We present an education standards ontology that has the potential for simplifying lesson planning for teachers, providing support for students by linking relevant resources, and providing a potential terminology for use in a lingua-franca for communicating with multiple communities about education components. We address the United Nations sustainable development goals concerned with education, with the support of semantic technologies. The goals of ensuring that all children graduate from primary and secondary schools and ensuring literacy and numeracy are our targets. We have created an education standards ontology along with a methodology for automatically generating this ontology. In this submission, we review literature related to educational applications that use semantic technologies and describe a web scraping method that we designed and used to automatically generate an education standards ontology. We also describe some potential uses of this ontology to assist in the UN education goals and reflect on next steps on uses of these existing educational resources to aide in improving literacy and numeracy in students and enabling future potential services and impact for an Educational Semantic Web.
Shortly after the 2001 article presenting the vision of the Semantic Web [
Since the Semantic Web 3.0 has more features than its hypertext-based Web
2.0 predecessor, educators may not be versed in the added functionality, or they
may not have enough motivation and time to perform manual annotations of
resources that may be needed to efectively enable use of some of the advanced
Web 3.0 resources. For humans, education is traditionally an interactive,
personal experience, or as one educator describes, “an artistic, social interchange
rather than one waiting for enhancement and possible substitution by a
humanmachine interaction [
The Common Core standards for mathematics [
In order to assess one’s knowledge, students often take examinations
throughout the academic year to determine if educational standards are being met.
Problems frequently arise when students prepare for these tests, as students often find
themselves frustrated as to which methods to use to approach certain problems
[
Our contributions include a literature review on the Educational Semantic Web domain, an automatic extraction method to generate an education standards ontology from web content, and the resulting open source ontology. The Python-based extraction code is available on GitHub3. We also have published
the generated education standards ontology in order to aid with the linking of education standards in semantic education applications4. Finally, we describe a vision of a semantically-enabled education of the future. 2
Semantic Web for education may leverage work from a wide range of areas. We identify some foundations in the areas of learning objects, semantic grid frameworks, content modeling, mobile learning, data science-driven learning, and open scholarship. 2.1
Building on earlier notions of a Learning Object (LO), in the context of
technology aided e-learning [
Other e-learning systems in the 2000s began to leverage both education grid
systems as well as ontologies. The Semantic Grid-based E-Learning Framework
(SELF) [
OntoEdu [
activity description can be used by a teacher to restrict a sequence of actions
such that a student must select a lesson before selecting a homework set.
Recent work in the e-learning direction includes an OWL ontology for metadata of
Interactive Learning Objects (ILO), created using the ILO Standard to permit
user interaction in eTutor applications [
In order to consider the impacts of the Semantic Web (Web 3.0) on education,
it is fruitful to reflect on the impacts of the hypertext-based web (Web 2.0).
Almost all levels of education today use at least Web 2.0 with support ranging
from managing course websites to discovering research articles on the Internet,
and much more. The Semantic Web implies a change in web architecture to go
beyond static HTML. As people have learned to use the hypertext model of Web
2.0, they can similarly learn how to use Semantic Web RDF model as they see
the value proposition, eventually resulting in a potential improvement on future
education [
Educator Greg Kearsley argues however that busy teachers will not have
time to become ‘hyperkrep (hypertextual knowledge representation) hackers’
and adoption of technologies will require simplicity from the end user
perspective [
Even before the aforementioned journal discussion, ontologies were beginning
to be used to model hypermedia content, such as with Ontoportal, a framework
for building web-based educational portals [
The teacher TPortal includes concepts aimed at experts and institutions,
including concepts related to teaching, assessment, and support materials. The
student XPortal additionally includes tutorials, courses, evaluation materials,
and standards. Similarly, a recent educational domain ontology designed for a
case study for the University of Palestine [
With the rise in popularity of mobile phones and the development of hand-held
technology for education, the idea of Mobile- or M-Learning naturally emerges
[
A recent M-Learning System aims to address this concern for the Arabic
language by designing a mobile story-telling application that links to related images
by using Natural Language Processing (NLP) techniques for Arabic text
extraction [
The Big Data to Knowledge (BD2K) initiative to facilitate both in-person and
online learning has resulted in the Educational Resource Discovery Index
(ERuDIte). ERuDIte has been applied in the context of general data science [
The Data Science Education Ontology (DSEO) uses data science methods to teach data science, and includes an ontology of learning domains. We plan to build a tutoring system that connects concepts from the DSEO with concepts from our ontology. By connecting mathematics standards to statistical terms, we can determine practice problems for the student to solve. 2.6
As the Semantic Web is decreasing ambiguity by supporting explicit term
definitions for use by both humans and machines, and a major goal of Web 3.0 is
related to data integration and interoperability, the implications on education
are plentiful [
An open scholarship environment, which includes sharing articles, code, data,
and education resources, can improve research and education [
While there are numerous resources on the web related to education, many
were designed under the hypertext paradigm of Web 2.0. For example, the
Common Core Standards website5 is written in Javascript and HTML and does not
leverage the more expressive RDF representation, resulting in dificulties and/or
limitations in machine understanding. Even though these websites are typically
not encoded in a Semantic Web language (that would encourage more structure
and links), we still observe some hierarchy and structure often including sets of
organized links. By observing the HTML structure of a web page, it is possible
to extract information in a structured way by leveraging web scraping libraries
such as BeautifulSoup [
