A Survey of Ontologies and Their Applications in e-Learning Environments

2021 ◽  
Author(s):  
Yi Wang ◽  
Ying Wang
Keyword(s):  
Learning Objects ◽  
Future Research ◽  
Knowledge Modeling ◽  
Learning Context ◽  
Scale Level ◽  
Semantic Richness ◽  
Ontology Evaluation ◽  
Wide Range ◽  
E Learning ◽  
Research Questions

Ontology technology has been investigated in a wide range of areas and is currently being utilized in many fields. In the e-learning context, many studies have used ontology to address problems such as the interoperability in learning objects, modeling and enriching learning resources, and personalizing educational content recommendations. We systematically reviewed research on ontology for e-learning from 2008 to 2020. The review was guided by 3 research questions: “How is ontology used for knowledge modeling in the context of e-learning?”, “What are the design principles, building methods, scale, level of semantic richness, and evaluation of current educational ontologies?”, and “What are the various ontology-based applications for e-learning?” We classified current educational ontologies into 6 types and analyzed them by 5 measures: design methodology, building routine, scale of ontology, level of semantic richness, and ontology evaluation. Furthermore, we reviewed 4 types of ontology-based e-learning applications and systems. The observations obtained from this survey can benefit researchers in this area and help to guide future research.

scholarly journals Towards motivation-based adaptation of difficulty in e-learning programs

2012 ◽  
Vol 28 (7) ◽  
Author(s):  
Anke Endler ◽  
Gunter Daniel Rey ◽  
Martin V. Butz
Keyword(s):  
Adaptation Strategies ◽  
Future Research ◽  
Proximal Development ◽  
Real World Data ◽  
Learning Classifier System ◽  
Wide Range ◽  
Learning Programs ◽  
Reported Study ◽  
E Learning ◽  
User Motivation

<span>The objective of this study was to investigate if an e-learning environment may use measurements of the user's current motivation to adapt the level of task difficulty for more effective learning. In the reported study, motivation-based adaptation was applied randomly to collect a wide range of data for different adaptations in a variety of motivational states. This data was then utilised to extract rules for an adequate motivation-based adaptation to maximise expected learning success. A learning classifier system was used for the data analysis, generating rules for suitable and unsuitable adaptations based on current user motivation data. We extracted a set of twelve rules which suggest particular adaptation strategies based on real-world data. These rules could generally be embedded into existing psychological theories, namely the Zone of Proximal Development and the Yerkes-Dodson Law. In future research, we intend to evaluate these rules on further studies and develop concrete sets of adaptation strategies based on user motivation measurements.</span>

scholarly journals Toward Social Media Content Recommendation Integrated with Data Science and Machine Learning Approach for E-Learners

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1798 ◽  
Author(s):  
Zeinab Shahbazi ◽  
Yung Cheol Byun
Keyword(s):  
Social Media ◽  
Computer Science ◽  
Data Science ◽  
Learning System ◽  
Local Context ◽  
Great Success ◽  
Learning Context ◽  
Wide Range ◽  
E Learning ◽  
Learning Software

Electronic Learning (e-learning) has made a great success and recently been estimated as a billion-dollar industry. The users of e-learning acquire knowledge of diversified content available in an application using innovative means. There is much e-learning software available—for example, LMS (Learning Management System) and Moodle. The functionalities of this software were reviewed and we recognized that learners have particular problems in getting relevant recommendations. For example, there might be essential discussions about a particular topic on social networks, such as Twitter, but that discussion is not linked up and recommended to the learners for getting the latest updates on technology-updated news related to their learning context. This has been set as the focus of the current project based on symmetry between user project specification. The developed project recommends relevant symmetric articles to e-learners from the social network of Twitter and the academic platform of DBLP. For recommendations, a Reinforcement learning model with optimization is employed, which utilizes the learners’ local context, learners’ profile available in the e-learning system, and the learners’ historical views. The recommendations by the system are relevant tweets, popular relevant Twitter users, and research papers from DBLP. For matching the local context, profile, and history with the tweet text, we recognized that terms in the e-learning system need to be expanded to cover a wide range of concepts. However, this diversification should not include such terms which are irrelevant. To expand terms of the local context, profile and history, the software used the dataset of Grow-bag, which builds concept graphs of large-scale Computer Science topics based on the co-occurrence scores of Computer Science terms. This application demonstrated the need and success of e-learning software that is linked with social media and sends recommendations for the content being learned by the e-Learners in the e-learning environment. However, the current application only focuses on the Computer Science domain. There is a need for generalizing such applications to other domains in the future.

