Automatic Generation of Educational Quizzes from Domain Ontologies

International audienceEducational quizzes are very valuable resources to test or evaluate the knowledge acquired by learners and to support lifelong learning on various topics or subjects, in an informal and entertaining way. The production of quizzes is a very time-consuming task and its automation is thus a real challenge in e-Education. In this paper, we address the research question of how to automate the generation of quizzes by taking advantage of existing knowledge sources available on the Web. We propose an approach that allows learners to take advantage of the knowledge captured in domain ontologies available on the Web and to discover or acquire a more in-depth knowledge of a specific domain by solving educational quizzes automatically generated from an ontology modelling the domain. The implementation and experimentation of our approach is presented through the use case of a world-famous French game of manually generated multiple-choice questions

Automatic generation of quizzes for museums using Deep Learning techniques

Trabajo de Fin de Máster en Internet de las Cosas, Facultad de Informática UCM, Departamento de Ingeniería del Software e Inteligencia Artificial, Curso 2020/2021En este trabajo se presenta el diseño de un algoritmo que permite obtener respuestas incorrectas a preguntas de donde se conoce la contestación correcta, empleando tecnologías de Web Semántica y técnicas de Deep Learning. Se plantea como entorno de explotación un minijuego, que se encuentra desplegado en el Museo de Ciencias Naturales de Madrid. El juego se basa en las áreas de las exposiciones como la evolución de la vida en la Tierra, que abarcan desde los primeros microorganismos hasta el Homo Sapiens, por medio de colección de fósiles, esqueletos, reconstrucciones e ilustraciones que recrean la vida en la Tierra en sus diferentes eras o etapas. Sobre esta base, se plantea la posibilidad de ampliar la programación del juego, en cuanto a un algoritmo que permita definir cuestionarios de tipo pregunta de opción múltiple, en donde habrá una respuesta correcta y tres incorrectas, con posibilidad de establecer niveles de conocimiento. La experiencia irá dirigida a famosos paleontólogos y sitios paleontológicos. Para esto, se emplean tecnologías de la Web Semántica como DBpedia y su variante SpotLigh, Wikidata, Wikipedia, Yago y técnicas de Deep Learning como es el caso de Word2Vect.This paper presents the design of an algorithm that allows to obtain incorrect answers to questions where the correct answer is known using Semantic Web technologies and Deep Learning techniques. A mini-game, which is deployed in the Museum of Natural Sciences of Madrid, is proposed as an operating environment. The game is based on the areas of exhibitions such as the evolution of life on Earth, ranging from the first microorganisms to Homo Sapiens, through a collection of fossils, skeletons, reconstructions, and illustrations that recreate life on Earth in its different eras or stages. On this basis, the possibility of extending the programming of the game, regarding the methodology for defining questionnaires question multiple choice type, where there will be a correct answer and three incorrect arises. The experience will be aimed at famous paleontologists and paleontological sites. For this, Semantic Web technologies are used as DBpedia and its variant Spotligh, Wikidata, Wikipedia, Yago and Deep Learning techniques as in the case of Word2Vect.Depto. de Ingeniería de Software e Inteligencia Artificial (ISIA)Fac. de InformáticaTRUEunpu

A Survey of the First 20 Years of Research on Semantic Web and Linked Data

International audienceThis paper is a survey of the research topics in the field of Semantic Web, Linked Data and Web of Data. This study looks at the contributions of this research community over its first twenty years of existence. Compiling several bibliographical sources and bibliometric indicators , we identify the main research trends and we reference some of their major publications to provide an overview of that initial period. We conclude with some perspectives for the future research challenges.Cet article est une étude des sujets de recherche dans le domaine du Web sémantique, des données liées et du Web des données. Cette étude se penche sur les contributions de cette communauté de recherche au cours de ses vingt premières années d'existence. En compilant plusieurs sources bibliographiques et indicateurs bibliométriques, nous identifions les principales tendances de la recherche et nous référençons certaines de leurs publications majeures pour donner un aperçu de cette période initiale. Nous concluons avec une discussion sur les tendances et perspectives de recherche

Ontologies for automatic question generation

Assessment is an important tool for formal learning, especially in higher education. At present, many universities use online assessment systems where questions are entered manually into a question bank system. This kind of system requires the instructor’s time and effort to construct questions manually. The main aim of this thesis is, therefore, to contribute to the investigation of new question generation strategies for short/long answer questions in order to allow for the development of automatic factual question generation from an ontology for educational assessment purposes. This research is guided by four research questions: (1) How well can an ontology be used for generating factual assessment questions? (2) How can questions be generated from course ontology? (3) Are the ontological question generation strategies able to generate acceptable assessment questions? and (4) Do the topic-based indexing able to improve the feasibility of AQGen. We firstly conduct ontology validation to evaluate the appropriateness of concept representation using a competency question approach. We used revision questions from the textbook to obtain keyword (in revision questions) and a concept (in the ontology) matching. The results show that only half of the ontology concepts matched the keywords. We took further investigation on the unmatched concepts and found some incorrect concept naming and later suggest a guideline for an appropriate concept naming. At the same time, we introduce validation of ontology using revision questions as competency questions to check for ontology completeness. Furthermore, we also proposed 17 short/long answer question templates for 3 question categories, namely definition, concept completion and comparison. In the subsequent part of the thesis, we develop the AQGen tool and evaluate the generated questions. Two Computer Science subjects, namely OS and CNS, are chosen to evaluate AQGen generated questions. We conduct a questionnaire survey from 17 domain experts to identify experts’ agreement on the acceptability measure of AQGen generated questions. The experts’ agreements for acceptability measure are favourable, and it is reported that three of the four QG strategies proposed can generate acceptable questions. It has generated thousands of questions from the 3 question categories. AQGen is updated with question selection to generate a feasible question set from a tremendous amount of generated questions before. We have suggested topic-based indexing with the purpose to assert knowledge about topic chapters into ontology representation for question selection. The topic indexing shows a feasible result for filtering question by topics. Finally, our results contribute to an understanding of ontology element representation for question generations and how to automatically generate questions from ontology for education assessment

