206 research outputs found
Hybrid human-AI driven open personalized education
Attaining those skills that match labor market demand is getting increasingly complicated as prerequisite knowledge, skills, and abilities are evolving dynamically through an uncontrollable and seemingly unpredictable process. Furthermore, people's interests in gaining knowledge pertaining to their personal life (e.g., hobbies and life-hacks) are also increasing dramatically in recent decades. In this situation, anticipating and addressing the learning needs are fundamental challenges to twenty-first century education. The need for such technologies has escalated due to the COVID-19 pandemic, where online education became a key player in all types of training programs. The burgeoning availability of data, not only on the demand side but also on the supply side (in the form of open/free educational resources) coupled with smart technologies, may provide a fertile ground for addressing this challenge. Therefore, this thesis aims to contribute to the literature about the utilization of (open and free-online) educational resources toward goal-driven personalized informal learning, by developing a novel Human-AI based system, called eDoer.
In this thesis, we discuss all the new knowledge that was created in order to complete the system development, which includes 1) prototype development and qualitative user validation, 2) decomposing the preliminary requirements into meaningful components, 3) implementation and validation of each component, and 4) a final requirement analysis followed by combining the implemented components in order develop and validate the planned system (eDoer).
All in all, our proposed system 1) derives the skill requirements for a wide range of occupations (as skills and jobs are typical goals in informal learning) through an analysis of online job vacancy announcements, 2) decomposes skills into learning topics, 3) collects a variety of open/free online educational resources that address those topics, 4) checks the quality of those resources and topic relevance using our developed intelligent prediction models, 5) helps learners to set their learning goals, 6) recommends personalized learning pathways and learning content based on individual learning goals, and 7) provides assessment services for learners to monitor their progress towards their desired learning objectives. Accordingly, we created a learning dashboard focusing on three Data Science related jobs and conducted an initial validation of eDoer through a randomized experiment. Controlling for the effects of prior knowledge as assessed by the pretest, the randomized experiment provided tentative support for the hypothesis that learners who engaged with personal eDoer recommendations attain higher scores on the posttest than those who did not. The hypothesis that learners who received personalized content in terms of format, length, level of detail, and content type, would achieve higher scores than those receiving non-personalized content was not supported as a statistically significant result
Design of an E-learning system using semantic information and cloud computing technologies
Humanity is currently suffering from many difficult problems that threaten the life and survival of the human race. It is very easy for all mankind to be affected, directly or indirectly, by these problems. Education is a key solution for most of them. In our thesis we tried to make use of current technologies to enhance and ease the learning process.
We have designed an e-learning system based on semantic information and cloud computing, in addition to many other technologies that contribute to improving the educational process and raising the level of students. The design was built after much research on useful technology, its types, and examples of actual systems that were previously discussed by other researchers.
In addition to the proposed design, an algorithm was implemented to identify topics found in large textual educational resources. It was tested and proved to be efficient against other methods. The algorithm has the ability of extracting the main topics from textual learning resources, linking related resources and generating interactive dynamic knowledge graphs. This algorithm accurately and efficiently accomplishes those tasks even for bigger books. We used Wikipedia Miner, TextRank, and Gensim within our algorithm. Our algorithm‘s accuracy was evaluated against Gensim, largely improving its accuracy.
