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

Tracking #: 2467-3681

Yi Wang
Ying Wang

Responsible editor: 
Aldo Gangemi

Submission type: 
Survey Article
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 2018. 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.
Full PDF Version: 

Major Revision

Solicited Reviews:
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Review #1
By Francesco Orciuoli submitted on 29/Jun/2020
Review Comment:

(review consisted only of confidential comments to the editors. The reviewer already suggested "accept" for the previous version)

Review #2
By Herminio Garcia-Gonzalez submitted on 02/Jul/2020
Major Revision
Review Comment:

This is a revision of a previous submission called “A Survey of Semantic Technology and Ontology for e-Learning” which I reviewed with a Major Revision decision. First of all, I have to thank the authors for the effort they have made submitting a new version of this article. Now, the paper is more coherent and cohesive which makes it easier to follow. In addition, the use of the suggested tables and figures gives a better grasp of works differences and similarities. Sections 1, 2 and 3 are now clearer and they show more evidently the need for this survey. However, I have to say that the rest of the paper still remains a bit confusing to me and, sometimes, hard to follow.

In Section 4, it is interesting how different works are evaluated by categories. However, in tables, a brief description or a brief note on the contributions or differences of the mentioned ontology respect to other ones in the same category is missing. In different subsections only some works are cited but not all the surveyed ones. This makes more important the above mentioned brief description, because without it I am forced to look for the title on the references or to search the article to see the actual differences. Moreover, these subsections are written like a related work section of a research paper which does not give and added value to this survey. I already gave this comment on the previous review but it was not well addressed or understood in this new version.

Section 5 suffers from the same problems as Section 4 but in this case Table 9 seems clearly insufficient. Even, not all works cited in Section 5 are present in Table 9. I do not understand why. It is also written like a related work without a good interconnection nor a fluent story between them.

About conclusions and some other discussion sections along the paper I think that, even though they are OK and are coherent with analysed data, they are a bit simple without any further analysis.

I would recommend to the authors to review these aspects deeply to polish a future version. Due to the given reasons and, because the main problems are still not well solved I opted for a Major Revision.

Review #3
By Aldo Gangemi submitted on 08/Nov/2020
Minor Revision
Review Comment:

I appreciate the substantial work carried out by the authors in revising their manuscript. It is now suitable as an introductory text, it looks more balanced and readable, and contains some relevant material for the Semantic Web community.
Therefore, I am in favour of updating the paper status to Minor Revisions (another Major would reject it), in order to support its publication.
However, now that the paper has a proper ordering, I realise that a section is missing to become fully beneficial, i.e. an analysis of the e-learning semantics covered by the ontologies.
In other words, while you have analysed the usage of ontology engineering in e-learning, and how methods have been applied, by topic, yet the reader misses how core concepts and relations in the different topics are represented in different works, so missing a guide in reusing any of those ontologies when designing a new e-learning system.
I realise it'd be difficult to perform a complete conceptual exploration of more than a hundred models, but probably each subtopic that you have analysed has core conceptual issues, which could be recognised in each of the ontologies, and a commented guide to their presence in different works would be great. This would also enable researchers to test how different ontologies have tackled similar problems.