Mathematics Education

2012 ◽  
pp. 60-89 ◽  
Author(s):  
Giovannina Albano
Keyword(s):  
Mathematics Education ◽  
Peer Assessment ◽  
Active Role ◽  
Learning Objects ◽  
Future Research ◽  
Domain Specific ◽  
E Learning ◽  
Learning Platforms ◽  
And Mathematics ◽  
Teaching Learning

This chapter is concerned with the integration of research in mathematics education and e-learning. Its main aim is to provide a perspective on the teaching/learning opportunities offered by e-learning platforms in a blended learning setting, as experienced at the Universities of Salerno and of Piemonte Orientale. Two types of teaching actions have been set above all: a) tailored units of learning, which have required the design/implementation of a huge pool of learning objects, according to domain-specific guidelines from mathematics education research and to various educational parameters from e-learning research; b) cooperative or individual teacher-driven learning activities together with various practice for self or peer assessment, which have been designed according both to e-learning and mathematics pedagogies based on the active role of the learner, the interaction with tutors and peers, and the importance of critical thinking and communication skills. Finally some feedback from students is reported, and some opportunities for future research are outlined.

Toward Predictive Models for E-Learning

2004 ◽  
pp. 220-234
Author(s):  
Maria Alexandra Rentroia-Bonito ◽  
Joaquim Armando Pires Jorge
Keyword(s):  
Predictive Models ◽  
Traditional Approach ◽  
Learning Experience ◽  
Interactive Media ◽  
Integrated Approach ◽  
Future Research ◽  
Learning Context ◽  
Learner Performance ◽  
E Learning ◽  
The Many

Currently, developing courseware for e-learning initiatives remains much of a black art. While we are mastering the process of authoring interactive media, we know little about the many factors that affect the e-learning experience. This can drastically limit return on invested efforts for organizations. Indeed, authoring multimedia content is a very expensive endeavor as compared to the traditional approach. A better understanding of the process could yield new approaches and insights to achieve a more ambitious goal: predictive models for e-learning. The reviewed literature highlights a lack of reliable results describing the interplay between e-learning context, web usability, cognitive styles, motivation, learner performance and satisfaction. Clearly, more research is needed to better understand and predict learner performance during an e-learning experience. The expected results of such an integrated approach would assist developers to design better e-learning experiences. This chapter proposes a holistic framework covering the interplay among Business-Process, People and Information-Systems issues. This could serve to guide future research.

The Utility of Disruptive Technologies in Interprofessional Education

2010 ◽  
pp. 190-203 ◽  
Author(s):  
Maggie Hutchings ◽  
Anne Quinney ◽  
Janet Scammell
Keyword(s):  
Transformative Learning ◽  
Learning Strategies ◽  
Cultural Change ◽  
Interprofessional Education ◽  
Learning Objects ◽  
Future Research ◽  
Discussion Boards ◽  
Educational Benefits ◽  
Face To Face ◽  
E Learning

This chapter will consider the educational benefits and challenges of introducing e-learning objects within an interprofessional curriculum. It examines the tensions of curriculum development as content or process-driven in the context of facilitating interactive learning using blended learning strategies which combine online and face-to-face interactions. This chapter draws upon an evaluation of student and staff experiences of an interprofessional curriculum incorporating health and social care users and carers as case scenarios in a web-based simulated community, Wessex Bay, and highlights congruent and disruptive factors in negotiating transformative learning and cultural change. It draws conclusions and recommendations for informing practice in interprofessional education and suggests directions for future research to inform the substance (interprofessional case scenarios) and spaces (discussion boards, chat rooms, classroom) for collaborative learning in an interprofessional curriculum.