The Common Core website is divided into two main portals, one for mathematics topics6 and another for English Language Arts7. Each of these pages contains a well-structured HTML sidebar, which links to each set of standards for given grade levels and topics. By selecting specific HTML tags and list items from the sidebars, we are able to traverse each link and extract relevant information that is used to generate ontology classes with labels, comments, and the subsumption hierarchy. We also capture provenance by connecting the URL of each link to the corresponding concept using prov:wasQuotedFrom. Using this methodology, we are able to generate 1906 ontology classes. A subset of the concepts from the English Language Arts standards associated with speaking and listening is shown in Figure 1. 4
An oft-quoted proverb states, “Give a man a fish, and you feed him for a day. Teach a man to fish, and you feed him for a lifetime.” Analogously, we believe students will benefit from learning how to learn. We expect open access learning resources will aide in self-learning. The Education Standards Ontology can be used to help students align the knowledge they gain with standards in the Common Core. Self-guided learning will not only support learning required in standard education systems but will also provide a foundation that will support “continuous learning” beyond primary or secondary education. Further, in today’s interdisciplinary world where many people often become self-taught experts or near-experts in new areas, we expect increased need for evaluating expertise and communicating that evaluation. Open ontologies and ontologyenabled environments that use well defined terms and that are aligned with published standards can provide a foundation for communication and comparison. 4.1
In today’s teaching approaches, we often find that lessons are taught in a standardized way, despite a multitude of students with varying learning rates and interests. This results in dificulties for students who learn at a slower pace and disengagement (or boredom) for higher performing students. Furthermore, individuals may have diferent learning styles (auditory, kinesthetic, or visual), often based on the way their brain processes information. We foresee an increase in personalized learning environments, where the approaches to conveying knowledge are targeted towards individual students’ needs, sometimes in response to special needs students.
In order for precision systems such as personalized learning environments to be successful, it is important to evaluate how well a student is receiving the
material being taught. Unfortunately, representative measurements of student progress are dificult to obtain, as much is left out in the examination process and complicating factors such as test anxiety sometimes skew results. A wide range of additional learning assessment technologies, including for example biometric measures of physiological indicators, to evaluate information reception may be included. Semantic annotations can provide support for connecting and integrating new assessment modalities. 4.2
In order for teachers to adopt new technologies, the value of the system has to
outweigh the learning barriers or ease of use issues. One such example includes
reliable automatic grading systems, as we are already beginning to see today.
Such platforms have been adopted because they are not overly complicated to
use, and are beneficial as they reduce the manual teacher workload. Question
answering capabilities of intelligent systems are continuously improving, from
search engines like Google to virtual assistants like Cortana [
Current day access to learning resources, including teaching materials, literature, and lesson plans, are often limited to students who are part of an academic institution. We predict expansion and improvement of remote access to learning resources. Physical class materials may be replaced by interactive materials, such as web-based learning resources.
Open access learning resources can benefit institutions, teachers, students, and parents by decreasing subscription fees, supporting customized lesson planning, and improving opportunities for learners globally. Also open-source resources help allow for collaborative learning and communication across communities.
We already see significant strides in terms of cloud-based education, where
teachers (and sometimes parents) have direct access to student homework, grades,
and projects. Students have direct access to course and library resources, and can
remotely attend lectures or watch video recordings. We are likely to see
intelligent classroom environments leverage sensor networks, as the Internet of Things
(IoT) [
Augmented reality techniques may be applied to learning environments, where virtual reality headsets can be used to add visual demonstrations to augment the physical classroom. Future augmented reality virtual classrooms may allow students and/or teachers to connect to a virtual reality environment where an educational lesson can take place. Of course, this does not have to be a classroom in the traditional sense, as virtual field-trips may provide methods for learners to witness world wonders, the outer reaches of space, or interactions at the molecular level. With virtual applications, learning can be fun rather than a chore; game-like simulations can provide enriching, interactive, and enjoyable environments. The efects of a virtual classroom are likely to have a huge impact in terms of social networking, in a sense the Facebook of the future. Ontologies will be used to semi-automatically create and connect virtual environments. 5
We introduce an approach for automatically generating an education standards ontology from the Common Core website. It should be noted that the extraction code is specific to the Common Core website, as we observe the HTML structure of the relevant web pages in order to know from where to extract concepts and descriptions. Despite minimal generality in the Common Core-specific script, the described approach of observing the HTML web structure of a page to automatically generate an ontology can be applied to other web pages. Future work includes exploring methods of automatic web scraping techniques that are robust or adaptable to the structure of the web page. More importantly, we believe a useful, relatively simply-generated ontology is produced.
In order to evaluate the value of our ontology, we plan to develop a smart tutoring framework that takes advantage of earlier education ontologies and uses the education standards ontology to link course concepts and questions to Common Core standards. This will help provide useful lessons to students who are in school districts that have adopted the Common Core, thereby potentially greatly simplifying lesson planning for teachers and providing much more support for students in the form of additional relevant resources. Such work has potential to improve literacy, numeracy, and graduation rates for students. 6
We reviewed literature related to Semantic Web and education applications. We identified active research for at least the last 15 years, with researchers publishing methods related to the use of learning objects, semantic grid frameworks, content modeling, mobile learning, and open scholarship. We describe the automatic extraction method we used to generate an education standards ontology. We have made both the extraction script and generated ontology publicly available in order to encourage collaboration and reuse. We also discuss some ways in which the education ontology and an ontology-enabled infrastructure can advance realizing the vision of the Educational Semantic Web.
This work was partially supported by the RPI Tetherless World Constellation. We thank the members of the Constellation for their suggestions, in particular Rebecca Cowan.