Distributed Semantic Social Networks: Architecture, Protocols and Applications

Online social networking has become one of the most popular services on the Web. Especially Facebook with its 845Mio+ monthly active users and 100Mrd+ friendship relations creates a Web inside the Web. Drawing on the metaphor of islands, Facebook is becoming more like a continent. However, users are locked up on this continent with hardly any opportunity to communicate easily with users on other islands and continents or even to relocate trans-continentally. In addition to that, privacy, data ownership and freedom of communication issues are problematically in centralized environments. The idea of distributed social networking enables users to overcome the drawbacks of centralized social networks. The goal of this thesis is to provide an architecture for distributed social networking based on semantic technologies. This architecture consists of semantic artifacts, protocols and services which enable social network applications to work in a distributed environment and with semantic interoperability. Furthermore, this thesis presents applications for distributed semantic social networking and discusses user interfaces, architecture and communication strategies for this application category.Soziale Netzwerke gehören zu den beliebtesten Online Diensten im World Wide Web. Insbesondere Facebook mit seinen mehr als 845 Mio. aktiven Nutzern im Monat und mehr als 100 Mrd. Nutzer- Beziehungen erzeugt ein eigenständiges Web im Web. Den Nutzern dieser Sozialen Netzwerke ist es jedoch schwer möglich mit Nutzern in anderen Sozialen Netzwerken zu kommunizieren oder aber mit ihren Daten in ein anderes Netzwerk zu ziehen. Zusätzlich dazu werden u.a. Privatsphäre, Eigentumsrechte an den eigenen Daten und uneingeschränkte Freiheit in der Kommunikation als problematisch empfunden. Die Idee verteilter Soziale Netzwerke ermöglicht es, diese Probleme zentralisierter Sozialer Netzwerke zu überwinden. Das Ziel dieser Arbeit ist die Darstellung einer Architektur verteilter Soziale Netzwerke welche auf semantischen Technologien basiert. Diese Architektur besteht aus semantischen Artefakten, Protokollen und Diensten und ermöglicht die Kommunikation von Sozialen Anwendungen in einer verteilten Infrastruktur. Darüber hinaus präsentiert diese Arbeit mehrere Applikationen für verteilte semantische Soziale Netzwerke und diskutiert deren Nutzer-Schnittstellen, Architektur und Kommunikationsstrategien. 

Assessing cognitive presence using automated learning analytics methods

With the increasing pace of technological changes in the modern society, there has been a growing interest from educators, business leaders, and policymakers in teaching important higher-order skills which were identified as necessary for thriving in the present-day globalized economy. In this regard, one of the most widely discussed higher order skills is critical thinking, whose importance in shaping problem solving, decision making, and logical thinking has been recognized. Within the domain of distance and online education, the Community of Inquiry (CoI) model provides a pedagogical framework for understanding the critical dimensions of student learning and factors which impact the development of student critical thinking. The CoI model follows the social-constructivist perspective on learning in which learning is seen as happening in both individual minds of learners and through the discourse within the group of learners. Central to the CoI model is the construct of cognitive presence, which captures the student cognitive engagement and the development of critical thinking and deep thinking skills. However, the assessment of cognitive presence is challenging task, particularly given its latent nature and the inherent physical and time separation between students and instructors in distance education settings. One way to address this problem is to make use of the vast amounts of learning data being collected by learning systems. This thesis presents novel methods for understanding and assessing the levels of cognitive presence based on learning analytics techniques and the data collected by learning environments. We first outline a comprehensive model for cognitive presence assessment which builds on the well-established evidence-cantered design (ECD) assessment framework. The proposed assessment model provides a foundation of the thesis, showing how the developed analytical models and their components fit together and how they can be adjusted for new learning contexts. The thesis shows two distinct and complementary analytical methods for assessing students’ cognitive presence and its development. The first method is based on the automated classification of student discussion messages and captures learning as it is observed in the student dialogue. The second analytics method relies on the analysis of log data of students’ use of the learning platform and captures the individual dimension of the learning process. The developed analytics also extend current theoretical understanding of the cognitive presence construct through data-informed operationalization of cognitive presence with different quantitative measures extracted from the student use of online discussions. We also examine methodological challenges of assessing cognitive presence and other forms of cognitive engagement through the analysis of trace data. Finally, with the intent of enabling for the wider adoption of the CoI model for new online learning modalities, the last two chapters examine the use of developed analytics within the context of Massive Open Online Courses (MOOCs). Given the substantial differences between traditional online and MOOC contexts, we first evaluate the suitability of the CoI model for MOOC settings and then assess students’ cognitive presence using the data collected by the MOOC platform. We conclude the thesis with the discussion of practical application and impact of the present work and the directions for the future research