HERRERA MARÍN, MAURICIO RENÉ
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HERRERA MARÍN, MAURICIO RENÉ
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Email
mherrera@ingenieros.udd.cl
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Scopus Author ID
55757469300

Research Output

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Now showing 1 - 10 of 17
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Facilitando el aprendizaje de trigonometría a través de una interfaz tangible

2020 , ZAMORANO URRUTIA, FRANCISCO JAVIER , CORTES LOYOLA, CATALINA , HERRERA MARÍN, MAURICIO RENÉ

En educación matemática, estudios evidencian dificultades y desafíos en la enseñanza-aprendizaje de trigonometría en educación secundaria y superior, donde no se estimula al estudiante a obtener un entendimiento conceptual profundo de los conceptos. Considerando su relevancia para diversas disciplinas, es necesario implementar nuevos acercamientos a su enseñanza, donde se privilegie un rol activo del estudiante en su propio aprendizaje. Diversos estudios demuestran que la incorporación de tecnologías digitales influyen positivamente aprendizaje de los alumnos, sin embargo, la mayoría de las tecnologías existentes responden al paradigma de interacción tradicional con un computador, donde no se considera el uso del cuerpo y de los múltiples sentidos. Las Interfaces Tangibles (TUI) en cambio, pueden albergar interacciones corporales, brindando directo tributo a la teoría de la Cognición Corporal. Sin embargo existe un vacío en la aplicación de TUI para la educación de trigonometría. Esta investigación consistió en diseñar y validar una interfaz tangible para la enseñanza-aprendizaje de trigonometría inicial. La interfaz alberga una experiencia de aprendizaje que privilegia la exploración, el uso de la intuición, y fomenta el aprendizaje colaborativo. Se realizó un Pre-Test diagnóstico con 119 estudiantes para determinar conocimientos previos dando un rendimiento promedio de 29.1%. Luego de dos intervenciones con la interfaz propuesta, los resultados de un Post-Test muestran un incremento del rendimiento en un 37.1%, lo que valida la efectividad pedagógica de la interfaz y experiencia pedagógica para el aprendizaje de conceptos básicos de trigonometría.

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Discovering the Spread Patterns of SARS-CoV-2 in Metropolitan Areas

2024 , HERRERA MARÍN, MAURICIO RENÉ , Vergara-Perucich, Francisco , Aguirre-Nunez, Carlos , GODOY FAUNDEZ, ALEX ORIEL

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Exploring the Roles of Local Mobility Patterns, Socioeconomic Conditions, and Lockdown Policies in Shaping the Patterns of COVID-19 Spread

2021 , HERRERA MARÍN, MAURICIO RENÉ , GODOY FAUNDEZ, ALEX ORIEL

The COVID-19 crisis has shown that we can only prevent the risk of mass contagion through timely, large-scale, coordinated, and decisive actions. This pandemic has also highlighted the critical importance of generating rigorous evidence for decision-making, and actionable insights from data, considering further the intricate web of causes and drivers behind observed patterns of contagion diffusion. Using mobility, socioeconomic, and epidemiological data recorded throughout the pandemic development in the Santiago Metropolitan Region, we seek to understand the observed patterns of contagion. We characterize human mobility patterns during the pandemic through different mobility indices and correlate such patterns with the observed contagion diffusion, providing data-driven models for insights, analysis, and inferences. Through these models, we examine some effects of the late application of mobility restrictions in high-income urban regions that were affected by high contagion rates at the beginning of the pandemic. Using augmented synthesis control methods, we study the consequences of the early lifting of mobility restrictions in low-income sectors connected by public transport to high-risk and high-income communes. The Santiago Metropolitan Region is one of the largest Latin American metropolises with features that are common to large cities. Therefore, it can be used as a relevant case study to unravel complex patterns of the spread of COVID-19.

