The Semantically Rich Learning Environments: A Systematic Literature Review

Purpose: The research is intended to extract repetitive themes in the field of semantic-rich learning and to express the basic opportunities and challenges therein. Method: The method applied was to review the articles published in the WOS database, during the years 2000 to 2020 by using the paradigm funnel technique; moreover the Nvivo software was used for document analysis and theme extraction. Findings: In the study, it was found that establishing access to appropriate educational content, proper analysis and representation of knowledge, human capabilities enhancement, personalization of learning, and improving the quality of assessment, are the most important positive effects of using STs in learning; Also, in this study, nine themes and seven major challenges in the field of semantic-rich learning were identified. Conclusion: personalization and adaptation, and the development of various ontologies, are the most cited themes; and access to learning content and concerns about the design and development of learning systems are the most important challenges facing semantic-rich learning environments. We believe that in order to overcome the enumerated challenges, the combination of STs with other emerging cognitive and communication technologies, such as IoT, is necessary and could be the subject of future research in this field

Ontology-Based Linked Data to Support Decision Making within Universities

In recent years, educational institutions worked hard to automate their work using more trending technologies that prove the success in supporting decision-making processes. Most the decisions in educational institutions rely on rating the academic research profiles of their staff. An enormous amount of scholarly data is produced continuously by online libraries that contain data about publications, citations, and research activities. This kind of data can change the accuracy of the academic decisions if linked with the local data of universities. The Linked Data technique in this study is applied to generate a link between university semantic data and an open knowledge graph to enrich the local data and improve academic decisions. As a proof of concept, a case study was conducted to allocate the best academic staff to teach a course regarding his profile, including research records. Further, the resulted data is available to reuse in the future for different purposes in academic domain. Finally, we compared the results of this link with previous work as evidence of the accuracy of leveraging this technology to improve decisions within universities

Strategies for preservation of digital records in Masvingo Province of Zimbabwe

Information and communication technologies (ICTs) have been embraced by a number of public institutions in Masvingo province of Zimbabwe as part of the government’s drive towards e-governance and improved service delivery. This has resulted in the generation of large volumes of digital records that are invaluable for strengthening accountability, transparency, decision making and service delivery. Preservation of these digital records has been cited as a daunting task for most institutions especially in sub-Saharan Africa. The dynamic nature of information technologies, obsolescence issues, as well as media degradation require digital preservation strategies in place to ensure that digital records remain accessible and usable over time. However, the National Archives of Zimbabwe (NAZ) mandated to preserve all types of records is at the moment unable to ingest digital records from public departments for preservation due to lack of adequate digital storage facilities and skilled manpower. The records creating agencies in Masvingo have been left on their own to deal with the digital preservation conundrum yet they are also faced with similar challenges. This qualitative study utilised the Open Archival Information System (OAIS) reference model as the conceptual framework to explore the strategies for preservation of digital records in Masvingo province in Zimbabwe. Data was gathered through interviews with officials from 13 out of 15 public departments that preserved digital records in Masvingo province, augmented by observation and document analysis. Research data was manually processed and thematically analysed in line with the objectives of the study. The study established that the strategies for preservation of digital records in Masvingo province were failing to guarantee their long-term preservation and security due to lack of supportive legislation, standards, policy guidelines, budgets, adequate and conducive infrastructure and skills. This has resulted in swathes of digital memory being lost. The study recommended the adoption of trusted digital repositories (TDRs) that are compliant to the OAIS standard, close co-operation between records creating agencies, NAZ, information technology (IT) experts and the academia in tackling digital preservation challenges, and the development of preservation policies and guidelines, as well as continuous training and provision of budgets to cater for preservation of digital records. In the absence of infrastructure, the NAZ should consider cloud computing for preservation of digital records as an interim solution while observing legal obligations.Information ScienceM. Inf. (Archival Science

Developing ontology-based decision-making framework for Middle Eastern region HEIs

Decision making is one of the most challenging processes that higher education institutions continuously experience worldwide. Most educational decisions rely mainly on evaluating the academic profile of staff members, which usually includes the academic and research activities of the teacher. The massive amount of scattered educational data, if represented in traditional forms, causes the problem of ambiguity and inaccuracy of decisions. Educational institutions have recently been attempting to apply emerging technologies in the data engineering field to solve as many challenges as possible. In addition, online libraries continuously produce an enormous amount of open scholarly data, including publications, citations, and other research activity records, which could effectively improve the quality of academic decisions when linked with the local data of universities. This thesis presents the academic profiles and course records semantically, and employs them with a scientific knowledge graph as linked data to enrich the internal data and support the decision-making process within universities. The proposed approach is applied to assign courses to the most qualified academic staff as a proof-of-concept experiment. Traditionally, this process is performed manually by heads of departments and is considered time-consuming, especially when the data are in textual format. This research aims to address this challenge. To this end, courses and academic profiles are represented semantically in RDF format, in order to improve the quality of the institutional data. To ensure the efficiency of this process, a survey is conducted to identify the key factors that influence decision making during the distribution of courses among staff members, which was successfully distributed to the heads of departments who actively participated and provided their variable insights into this matter. The survey results indicated that the research areas of academic staff and whether they had taught the course before are the most important factors that are usually considered in this type of decision. Furthermore, this study proves the importance of generating links between local data and external repositories with updated research records to improve the course–teacher assignment process. Linked data technology is applied to combine all the possible information affecting the course–teacher assignment decision from different resources, and the sufficiency of the linked data and the selection of external data are examined using data mining techniques. Two prediction models are developed to predict the most qualified academic teacher to teach each course, with the results being associated with 314 academic teachers and 119 courses from the Faculty of Computing and Information Technology at King Abdulaziz University. According to the obtained accuracy of the models, it is suggested that the performance is improved when the data are enriched with external scholarly open data using LD, with the accuracy increasing from 80.95% to 93.26% after applying LD techniques. Additionally, adding research records of the academic member improved the sensitivity of the models to 89.11% and 97.76%. These improvements demonstrate the importance of considering the research activities of academic members when distributing courses, especially when extracted from external repositories using LD

