Examinando por Autor "Lozano-Osorio, Isaac"

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A Case Study on Learning visual programing with TutoApp for Composition of Tutorials: An approach for Learning by Teaching
(IEEE, 2022) Paredes-Velasco, Maximiliano; Lozano-Osorio, Isaac; Pérez-Marín, Diana; Santacruz-Valencia, Liliana Patricia
Teaching programming is a topic that has generated a high level of interest among researchers in recent decades. In particular, multiple approaches to teaching visual programming have been explored, from the use of tools such as Scratch, robots, unplugged programming or activities for the development of computational thinking. Despite the wide range of resources used, students generally tend to perform poorly academically and perceive learning visual programming as a complex and demotivating task. In this article, the TutoApp system is proposed together with a new methodology based on "Learning by Teaching”, where students create tutorials in their mobile devices to explain programming concepts to their peers. The hypothesis of this paper is that the use of this tool improves learning outcomes and the level of student satisfaction. An experiment with a pre-post- test design has been carried out with 57 university students in an introductory programming course, 30 belonging to a control group (did not use TutoApp) and 27 belonging to the experimental group (used TutoApp). The findings indicate that the creation of tutorials with TutoApp significantly improved students' academic performance over those who did not use it, specifically in learning the loops and conditional control structures. However, it was observed that anxiety increased in all students while learning visual programming. The results of this study open the door to the validation of the use of systems and methodologies for creating tutorials for teaching visual programming to university students.
A variable neighborhood search approach for the adaptive multi round influence maximization problem
(Springer, 2024-08-20) Lozano-Osorio, Isaac; Sánchez-Oro, Jesús; Duarte, Abraham
Social Networks have been in continuous growing during the last decades. The huge amount of information and applications has led to an increase in the interest of scientists and practitioners in the study of problems related to the influence in Social Networks. Some of the wide variety of real-world applications in this area are viral marketing, disease analysis, rumor detection, public opinion, among others. In this paper, the Adaptive Multi Round Influence Maximization problem is studied, in which the influence of a set of selected users (seed set) is propagated in multiple rounds independently, with the possibility of selecting different seed sets in each round. Therefore, seed sets can be adaptively selected based on the propagation results in the previous rounds. Since each node is activated with a certain probability, the total number of activated nodes must be calculated through an Influence Diffusion Model (IDM), which results in a rather computationally demanding method. In this research, the Independent Cascade Model is considered, which is one of the most extended IDMs, and also the one used in the best previous method. Practitioners highlight the relevance of designing an algorithm capable of efficiently solving the problem. In this research, the problem is addressed by considering the Variable Neighborhood Search methodology, proposing a novel constructive method that relies on independent probability based on events, and an intelligent local search method. Our best algorithm is compared with the state-of-the-art method, named AdaIMM, to analyze the performance of the proposal. The obtained results show the superiority of the proposal in both quality (influence spread) and computing time, obtaining the best solution in all the 40 instances considered requiring half of the computing time than the best previous approach (28 s vs. 53 s). Additionally, the best previous method presents an average deviation of 24.23%. These results are further confirmed by conducting non-parametric statistic tests.
An efficient and effective GRASP algorithm for the Budget Influence Maximization Problem
(Springer, 2023-09-21) Lozano-Osorio, Isaac; Sánchez-Oro, Jesús; Duarte, Abraham
Social networks are in continuous evolution, and its spreading has attracted the interest of both practitioners and the scientific community. In the last decades, several new interesting problems have aroused in the context of social networks, mainly due to an overabundance of information, usually named as infodemic. This problem emerges in several areas, such as viral marketing, disease prediction and prevention, and misinformation, among others. Then, it is interesting to identify the most influential users in a network to analyze the information transmitted, resulting in Social Influence Maximization (SIM) problems. In this research, the Budget Influence Maximization Problem (BIMP) is tackled. BIMP proposes a realistic scenario where the cost of selecting each node is different. This is modeled by having a budget that can be spent to select the users of a network, where each user has an associated cost. Since BIMP is a hard optimization problem, a metaheuristic algorithm based on Greedy Randomized Adaptive Search (GRASP) framework is proposed.
An Efficient Fixed Set Search for the Covering Location with Interconnected Facilities Problem
(Springer, 2023-02-23) Lozano-Osorio, Isaac; Sánchez-Oro, Jesús; Martínez-Gavara, Anna; López-Sánchez, Ana D.; Duarte, Abraham
This paper studies the Coverage Location Problem with Interconnected Facilities (CPIF). It belongs to the family of Facility Location Problems, but being more realistic to nowadays situations as surveillance, or natural disaster control. This problem aims at locating a set of interconnected facilities to minimize the number of demand points that are not covered by the selected facilities. Two facilities are considered as interconnected if the distance between them is smaller than or equal to a predefined distance, while a facility covers a demand point if the distance to it is smaller than a certain threshold. The wide variety of real-world applications that fit into this model makes them attractive for designing an algorithm able to solve the problem efficiently. To this end, a metaheuristic algorithm based on the Fixed Set Search framework is implemented. The proposed algorithm will be able to provide high-quality solutions in short computational times, being competitive with the state-of-the-art.