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Understanding water disputes in Chile with text and data mining tools

2019 , HERRERA MARÍN, MAURICIO RENÉ , CANDIA VALLEJOS, CRISTIAN ESTEBAN , Diego Rivera Salazar , Douglas Aitken , Daniel Brieba , BOETTIGER PHILIPPS, CAMILA , Guillermo Donoso , GODOY FAUNDEZ, ALEX ORIEL

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Inside the Black Box: Uncovering Dynamics and Characteristics of the Chilean Central Government Bureaucracy with a Novel Dataset

2024 , Daniel Brieba , HERRERA MARÍN, MAURICIO RENÉ , Marcelo Riffo , GARRIDO MELLA, DANILO GUILLERMO FELIPE

This article examines bureaucracies using a novel dataset of Chilean central government employees from 2006 to 2020. Unlike perception-based sources, this dataset provides objective, disaggregated, and longitudinal insights into bureaucrats’ characteristics and careers. The authors validate it against official employment statistics and conduct an exploratory and descriptive analysis, presenting six descriptive findings about the Chilean bureaucracy that cannot be discovered using available aggregate data. The analysis reveals significant degrees of personnel stability and professionalization in the civil service, but with considerable rigidity in careers and substantial interagency heterogeneity in turnover, wages, and exposure to political cycles. These findings suggest that the Chilean national bureaucracy is mostly well developed along Weberian lines, though not uniformly so. These measurements also serve as a benchmark for comparing other Latin American bureaucracies in the future.

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Design of a multisensory interface that explores human-technology interaction to facilitate the learning of basic trigonometry concepts

2024 , ZAMORANO URRUTIA, FRANCISCO JAVIER , CORTES LOYOLA, CATALINA , HERRERA MARÍN, MAURICIO RENÉ

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New Highly Portable Simulator (SECMA) Based on Virtual Reality for Teaching Essential Skills in Minimally Invasive Surgeries

2023 , GUZMAN MONTOTO, JOSE IGNACIO , HERRERA MARÍN, MAURICIO RENÉ , RODRÍGUEZ BELTRÁN, CAMILO IGNACIO

This study presents a new minimal access surgery training system, SECMA, and its constructive validation to determine its usefulness for training basic laparoscopic skills. SECMA is an affordable, highly portable, mobile virtual reality training tool for laparoscopic techniques that integrates the Oculus Quest with a mechanical interface for surgeon simulation of forceps using the hand controllers of these devices. It allows the execution of structured activities (supported by virtual scenarios simulating operating rooms developed in Unity), performance evaluation, and real-time data capture. Two experiments were carried out: 1) coordination; and 2) capture and transport, with a total of 21 individuals divided into two groups: a novice group (inexperienced) of 10 participants and an expert group (>100 endoscopic procedures) of 11 participants. Total task time score, right-hand speed, path length, and other metrics from several consecutive runs on the simulator were compared between experts and novices. Data automatically recorded by SECMA during the experiments were analyzed using hypothesis tests, linear regressions, analysis of variance, principal component analysis, and machine learning-supervised classifiers. In the experiments, the experts scored significantly better than the novices in all the parameters used. The tasks evaluated discriminated between the skills of experienced and novice surgeons, giving the first indication of construct validity for SECMA.

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Interdisciplinary design process of a multi-sensory interface to facilitate learning of basic concepts of trigonometry

2019 , CORTES LOYOLA, CATALINA , ZAMORANO URRUTIA, FRANCISCO JAVIER , HERRERA MARÍN, MAURICIO RENÉ

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Comment on “An algorithm for moment-matching scenario generation with application to financial portfolio optimization”

2018 , Juan Pablo Contreras , BOSCH PÉREZ, PAUL JESÚS , HERRERA MARÍN, MAURICIO RENÉ

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Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies

2018 , BOSCH PÉREZ, PAUL JESÚS , HERRERA MARÍN, MAURICIO RENÉ , Julio López , Sebastián Maldonado

We have developed a new methodology for examining and extracting patterns from brain electric activity by using data mining and machine learning techniques. Data was collected from experiments focused on the study of cognitive processes that might evoke different specific strategies in the resolution of math problems. A binary classification problem was constructed using correlations and phase synchronization between different electroencephalographic channels as characteristics and, as labels or classes, the math performances of individuals participating in specially designed experiments. The proposed methodology is based on using well-established procedures of feature selection, which were used to determine a suitable brain functional network size related to math problem solving strategies and also to discover the most relevant links in this network without including noisy connections or excluding significant connections.

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