Framework for digital preservation of electronic government in Ghana

The global perspective on digital revolution is one that has received a rapturous approval from information professionals, scholars and practitioners. However, such an approval has come at a great cost to memory institutions as the preservation of digital information has proved to be a complex phenomenon to memory institutions. Guided by the multi method design and underpinned by the triangulation of questionnaires, interviews, observation and document analysis, the study examined digital preservation of e-government in Ghana. Findings revealed that the creation of databases, digital publication, emails, website information and tweets were often ocassioned by the use of ICT, e-government, and application of legislations and public policies. It observed that these types of digital records were in urgent need for preservation as most of the ministries and agencies were unable to access their digital records. While the application of a digital preservation tool (Lots of Copies Keeps Stuff Safe) was a familiar terrain to the ministries and agencies, there was expressed lack of awareness about digital preservation support organisations and digital preservation standards. The study identified funding, level of security and privacy, skills training and technological obsolescence as factors that pose key threats to digital preservation. It noted backup strategy, migration, metadata and trusted repositories as the most widely implemented preservation strategy across the ministries and agencies. On the other hand, cloud computing, refreshing and emulation were the least implemented preservation strategies used to address the digital preservation challenges . The study recommends that the ministries and agencies can address many of the digital preservation challenges if they leverage on collaborative and participatory opportunities. Such collaborative and participatory opportunities involve the use of experts from other institutions to share resources and use a common protocol through cloud computing and Open Data. It further recommends that the process of developing a digital preservation policy can be guided by a template document from other jurisdictionsInformation ScienceD. Litt et Phil. (Information Science

Taming web data : exploiting linked data for integrating medical educational content

Open data are playing a vital role in different communities, including governments, businesses, and education. This revolution has had a high impact on the education field. Recently, new practices are being adopted for publishing and connecting data on the web, known as "Linked Data", and these are used to expose and connect data which were not previously linked. In the context of education, applying Linked Data practices to the growing amount of open data used for learning is potentially highly beneficial. The work presented in this thesis tackles the challenges of data acquisition and integration from distributed web data sources into one linked dataset. The application domain of this thesis is medical education, and the focus is on bridging the gap between articles published in online educational libraries and content published on Web 2.0 platforms that can be used for education. The integration of a collection of heterogeneous resources is to create links between data collected from distributed web data sources. To address these challenges, a system is proposed that exploits the Linked Data for building a metadata schema in XML/RDF format for describing resources and enriching it with external dataset that adds semantic to its metadata. The proposed system collects resources from distributed data sources on the web and enriches their metadata with concepts from biomedical ontologies, such as SNOMED CT, that enable its linking. The final result of building this system is a linked dataset of more than 10,000 resources collected from PubMed Library, YouTube channels, and Blogging platforms. The effectiveness of the system proposed is evaluated by validating the content of the linked dataset when accessed and retrieved. Ontology-based techniques have been developed for browsing and querying the linked dataset resulting from the system proposed. Experiments have been conducted to simulate users' access to the linked dataset and validate its content. The results were promising and have shown the effectiveness of using SNOMED CT for integrating distributed resources from diverse web data sources

Production and consumption of university Linked Data

Linked Data increases the value of an organisation's data over the web by introducing explicit and machine processable links at the data level. We have adopted this new stream of data representation to produce and expose existing data within The Open University (OU) as Linked Data. We present in this paper our approach for producing the data, based on well-defined workflows at the organisation as well as the technical levels. We also discuss the data already available to consume, and show the potential improvements that Linked Data brings by presenting three applications: (1) the OU Expert Search system for finding experts at the OU based on a specified topic of interest, (2) the Social Study application to identify potential courses for students based on their Facebook profile information, and (3) the Linked OpenLearn application that helps students identify related media and courses to OpenLearn units at the OU. Before concluding the paper, we show the potential benefits and an approach towards interlinking data beyond The Open University with other universities, using a common categorisation scheme