Recommendation Research in E-Learning

2011 ◽  
Vol 121-126 ◽  
pp. 3067-3071
Author(s):  
Bing Wu ◽  
Wen Xia Xu ◽  
Jun Ge
Keyword(s):  
Web Of Science ◽  
Research Work ◽  
Future Research ◽  
Research Development ◽  
Learning Context ◽  
Context Model ◽  
Main Research ◽  
E Learning ◽  
Learning Research ◽  
Popular Language

This study is a productivity review on the literature gleaned from web of science databases concerning recommendation in E-Learning research. The result indicates that the number of literature productions on this topic is growing in recently 4 years, approximately the same number in 2008, 2009 and 2011. The main research development country is Taiwan, and from the analysis of the distribution of language, English is the most popular language. Moreover the research focuses on are mainly context model and system design to explore fundamental components of E-Learning context and offer a learning environment suitable for users, also the limitations and future research of these research were discussed, so that the direction for future research work can be explored.

scholarly journals A multi-stakeholder approach to the co-production of the research agenda for medicines optimisation

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
John Fellenor ◽  
Nicky Britten ◽  
Molly Courtenay ◽  
Rupert A. Payne ◽  
Jose Valderas ◽  
...  
Keyword(s):  
Research Agenda ◽  
Public Involvement ◽  
Stakeholder Group ◽  
Nominal Group ◽  
Future Research ◽  
Medicines Use ◽  
Wide Range ◽  
Research Questions ◽  
Medicines Optimisation ◽  
Multi Stakeholder

Abstract Background Up to 50% of medicines are not used as intended, resulting in poor health and economic outcomes. Medicines optimisation is ‘a person-centred approach to safe and effective medicines use, to ensure people obtain the best possible outcomes from their medicines’. The purpose of this exercise was to co-produce a prioritised research agenda for medicines optimisation using a multi-stakeholder (patient, researcher, public and health professionals) approach. Methods A three-stage, multiple method process was used including: generation of preliminary research questions (Stage 1) using a modified Nominal Group Technique; electronic consultation and ranking with a wider multi-stakeholder group (Stage 2); a face-to-face, one-day consensus meeting involving representatives from all stakeholder groups (Stage 3). Results In total, 92 research questions were identified during Stages 1 and 2 and ranked in order of priority during stage 3. Questions were categorised into four areas: ‘Patient Concerns’ [e.g. is there a shared decision (with patients) about using each medicine?], ‘Polypharmacy’ [e.g. how to design health services to cope with the challenge of multiple medicines use?], ‘Non-Medical Prescribing’ [e.g. how can the contribution of non-medical prescribers be optimised in primary care?], and ‘Deprescribing’ [e.g. what support is needed by prescribers to deprescribe?]. A significant number of the 92 questions were generated by Patient and Public Involvement representatives, which demonstrates the importance of including this stakeholder group when identifying research priorities. Conclusions A wide range of research questions was generated reflecting concerns which affect patients, practitioners, the health service, as well the ethical and philosophical aspects of the prescribing and deprescribing of medicines. These questions should be used to set future research agendas and funding commissions.

scholarly journals A multi-stakeholder approach to the co-production of the research agenda for medicines optimisation

2020 ◽  
Author(s):  
John Fellenor ◽  
Nicky Britten ◽  
Molly Courtenay ◽  
Rupert A Payne ◽  
Jose Valderas ◽  
...  
Keyword(s):  
Research Agenda ◽  
Public Involvement ◽  
Stakeholder Group ◽  
Nominal Group ◽  
Future Research ◽  
Medicines Use ◽  
Wide Range ◽  
Research Questions ◽  
Medicines Optimisation ◽  
Multi Stakeholder

Abstract Background Up to 50% of medicines are not used as intended, resulting in poor health and economic outcomes. Medicines optimisation is ‘a person-centred approach to safe and effective medicines use, to ensure people obtain the best possible outcomes from their medicines’. The purpose of this exercise was to co-produce a prioritised research agenda for medicines optimisation using a multi-stakeholder (patient, researcher, public and health professionals) approach. Methods A three-stage, multiple method process was used including: generation of preliminary research questions (Stage 1) using a modified Nominal Group Technique; electronic consultation and ranking with a wider multi-stakeholder group (Stage 2); a face-to-face, one-day consensus meeting involving representatives from all stakeholder groups (Stage 3). Results In total, 92 research questions were identified during Stages 1 and 2 and ranked in order of priority during stage 3. Questions were categorised into four areas: ‘Patient Concerns’ [e.g. is there a shared decision (with patients) about using each medicine?], ‘Polypharmacy’ [e.g. how to design health services to cope with the challenge of multiple medicines use?], ‘Non-Medical Prescribing’ [e.g. how can the contribution of non-medical prescribers be optimised in primary care?], and ‘Deprescribing’ [e.g. what support is needed by prescribers to deprescribe?]. A significant number of the 92 questions were generated by Patient and Public Involvement representatives, which demonstrates the importance of including this stakeholder group when identifying research priorities. Conclusions A wide range of research questions was generated reflecting concerns which affect patients, practitioners, the health service, as well the ethical and philosophical aspects of the prescribing and deprescribing of medicines. These questions should be used to set future research agendas and funding commissions.

