Refining Non-Taxonomic Relation Labels with External Structured Data to Support Ontology Learning

This paper presents a method to integrate external knowledge sources such as DBpedia and OpenCyc into an ontology learning system that automatically suggests labels for unknown relations in domain ontologies based on large corpora of unstructured text. The method extracts and aggregates verb vectors from semantic relations identified in the corpus. It composes a knowledge base which consists of (i) verb centroids for known relations between domain concepts, (ii) mappings between concept pairs and the types of known relations, and (iii) ontological knowledge retrieved from external sources. Applying semantic inference and validation to this knowledge base yields a refined relation label suggestion. A formal evaluation compares the accuracy and average ranking precision of this hybrid method with the performance of methods that solely rely on corpus data and those that are only based on reasoning and external data sources

LiDom builder: Automatising the construction of multilingual domain modules

136 p.Laburpena Lan honetan LiDOM Builder tresnaren analisi, diseinu eta ebaluazioa aurkezten dira. Teknologian oinarritutako hezkuntzarako tresnen Domeinu Modulu Eleaniztunak testuliburu elektronikoetatik era automatikoan erauztea ahalbidetzen du LiDOM Builderek. Ezagutza eskuratzeko, Hizkuntzaren Prozesamendurako eta Ikaste Automatikorako teknikekin batera, hainbat baliabide eleaniztun erabiltzen ditu, besteak beste, Wikipedia eta WordNet.Domeinu Modulu Elebakarretik Domeinu Modulu Eleaniztunerako bidean, LiDOM Builder tresna DOM-Sortze ingurunearen (Larrañaga, 2012; Larrañaga et al., 2014) bilakaera dela esan genezake. Horretarako, LiDOM Builderek domeinua ikuspegi eleaniztun batetik adieraztea ahalbidetzen duen mekanismoa dakar. Domeinu Modulu Eleaniztunak bi maila ezberdinetako ezagutza jasotzen du: Ikaste Domeinuaren Ontologia (IDO), non hizkuntza ezberdinetan etiketatutako topikoak eta hauen arteko erlazio pedagogikoak jasotzen baitira, eta Ikaste Objektuak (IO), hau da, metadatuekin etiketatutako baliabide didaktikoen bilduma, hizkuntza horietan. LiDOM Builderek onartutako hizkuntza guztietan domeinuaren topikoak adierazteko aukera ematen du. Topiko bakoitza lotuta dago dagokion hizkuntzako bere etiketa baliokidearekin. Gainera, IOak deskribatzeko metadatu aberastuak erabiltzen ditu hizkuntza desberdinetan parekideak diren baliabide didaktikoak lotzeko.LiDOM Builderen, hasiera batean, domeinu-modulua hizkuntza jakin batean idatzitako dokumentu batetik erauziko da eta, baliabide eleaniztunak erabiliko dira, gerora, bai topikoak bai IOak beste hizkuntzetan ere lortzeko. Lan honetan, Ingelesez idatzitako liburuek osatuko dute informazio-iturri nagusia bai doitze-prozesuan bai ebaluazio-prozesuan. Zehazki, honako testuliburu hauek erabili dira: Principles of Object Oriented Programming (Wong and Nguyen, 2010), Introduction to Astronomy (Morison, 2008) eta Introduction to Molecular Biology (Raineri, 2010). Baliabide eleaniztunei dagokienez, Wikipedia, WordNet eta Wikipediatik erauzitako beste hainbat ezagutza-base erabili dira. Testuliburuetatik Domeinu Modulu Eleaniztunak eraikitzeko, LiDOM Builder hiru modulu nagusitan oinarritzen da: LiTeWi eta LiReWi moduluak IDO eleaniztuna eraikitzeaz arduratuko dira eta LiLoWi, aldiz, IO eleaniztunak eraikitzeaz. Jarraian, aipatutako modulu bakoitza xehetasun gehiagorekin azaltzen da.¿ LiTeWi (Conde et al., 2015) moduluak, edozein ikaste-domeinutako testuliburu batetik abiatuta, Hezkuntzarako Ontologia bati dagozkion hainbat termino eleaniztun identifikatuko ditu, hala nola TF-IDF, KP-Miner, CValue eta Shallow Parsing Grammar. Hori lortzeko, gainbegiratu gabeko datu-erauzketa teknikez eta Wikipediaz baliatzen da. Ontologiako topikoak erauzteak LiTeWi-n hiru urrats ditu: lehenik hautagai diren terminoen erauzketa; bigarrenik, lortutako terminoen konbinatzea eta fintzea azken termino zerrenda osatuz; eta azkenik, zerrendako terminoak beste hizkuntzetara mapatzea Wikipedia baliatuz.¿ LiReWi (Conde et al., onartzeko) moduluak Hezkuntzarako Ontologia erlazio pedagogikoez aberastuko du, beti ere testuliburua abiapuntu gisa erabilita. Lau motatako erlazio pedagogikoak erauziko ditu (isA, partOf, prerequisite eta pedagogicallyClose) hainbat teknika eta ezagutza-base konbinatuz. Ezagutza-baseen artean Wikipedia, WordNet, WikiTaxonomy, WibiTaxonomy eta WikiRelations daude. LiReWi-k ere hiru urrats emango ditu erlazioak lortzeko: hasteko, ontologiako topikoak erlazioak erauzteko erabiliko diren ezagutza-base desberdinekin mapatuko ditu; gero, hainbat erlazio-erauzle, bakoitza teknika desberdin batean oinarritzen dena, exekutatuko ditu konkurrenteki erlazio hautagaiak erauzteko; eta, bukatzeko, lortutako emaitza guztiak konbinatu eta iragaziko ditu erlazio pedagogikoen azken multzoa lortuz. Gainera, DOM-Sortzetik LiDOM Buildererako trantsizioan, tesi honetan hobetu egin dira dokumentuen indizeetatik erauzitako isA eta partOf erlazioak, Wikipedia baliabide gehigarri bezala erabilita (Conde et al., 2014).¿ LiLoWi moduluak IOak -batzuk eleaniztunak- erauziko ditu, abiapuntuko testuliburutik ez ezik Wikipedia edo WordNet bezalako ezagutza-baseetatik ere. IDO ontologiako topiko bakoitza Wikipedia eta WordNet-ekin mapatu ostean, LiLoWi-k baliabide didaktikoak erauziko ditu hainbat IO erauzlez baliatuz.IO erauzketa-prozesuan, DOM-Sortzetik LiDOM Buildereko bidean, eta Wikipedia eta WordNet erabili aurretik, ingelesa hizkuntza ere gehitu eta ebaluatu da (Conde et al., 2012).LiDOM Builderen ebaluaziori dagokionez, modulu bakoitza bere aldetik testatua eta ebaluatua izan da bai Gold-standard teknika bai aditu-ebaluazioa baliatuz. Gainera, Wikipedia eta WordNet ezagutza-baseen integrazioak IOen erauzketari ekarri dion hobekuntza ere ebaluatu da. Esan genezake kasu guztietan lortu diren emaitzak oso onak direla.Bukatzeko, eta laburpen gisa, lau dira LiDOM Builderek Domeinu Modulu Eleaniztunaren arloari egin dizkion ekarpen nagusiak:¿ Domeinu Modulu Eleaniztunak adierazteko mekanismo egokia.¿ LiTeWiren garapena. Testuliburuetatik Hezkuntzarako Ontologietarako terminologia eleaniztuna erauztea ahalbidetzen du modulu honek. Ingelesa eta Gaztelera hizkuntzentzako termino-erauzlea eskura dago https://github.com/Neuw84/LiTe URLan.¿ LiReWiren garapena. Testuliburuetatik Hezkuntzarako Ontologietarako erlazio pedagogikoak erauztea ahalbidetzen du modulu honek. Erabiltzen duen Wikipedia/WordNet mapatzailea eskura dago https://github.com/Neuw84/Wikipedia2WordNet URLan.¿ LiLoWiren garapena. Testuliburua eta Wikipedia eta WordNet ezagutza-baseak erabilita IO eleaniztunak erauztea ahalbidetzen du modulu honek