APRENDER ENSEÑANDO: CREACIÓN DE TUTORIALES CON TUTOAPP EN EL ÁMBITO DE FORMACIÓN PROFESIONAL
(2023-11) Ruiz-Omedilla, Sonia; Lozano-Osorio, Isaac; Paredes-Velasco, Maximiliano
El auge de las metodologías activas en educación y su importancia para atender a la diversidad presente en las aulas, se plantea como una oportunidad para realizar una intervención en la etapa de Formación Profesional introduciendo la metodología activa aprender enseñando, utilizando tecnología móvil a través de una aplicación Android, llamada TutoApp. Con esta aplicación los estudiantes crean tutoriales y breves cuestionarios relacionados con los contenidos a trabajar, de manera que este material facilite el aprendizaje tanto a sus creadores como al resto de compañeros. En la intervención descrita se valoran las emociones experimentadas por los estudiantes antes y después de la experiencia junto al rendimiento académico. La experiencia apunta a un mayor rendimiento en el aprendizaje y el dominio de los contenidos trabajados de los alumnos que usaron la herramienta de TutoApp respecto a los que no lo usaron. Sin embargo, no se encontró que el uso de la herramienta mejorase significativamente el estado emocional de los estudiantes.
BlueThinking, a programming tool for the development of executive functions at childhood
(Association for Computing Machinery, 2019-06-25) Lozano-Osorio, Isaac; Roldán-Álvarez, David; Bacelo, Adrián; Martín, Estefanía
Research shows that teaching computer programming to children help them develop important 21st century skills such as planning, problem solving, and flexibility of thinking. However, teaching these skills to young children is not an easy task as the existing tools in the market do not seem to be well adapted for them. The aim of this work is to present BlueThinking, an inclusive application to learn programming at early stages. A preliminary evaluation with 5 and 6 years old children was carried out to get the first impressions of the application and detect possible issues. The results show that the degree of children satisfaction with the application was high. Therefore, we believe BlueThinking could be easily used with young children to help them developing the aforementioned skills as well as to introduce them in a subtle way to the world of computer programming.
Dynamic Path Relinking for the Target Set Selection problem
(Elsevier, 2023) Lozano-Osorio, Isaac; Oliva-García, Andrea; Sánchez-Oro, Jesús
This research proposes the use of metaheuristics for solving the Target Set Selection (TSS) problem. This problem emerges in the context of influence maximization problems, in which the objective is to maximize the number of active users when spreading information throughout a social network. Among all the influence maximization variants, TSS introduces the concept of reward of each user, which is the benefit associated to its activation. Therefore, the problem tries to maximize the reward obtained among all active users by selecting an initial set of users. Each user has also associated an activation cost, and the total sum of activation costs of the initial set of selected users cannot exceed a certain budget. In particular, two Path Relinking approaches are proposed, comparing them with the best method found in the state of the art. Additionally, a more challenging set of instances are derived from real-life social networks, where the best previous method is not able to find a feasible solution. The experimental results show the efficiency and efficacy of the proposal, supported by non-parametric statistical tests.
Learning by Teaching: Creation of Tutorials in the Field of Vocational Training
(IEEE, 2024-04-29) Lozano-Osorio, Isaac; Ruiz-Olmedilla, Sonia; Pérez-Marín, Diana; Paredes-Velasco, Maximiliano
Contribution: A methodology based on the learning by teaching approach facilitated by a mobile learning tool for creating tutorials. A study of the impact this methodology has had on the emotional well-being of students and its correlation with academic performance has also been carried out. Background: Insufficient resources and the absence of targeted teaching methods for technical content in vocational training may impact academic outcomes and lead to student demotivation. Previous studies indicate that employing active group methodologies contributes to the improvement of educational quality and positively influences the emotional well-being of students. Intended Outcomes: Improved academic performance, motivation levels, and collaborative work among peers, particularly within vocational training cycles. Application Design: A quasi-experimental design with a pre–post assessment of knowledge and emotional states. The study was carried out with 131 vocational training students, with one group following a conventional master class methodology that used practical activities, and another group following the learning by teaching methodology, where students created explanatory tutorials for their peers using a mobile application. Findings: Students who followed the proposed methodology significantly improved learning results compared to those who followed the traditional methodology. This improvement was evident both at the end of the experience and in the final evaluation of the course. Moreover, results revealed that the emotions of enjoyment and pride at the end of the learning process positively correlated with the acquisition of knowledge and that this correlation was more pronounced within the cohort that followed the learning by teaching methodology.
Questionnaires to measure emotions and learning outcomes in a vocational training experience with Learning by Teaching
(Serie de Informes Técnicos DLSI1-URJC, 2024-04) Lozano-Osorio, Isaac; Ruiz-Olmedilla, Sonia; Perez-Marin, Diana; Paredes-Velasco, Maximiliano
The present work presents the questionnaires used in an experiment conducted with vocational training students, which measured the impact of the Learning by Teaching methodology on students' emotions and academic outcomes. First, the context in which the experiment was conducted is briefly described, followed by the display of the questionnaires used, in both English and Spanish versions.
What Characteristics Define a Good Solution in Social Influence Minimization Problems?
(Springer, 2024-06-18) Lozano-Osorio, Isaac; Sánchez-Oro, Jesús; Duarte, Abraham; Sörensen, Kenneth
The evolution of Social Networks has introduced significant challenges related to information overload. These challenges are covered in diverse areas, such as viral marketing or misinformation control. As social networks grow in complexity, the essential need to leverage data-driven insights becomes evident. The aim of the Social Influence Minimization Problem (IMP) is to identify and strategically block users to curtail information dissemination. Structural insights can be extracted through data-mining techniques to guide the design of efficient heuristics and the identification of influential users to be blocked. Considering good and bad quality solutions, a supervised learning approach is used to classify the extracted features, that allowed meaningful conclusions to be drawn regarding the features of these solutions. The IMP is addressed through the proposal of a robust heuristic method, based on the most relevant features, which is effective and efficient when compared with the state-of-the-art approaches.