Top secret from the bottom up

2017 ◽  
Vol 22 (4) ◽  
pp. 556-561
Author(s):  
Craig R. Scott ◽  
SoeYoon Choi
Keyword(s):  
Private Sector ◽  
Word Processing ◽  
Corporate Communication ◽  
Future Research ◽  
Content Type ◽  
Wide Range ◽  
Challenges And Opportunities ◽  
Research Questions ◽  
State Organizations ◽  
Public Society

Purpose The emerging area of message classification is one of growing relevance to a wide range of organizational communicators as a variety of non-state organizations and their members increasingly use and misuse various terms to restrict their communication. This includes formal classifications for data security, financial/knowledge management, human resources, and other functions as well as those used informally by organizational members. Especially in a data-rich environment where our word-processing programs, e-mail tools, and other technologies afford us opportunities to engage in classification, a wide range of people at all organizational levels may serve as custodians of their own data and thus have the ability (as well as perhaps the need) to classify messages in various ways. The purpose of this paper is to describe key classification terms ranging from those found in government (e.g. top secret, confidential) to those in the private sector (e.g. business use only, trademarked) to an even wider set of terms used informally by organizational members (e.g. personal, preliminary). The growing use of message classifications will likely create various challenges and opportunities for organizations, their members, and the broader public/society. A set of future research questions is offered for corporate communication researchers and practitioners, who are well positioned to examine this emerging phenomenon. Design/methodology/approach This paper draws on existing literature related to the growing use of message classifications to offer a list of classification terms and an agenda for future research. Findings This work describes key classification terms ranging from those found in government (e.g. top secret, confidential) to those in the private sector (e.g. business use only, trademarked) to an even wider set of terms used informally by organizational members (e.g. personal, preliminary). This expanded notion of classification will likely create various challenges and opportunities for organizations, their members, and the broader public/society. Originality/value The emerging area of message classification is one of growing relevance to a wide range of organizational communicators as a variety of non-state organizations and their members increasingly use and misuse various terms to restrict their communication. A set of future research questions is offered for corporate communication researchers and practitioners, who are well positioned to examine this emerging phenomenon.

scholarly journals The Effects of Gender and Age on Students’ Use of a Learning Management System in Saudi Arabia

2020 ◽  
pp. 135-145
Author(s):  
Ahmed Alshehri ◽  
◽  
Malcolm J. Rutter ◽  
Sally Smith
Keyword(s):  
Management System ◽  
Structural Equation ◽  
Learning Management System ◽  
National Level ◽  
Future Research ◽  
Research Approach ◽  
Learning Context ◽  
Gender And Age ◽  
E Learning ◽  
Learning Management

The success of an e-learning intervention relies, to a considerable extent, on the student’s acceptance of the system. Still, the challenge for educational institutions is to determine the factors that influence the user’s acceptance of a Learning Management System (LMS) particularly, the demographic variables of age and gender, which would allow for effective approaches to implementation. Therefore, this study aims to analyse the moderating effects of gender and age in the acceptance and use of an LMS. Furthermore, the study is located in a Saudi tertiary learning context where students have unique psychological and social characteristics and where LMS are being rolled out on a national level. To this end, the study utilised a UTAUT (Unified Theory of Acceptance and Use of Technology) model as a base model, with an additional six usability variables, to investigate empirically the variables that influence the students’ use of an LMS in Saudi higher education. By using a quantitative research approach and a sample size of 605 students, data were collected from students in five Saudi universities. Partial Least Squares Structural Equation Modelling (PLS-SEM) in conjunction with multigroup analysis techniques were employed to assess the model. The findings revealed that both gender and age moderated a single association between the facilitating conditions and actual use where female and younger students exhibited higher perceptions of the association than did their counterparts. The research has several implications for decision-makers, administrators and designers of e-learning systems. In light of the study findings, the limitations and future research avenues were discussed.

Sign in / Sign up

Export Citation Format

Share Document