to describe the label information: a metadata schema including vocabularies. Furthermore, machine-actionable decisions on the label information for relabeling can be enabled by the representation of images and schema-based metadata as FAIR Digital Objects (DOs). We introduce a metadata schema including vocabularies to describe ML image data represented as FAIR DOs that can be accessed for relabeling. The specifications of the metadata schema are presented. The relevance of a standardized metadata description including vocabularies for relabeling ML image data is emphasized. It is shown how the metadata is accessed with FAIR DOs and how vocabularies support automated relabeling. This contribution supplements the content of “FAIR DO Application Case for Composing Machine Learning Training Data” with a focus on the semantic aspects for relabeling. This work has been supported by the research program ‘Engineering Digital Futures’ of the Helmholtz Association of German Research Centers and the Helmholtz Metadata Collaboration Platform. This project has received funding from the ‘European Union’s Horizon 2020‘ research and innovation program under grant agreement No. 101007417 within the framework of the ‘NFFA-Europe Pilot‘ (NEP) Joint Activities

Extending the 5S Framework of Digital Libraries to support Complex Objects, Superimposed Information, and Content-Based Image Retrieval Services

Advanced services in digital libraries (DLs) have been developed and widely used to address the required capabilities of an assortment of systems as DLs expand into diverse application domains. These systems may require support for images (e.g., Content-Based Image Retrieval), Complex (information) Objects, and use of content at fine grain (e.g., Superimposed Information). Due to the lack of consensus on precise theoretical definitions for those services, implementation efforts often involve ad hoc development, leading to duplication and interoperability problems. This article presents a methodology to address those problems by extending a precisely specified minimal digital library (in the 5S framework) with formal definitions of aforementioned services. The theoretical extensions of digital library functionality presented here are reinforced with practical case studies as well as scenarios for the individual and integrative use of services to balance theory and practice. This methodology has implications that other advanced services can be continuously integrated into our current extended framework whenever they are identified. The theoretical definitions and case study we present may impact future development efforts and a wide range of digital library researchers, designers, and developers

A web services architecture for learning object discovery and assembly

Courseware systems are often based on an assembly of different components, addressing the different needs of storage and delivery functionality. The Learning Technology Standard Architecture LTSA provides a generic architectural framework for these systems. Recent developments in Web technology – e.g. the Web services framework – have greatly enhanced the flexible and interoperable implementation of courseware architectures. We argue that in order to make the Web services philosophy work, two enhancements to the LTSA approach are required. Firstly, a combination with metadata annotation is needed to support the discovery of educational Web services. Secondly, if these components are to be provided in form of services, more support is needed for their assembly. Architectural patterns of a finer degree of granularity shall satisfy this need

A structured model metametadata technique to enhance semantic searching in metadata repository

This paper discusses on a novel technique for semantic searching and retrieval of information about learning materials. A novel structured metametadata model has been created to provide the foundation for a semantic search engine to extract, match and map queries to retrieve relevant results. Metametadata encapsulate metadata instances by using the properties and attributes provided by ontologies rather than describing learning objects. The use of ontological views assists the pedagogical content of metadata extracted from learning objects by using the control vocabularies as identified from the metametadata taxonomy. The use of metametadata (based on the metametadata taxonomy) supported by the ontologies have contributed towards a novel semantic searching mechanism. This research has presented a metametadata model for identifying semantics and describing learning objects in finer-grain detail that allows for intelligent and smart retrieval by automated search and retrieval software