Augmenting the system design with the implemented algorithm will produce many useful services for improving the learning process such as: identifying main topics of big textual learning resources automatically and connecting them to other well defined concepts from Wikipedia, enriching current learning resources with semantic information from external sources, providing student with browsable dynamic interactive knowledge graphs, and making use of learning groups to encourage students to share their learning experiences and feedback with other learners.Programa de Doctorado en IngenierÃa Telemática por la Universidad Carlos III de MadridPresidente: Luis Sánchez Fernández.- Secretario: Luis de la Fuente ValentÃn.- Vocal: Norberto Fernández GarcÃ
Evaluación de la Accesibilidad y Adaptabilidad de Objetos de Aprendizaje y cursos online a través de estándares y metadatos
El emprendimiento ha adquirido relevancia como tema de investigación en los últimos años. El individuo emprendedor tiene un rol influyente en la economÃa, por lo que entender sus motivaciones y aspiraciones es clave en esta investigación. El emprendimiento puede considerarse desde dos perspectivas, a nivel individual y desde el punto de vista de la organización, tratando asà el intraemprendimiento o emprendimiento corporativo. Asà pues, este trabajo tiene como objetivo principal analizar los diferentes niveles en los que se desarrolla la actividad emprendedora y entender el vÃnculo existente con las soft skills, permitiendo asà considerar esta actividad como elemento de dinamización. Para abordar el objetivo general planteado se ha estudiado en primera instancia la literatura anterior vinculada con el concepto de emprendimiento, la cual queda vinculada al entorno individual y organizacional. Posteriormente, se analizan las habilidades o soft skills determinantes como elementos influyentes que permiten el desarrollo y crecimiento emprendedor. De esta forma, se consigue abordar la repercusión de la actividad emprendedora e intraemprendedora desde una perspectiva general. En esta lÃnea, elementos como la creatividad y el conocimiento han quedado vinculados a lo largo de toda la investigación, puesto que los emprendedores requieren la actualización constante de conocimientos, y la búsqueda y el aprovechamiento de las oportunidades existentes. En consecuencia, esta investigación contribuye con el gap existente en la literatura y permite poner en valor las capacidades más relevantes en el entramado laboral, permitiendo con esto analizar los nuevos vÃnculos entre la sociedad y la iniciativa emprendedora. Las primeras aproximaciones de la investigación se han desarrollado a través del análisis de la base de datos European Skills, Competences, Qualifications and Occupations (ESCO), la cual ha permitido destacar las cualidades y competencias clave en el desarrollo emprendedor. A su vez, se ha realizado, como primer artÃculo de la tesis un análisis bibliométrico del concepto de emprendimiento. Con esto se ha conseguido destacar a los investigadores más representativos en este ámbito, y entender las redes y conexiones existentes entre ellos. De igual forma, se han destacado las palabras innovación y formación vinculadas a este concepto siendo clave para continuar con la investigación en el tema. A nivel del individuo se ha desarrollado un análisis de las motivaciones del emprendedor, quedando reflejado en el segundo artÃculo de la tesis. En este caso, la investigación ha examinado cómo influyen las variables de creatividad, comunicación y liderazgo en la decisión de convertirse en emprendedor en una situación prepandémica y en la situación actual, considerada como la nueva normalidad. En este sentido, la motivación emprendedora ha destacado por quedar influenciada por factores como la incertidumbre. Además, las variables creatividad, comunicación y liderazgo no son representativas en la presencia de emprendedores potenciales en la situación post-pandémica de nueva normalidad, sin embargo, sà que lo eran antes de la Covid-19. Por consiguiente, se vuelve necesario mencionar que debido a la Covid-19 se desarrolló un análisis comparativo, enriqueciendo en gran medida los resultados obtenidos. Por último, y debido a la dificultad que supone acceder a los datos estratégicos internos de las organizaciones, se han estudiado las variables que impactan en la estrategia de la empresa a través del desarrollo de una encuesta a 241 pequeñas y medianas empresas (PYMES). Esto, ha permitido considerar la influencia que ha tenido cada variable destacada en el análisis anterior, creatividad, comunicación y liderazgo, en la organización. En consecuencia, a través del tercer artÃculo se consigue un análisis en profundidad de la repercusión de la formación y las skills determinantes en la estrategia empresarial. Se investiga en este artÃculo si esas variables impactan directamente en el desarrollo de iniciativas intraemprendedoras. La investigación destaca la relevancia de la formación de los empleados en las organizaciones como componente diferencial y generador de valor. Asà pues, la formación en habilidades y competencias les permitirá desarrollar actividades emprendedoras, lo que ayudará a la toma de decisiones estratégicas y a la diferenciación en el actual mercado competitivo y cambiante
GELCO: Gamified Educational Learning Contents Ontology
Higher education students and teachers lack the necessary information to monitor and analyse student performance with respect to the learning experience and autonomous work during the semester. This research is based on the need for continuous improvement of student learning monitoring for students and teachers. It aims to combine ontologies with a monitoring platform, creating new ways of structuring and visualizing the elements of a course unit, of mapping and visualizing the dependencies between taught concepts and coursework, enabling the inference of new knowledge. The Gamified Educational Learning Contents Ontology (GELCO) was designed to define educational concepts and respective relations. A Syllabus Content Mindmap was developed within the Learning Scorecard, an academic performance management platform based on Business Intelligence and Gamification, taking advantage of the knowledge from GELCO. The ontology was successfully evaluated with competency questions, and students found the mindmap visualization useful and valuable for their academic performance monitoring
