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Permanent URI for this collectionhttps://repositorio.grial.eu/handle/123456789/34
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Item Showcasing sentiment classification and word prediction in the quantum natural processing area(CEUR-WS.org, 2023-12-05) Peral-García, D.; Cruz-Benito, J.; García-Peñalvo, F. J.The advent of quantum computers makes it possible to perform quantum computations in different areas like machine learning, finance, or chemistry. This paper showcases one of the emerging areas under quantum machine learning, quantum natural language processing. We present two quantum natural language processing tasks, sentiment classification and missing word prediction in a sentence. We show how these tasks can be achieved even in real quantum computers using the two main libraries in this subfield, DisCoPy, and lambeq.Item Desarrollo de herramientas y métodos automatizados para la simulación y mejora de procesos de computación cuántica basados en inteligencia artificial(Jornada de seguimiento de la actividad investigadora 2021-2022 USAL, 2022-05-24) Peral García, D.; Cruz-Benito, J.; García-Peñalvo, F. J.Con la premisa de alcanzar velocidades de cálculo exponencialmente supe-riores a la computación clásica, la computación cuántica está evolucionan-do rápidamente para convertirse en una de las áreas más populares de la in-geniería informática. Aunque, hasta hace poco, la mayor parte del trabajo en computación cuántica era puramente teórico o sus simulaciones eran im-plementadas en hardware clásico, la aparición de los denominados disposi-tivos Noisy Intermediate Scale Quantum (NISQ) ha permitido la ejecución de estos trabajos en computadores cuánticos. Recientemente, el área de apli-cación de los algoritmos cuánticos se ha ampliado de forma muy notable y ha proporcionado métodos prometedores en áreas como la química, la reso-lución de sistemas de ecuaciones lineales, las simulaciones físicas y el aprendizaje automático. Una de las áreas más emergentes ha sido el campo del aprendizaje automático, con los dispositivos y algoritmos cuánticos existentes, ya se han producido algunos avances como la creación de redes neuronales con capas cuánticasItem Enabling adaptability in web forms based on user characteristics detection through A/B testing and machine learning(IEEE, 2018-02-14) Cruz-Benito, J.; Vázquez-Ingelmo, A.; Sánchez-Prieto, J. C.; Therón, R.; García-Peñalvo, F. J.; Martín-González, M.This paper presents an original study with the aim of improving users' performance in completing large questionnaires through adaptability in web forms. Such adaptability is based on the application of machine-learning procedures and an A/B testing approach. To detect the user preferences, behavior, and the optimal version of the forms for all kinds of users, researchers built predictive models using machine-learning algorithms (trained with data from more than 3000 users who participated previously in the questionnaires), extracting the most relevant factors that describe the models, and clustering the users based on their similar characteristics and these factors. Based on these groups and their performance in the system, the researchers generated heuristic rules between the different versions of the web forms to guide users to the most adequate version (modifying the user interface and user experience) for them. To validate the approach and con rm the improvements, the authors tested these redirection rules on a group of more than 1000 users. The results with this cohort of users were better than those achieved without redirection rules at the initial stage. Besides these promising results, the paper proposes a future study that would enhance the process (or automate it) as well as push its application to other eldsItem AI-Driven Assessment of Students: Current Uses and Research Trends(Springer, 2020-07-19) Sánchez-Prieto, J. C.; Gamazo, A.; Cruz-Benito, J.; Therón, R.; García-Peñalvo, F. J.During the last decade, the use of AIs is being incorporated into the educational field whether to support the analysis of human behavior in teaching-learning contexts, as didactic resource combined with other technologies or as a tool for the assessment of the students. This proposal presents a Systematic Literature Review and mapping study on the use of AIs for the assessment of students that aims to provide a general overview of the state of the art and identify the current areas of research by answering 6 research questions related with the evolution of the field, and the geographic and thematic distribution of the studies. As a result of the selection process this study identified 20 papers focused on the research topic in the repositories SCOPUS and Web of Science from an initial amount of 129. The analysis of the papers allowed the identification of three main thematic categories: assessment of student behaviors, assessment of student sentiments and assessment of student achievement as well as several gaps in the literature and future research lines addressed in the discussion.Item Assessed by Machines: Development of a TAM-Based Tool to Measure AI-based Assessment Acceptance Among Students(2020-12-05) Sánchez-Prieto, J. C.; Cruz-Benito, J.; Therón, R.; García-Peñalvo, F. J.In recent years, the use of more and more technology in education has been a trend. The shift of traditional learning procedures into more online and tech-ish approaches has contributed to a context that can favor integrating Artificial-Intelligence-based or algorithm-based assessment of learning. Even more, with the current acceleration because of the COVID-19 pandemic, more and more learning processes are becoming online and are incorporating technologies related to automatize assessment or help instructors in the process. While we are in an initial stage of that integration, it is the moment to reflect on the students' perceptions of being assessed by a non-conscious software entity like a machine learning model or any other artificial intelligence application. As a result of the paper, we present a TAM-based model and a ready-to-use instrument based on five aspects concerning understanding technology adoption like the AI-based assessment on education. These aspects are perceived usefulness, perceived ease of use, attitude towards use, behavioral intention, and actual use. The paper's outcomes can be relevant to the research community since there is a lack of this kind of proposal in the literature.Item How to Measure Teachers’ Acceptance of AI-driven Assessment in eLearning: A TAM-based Proposal(ACM, 