Diagram-based intelligent tutoring systems

This work first presents two implementations of Intelligent Tutoring Systems (ITSs) on engineering undergraduate-level diagram education: StaticsTutor for free-body diagram and Thermo Cycle Tutor for refrigeration T-v diagram. Initial investigations on several groups of students have shown their educational effectiveness. Unlike text-based input, diagram has some intrinsic challenges that lead it hard to teach. One example is conceptual knowledge is highly interconnected with procedural knowledge. Learned from the two ITSs, we provided some general pedagogical guidelines for the future Diagram-based ITSs. Also, we learned classes can be used as a way of representing geometric shapes in diagrams. Thus, we extended our work to the generality of how the current approach can be applied to other domains. We chose a popular type of diagram, called Block Diagram, which contains geometric objects and lines/arrows in connecting them. We developed a methodology to represent a diagram’s information and an ontology of diagram evaluation processes to diagnose students\u27 diagrams. Our work contributes to the development of Diagram-based ITSs authoring tools

A Reference Computational Model to Manage the Semantics of Learning Environments using SWRL Enabled OWL Ontologies

This thesis proposes a reference model and its computational core to support the creation of software applications within educational environments, which address Differences In Learning (DiffInL) and are applicable to both learners and instructors. This work differs from others in that the strength of this model resides on the re-usable character of the reasoning mechanism enabled by the computational environment. The starting point is the definition of agreed learning goals that the learner needs to achieve. In turn, the reference model generates personalised, best-practice teaching and learning materials, suitable for achieving the individual’s learning goals. This reference model consists of MODEL and MANAGEMENT components. The MODEL components store the domain needed to create learners and instructional models, which are required for the creation of Learning Spaces (LeS). The MANAGEMENT compo- nent also manages the semantics stored in various model components in order to carry out the configuration of an LeS. The architecture of software applications generated from the reference model is illustrated and contains: Netbeans IDE 8.0.2, JavaServer Faces framework and OWL-API library. We tested this to generate teaching practices for Learning Difficulties (LDif) student. In order to prove the feasibility of creating a software application from the reference model, an example of a particular scenario in a specific educational setting for LDif Students has been shown. This proposed model has successfully proved its ability to address the needs of LDif Students through a corresponding novel and re-usable reasoning mechanism implemented in Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) computational environments. The reference model has shown its ability to integrate with different disciplines such as psychology, sociology and human-computer interactions. The main contribution to research is the creation of a novel reference computational model which addresses the needs of people with DiffInL. The strength of this model resides on the re-usable character of the reasoning mechanism enabled by the computational environment. The whole framework allows a unified implementation which takes into account classes, constraints, matching, and inference mechanisms for the complete configuration of an LeS. The suggested approach also differs from previous work in that it is personalised, and the applied reasoning rules are dynamic. Therefore this model can be constantly “tuned” according to the questions we may ask in such environments. Overall, the proposed reference model in this research offers a promising and feasible solution that can support current educational systems and benefit both learners and instructors. It also demonstrates the applicability of the latest technologies and would allow for future technologies to be incorporated, in order to enhance the model