Computer-Driven Instructional Design with INTUITEL
INTUITEL is a research project that was co-financed by the European Commission with the aim to advance state-of-the-art e-learning systems via addition of guidance and feedback for learners. Through a combination of pedagogical knowledge, measured learning progress and a broad range of environmental and background data, INTUITEL systems will provide guidance towards an optimal learning pathway. This allows INTUITEL-enabled learning management systems to offer learners automated, personalised learning support so far only provided by human tutors INTUITEL is - in the first place - a design pattern for the creation of adaptive e-learning systems. It focuses on the reusability of existing learning material and especially the annotation with semantic meta data. INTUITEL introduces a novel approach that describes learning material as well as didactic and pedagogical meta knowledge by the use of ontologies. Learning recommendations are inferred from these ontologies during runtime. This way INTUITEL solves a common problem in the field of adaptive systems: it is not restricted to a certain field. Any content from any domain can be annotated. The INTUITEL research team also developed a prototype system. Both the theoretical foundations and how to implement your own INTUITEL system are discussed in this book
Predictive long-term asset maintenance strategy: development of a fuzzy logic condition-based control system
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceTechnology has accelerated the growth of the Facility Management industry and its roles are
broadening to encompass more responsibilities and skill sets. FM budgets and teams are becoming
larger and more impactful as new technological trends are incorporated into data-driven strategies.
This new scenario has motivated institutions such as the European Central Bank to initiate projects
aimed at optimising the use of data to improve the monitoring, control and preservation of the assets
that enable the continuity of the Bank's activities. Such projects make it possible to reduce costs, plan,
manage and allocate resources, reinforce the control, and efficiency of safety and operational systems.
To support the long-term maintenance strategy being developed by the Technical Facility
Management section of the ECB, this thesis proposes a model to calculate the Left wear margin of the
equipment. This is accomplished through the development of an algorithm based on a fuzzy logic
system that uses Python language and presents the system's structure, its reliability, feasibility,
potential, and limitations. For Facility Management, this project constitutes a cornerstone of the
ongoing digital transformation program
The use of accessibility metadata in e‑learning environments: a systematic literature review
E-learning environments constitute an essential element in education, as they help students to ensure their pass their courses and graduate on time. Although guidelines, techniques, and methods have been presented in some literature in recent years to contribute to the development of accessible e-learning environments that promote digital inclusion, their implementation is challenging. In this context, the use of accessibility metadata not only provides a way to enhance the description of adapted educational resources but also facilitates their search according to the needs and preferences of students, in particular those with disabilities. In this paper, a systematic review was conducted in order to provide the state of the art regarding the use of accessibility metadata in e-learning environments. A total of 746 documents were found during the period from 2012 to 2019, of which 31 were selected according to the inclusion and exclusion criteria relevant to our review. The findings revealed an intensive use of models and standards of accessibility in e-learning environments, however, using accessibility metadata remains underused. In fact, the evaluation of accessibility and adaptability through the use of its metadata was not found. The fndings obtained also helped to establish challenges and opportunities in this research feld as well as to provide an overview that could support those who generate educational resources to keep their interest in making them accessible.publishedVersio
E-Learning
E-learning enables students to pace their studies according to their needs, making learning accessible to (1) people who do not have enough free time for studying - they can program their lessons according to their available schedule; (2) those far from a school (geographical issues), or the ones unable to attend classes due to some physical or medical restriction. Therefore, cultural, geographical and physical obstructions can be removed, making it possible for students to select their path and time for the learning course. Students are then allowed to choose the main objectives they are suitable to fulfill. This book regards E-learning challenges, opening a way to understand and discuss questions related to long-distance and lifelong learning, E-learning for people with special needs and, lastly, presenting case study about the relationship between the quality of interaction and the quality of learning achieved in experiences of E-learning formation
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