2019-10-16) Sánchez-Prieto, J. C.; Cruz-Benito, J.; Therón, R.; García-Peñalvo, F. J.The use of AI is becoming a growing reality the educational field. One of the activities in which it is beginning to be implemented is the assessment of student achievement. This way, we can find in the literature an increasing number of investigations focused on the possibilities offered by the adoption of AI-driven assessment. However, the use of AI is also a source of concern that raises suspicions in some sectors of our society. In this context, knowing the position of the teachers towards this topic is critical to guarantee the successful development of the field. This paper intends to fill a research gap in the literature by offering a technology adoption model based on TAM to study the factors that condition the use of AI-driven assessment among teachers. To present this model we offer a background on the use of AI in education and the technology acceptance among teachers, as well as the definition of the eight constructs and the relational hypotheses included. Finally, the possibilities of the model and future lines of research are discussed.Item Analyzing the software architectures supporting HCI/HMI processes through a systematic review of the literature(2019-03-22) Cruz-Benito, J.; García-Peñalvo, F. J.; Therón, R.Many researchers have dealt with Human-Computer Interaction or Human-Machine Interaction by building or designing software architectures that facilitate the users’ interaction or recognize users’ inputs to the generate proper responses. Many studies include these approaches in different research areas: from research in healthcare to mobile environments, robotics, etc. Interaction is seen as a critical concept, and the work for its improvement is a crucial factor for many platforms, systems, and business domains. The goal of this manuscript is to present a systematic review of the literature to identify, analyze and classify the published approaches to support or enhance Human-Computer Interaction or Human-Machine Interaction from the perspective of software architectures. The method followed is the systematic review following the guidelines related to Systematic Literature Reviews methods such as the one proposed by Kitchenham and other authors in the field of software engineering. As results, this study identified 39 papers that included software architectures to improve or analyze Human-Computer Interaction or Human-Machine Interaction. Three main approaches were found on software architectures: layered architectures, modular architectures, and architectures based on software agents, but they lacked standardization and were mainly ad-hoc solutions. The primary interfaces covered were those related to Graphical User Interfaces (GUIs) and multimodal/natural ones. The primary application domain detected were in multimodal systems. The main purpose of most of the papers was to support multimodal interaction. Some conclusions achieved are that the generic solutions to support or analyze HCI/HMI processes are still rare in the literature. Despite many works dealing with this topic and its issues and challenges, it is necessary to keep on improving the research in this area through the application of standard techniques and solutions, exploring new ways of analyzing and interpreting interaction, escaping from ad-hoc solutions or evaluating the solutions proposed.Item Scaffolding the OEEU's Data-Driven Ecosystem to Analyze the Employability of Spanish Graduates(IGI Global, 2018-01-01) Vázquez-Ingelmo, A.; Cruz-Benito, J.; García-Peñalvo, F. J.; Martín-González, M.This chapter outlines the technological evolution experimented by the Observatory for University Employability and Employment’s information system to become a data-driven technological ecosystem. This observatory collects data from more than 50 Spanish universities and their graduate students (bachelor’s degree, master’s degree) with the goal of measuring the factors that lead to students’ employability and employment. The goals pursued by the observatory need a strong technological support to gather, process, and disseminate the related data. The system that supports these tasks has evolved from a standard (traditional) information system to a data-driven ecosystem, which provides remarkable benefits covering the observatory’s requirements. The benefits, the foundations, and the way the data-driven ecosystem is built will be described throughout the chapter, as well as how the information obtained is exploited in order to provide insights about the employment and employability variables.Item Proposing a machine learning approach to analyze and predict employment and its factors(2018-08-28) García-Peñalvo, F. J.; Cruz-Benito, J.; Martín-González, M.; Vázquez-Ingelmo, A.; Sánchez-Prieto, J. C.; TherónThis paper presents an original study with the aim of propose and test a machine learning approach to research about employability and employment. To understand how the graduates get employed, researchers propose to build predictive models using machine learning algorithms, extracting after that the most relevant factors that describe the model and employing further analysis techniques like clustering to get deeper insights. To test the proposal, is presented a case study that involves data from the Spanish Observatory for Employability and Employment (OEEU). Using data from this project (information about 3000 students), has been built predictive models that define how these students get a job after finalizing their degrees. The results obtained in this case study are very promising, and encourage authors to refine the process and validate it in further research.Item Herramienta para la validación de elementos de mejora UX/Engagement para los cuestionarios de recogida de información de egresados en el contexto del Observatorio de Empleabilidad y Empleo Universitarios (OEEU)(Grupo GRIAL, 2017-02-19) Cruz-Benito, J.; Therón, R.; García-Peñalvo, F. J.; Martín-González, M.La recogida de información mediante cuestionarios y entrevistas es uno de los métodos más conocidos y utilizados en la actualidad, tanto en el medio físico como en el digital. Es común que cualquier web que se visite cuente con algún formulario para la entrada de información, ya sea como punto de contacto, como parte del acceso a partes privadas del sistema, como parte de un proceso de pago, etc. Los formularios están tan integrados en la interacción del usuario dentro de una web, que puntualmente se relativiza su importancia y se presupone que el usuario va a completarlo por el mero hecho de utilizarlos habitualmente