Modelo para la generación de cursos virtuales usando tecnologías de la web semántica para sistemas de gestión de aprendizaje

La oferta de educación virtual crece rápidamente y a su vez el uso de entornos virtuales de aprendizaje (VLE). La mayoría de docentes explotan muy limitadamente los VLEs, debido a su conocimiento limitado de pedagogías y de las teorías de diseño instruccional. La revisión de la literatura analizada, dio como resultado que pocos modelos de diseño instruccional han incluido el uso de las tecnologías de la web semántica para sus soluciones educativas. Sin embargo, aquellos trabajos que toman en cuenta dichas tecnologías, se enfocan más en el contenido específico del diseño de curso y otros trabajos asumen que el docente debería conocer acerca de diseño instruccional. Esto permitió notar, que no se toma en cuenta aspectos como: el enfoque pedagógico, es decir las teorías de aprendizaje y/o de diseño instruccional, el contexto del curso y la secuencia de actividades. Adicionalmente, ninguno de los trabajos considera la integración a un VLE. Se identifica los factores que influyen en el modelado del proceso de creación de contenido educativo en cursos online para entornos LMS tradicionales, y se propone un Modelo para el proceso de construcción de cursos virtuales utilizando tecnologías de le web semántica como RDF, OWL, SWRL, SPARQL para sistemas de gestión de aprendizaje. Este modelo permite producir en forma estructurada, organizada y pedagógicamente asistida, las plantillas de cursos virtuales. Para plasmar el modelo se plantea una arquitectura que permite desarrollar módulos de creación de plantillas de cursos en el sistema de gestión de aprendizaje Moodle. Se acompaña de la descripción del desarrollo de los diferentes módulos de creación de cursos virtuales mediante la metodología SCRUM. Para validar el modelo propuesto se plantean dos estudios: el primero aplicado en docentes universitarios respecto a cuatro aspectos analizados: facilidad de uso, soporte pedagógico, satisfacción y tiempo; se observó que existe una diferencia significativa a favor de la construcción de cursos virtuales en un LMS en donde se incorpora el modelo propuesto. En el segundo estudio, aplicado en estudiantes universitarios, se observó que, en el aspecto de la facilidad de uso, sí existe una diferencia significativa a favor del uso del aula virtual usada por los estudiantes y que fue creada por un docente con el módulo que incorpora el modelo propuesto. Se afirma entonces que el modelo planteado ofrece mejoras con respecto al proceso de creación de aulas virtuales tradicional que se incorpora en un LMS.Abstract: The virtual education offer grows rapidly and, in turn, the use of virtual environment of learning (VLE). Most teachers exploit in a very limited way the VLEs due to the limited knowledge of the of pedagogy and instructional design theories. The analyzed systematic review of literature resulted in the fact that few models of instructional design have included the use of semantic web technologies for their educational solutions. However, those works that take into account such technologies focus more on the specific content of course design and other works assume that the teacher should know about the instructional design. This permitted to note that aspects such as the pedagogic focus (i.e., the learning theories and instructional design theories), the course context and the activity sequence are not considered. Additionally, no work considers the integration to a VLE. Factors influencing on the modelling of the creation process of educational content in online courses for traditional LMS environment are identified, and a Model for the construction process of virtual courses is proposed, using semantic web technologies such as RDF, OWL, SWRL, and SPARQL for learning management systems. This model can produce in a structured, organized and pedagogically-assisted way, the designs of virtual courses templates. To put into practice the model, an architecture allowing to develop modules of design creation of courses in the Moodle learning management system is stated. Included there is the description of the development of the different virtual course creation modules through SCRUM methodology. To validate the proposed model, two studies are stated: the first one is applied to university teachers as to four analyzed aspects: usability, pedagogic support, satisfaction and time. It is observed that there is a significant difference in favor of the construction of virtual courses in a LMS where the proposed model is incorporated. In the second study is applied to university students, it was observed that in the aspect of usability, there is a significant difference in favor of the use of the virtual classroom used by students, which was created by a teacher with a module incorporating the proposed model. It is, therefore, affirmed that the proposed model offers improvements as to the traditional creation process of virtual classrooms incorporated into an LMS.Doctorad