Person:
Zúñiga Prieto, Miguel Ángel

Birth Date

1972-12-15

ORCID

0000-0001-9369-1813

Scopus Author ID

56524481200

Afiliación

Universidad de Cuenca, Cuenca, Ecuador
Universidad de Cuenca, Departamento de Ciencias de la Computación, Cuenca, Ecuador
Universitat Politécnica de Valencia, Valencia, España

País

Ecuador

Organizational Units

Organizational Unit

Facultad de Ingeniería

La Facultad de Ingeniería, a inicios de los años 60, mediante resolución del Honorable Consejo Universitario, se formalizó la Facultad de Ingeniería de la Universidad de Cuenca, conformada por las escuelas de Ingeniería Civil y Topografía. Esta nueva estructura permitió una mayor especialización y fortalecimiento en áreas clave para el desarrollo regional. Cuenta con programas académicos reconocidos internacionalmente, que promueven y lideran actividades de investigación. Aplica un modelo educativo centrado en el estudiante y con procesos de mejora continua. Establece como prioridad una educación integra, la formación humanística es parte del programa de estudios que complementa a la sólida preparación científico-técnica. Las actividades culturales pertenecen a un programa permanente y activo al interior de nuestras dependencias, a la par de proyectos que desde el alumnado y bajo la supervisión de docentes cumplen con servicios de apoyo a nivel local y regional; promoviendo así una vinculación estrecha con la comunidad.

Job Title

Profesor (T)

Last Name

Zúñiga Prieto

First Name

Miguel Ángel

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Search Results

Now showing 1 - 10 of 18

Automation of the generation of accessible digital educational material for students with visual disabilities
(Springer, 2020) Cabrera Medina, Boris Fabricio; Zúñiga Prieto, Miguel Ángel
Online learning has grown in the last years, where educational institutions are offering courses or study programs in different knowledge areas. Online learning allows students to participate actively in cooperative learning activities, interacting without the preconceived notions of disability that other participants could have, which affects the relationship. However, these advantages have often not become a reality for most people with disabilities, especially in the educational context. For instance, courses’ web pages are not accessible for people with visual disabilities, which makes the experience of taking a course frustrating and tedious. This article proposes a Model-Driven Development approach for supporting the design and generation of accessible educational material, for example, accessible Learning Objects (LO). This approach provides a software infrastructure that includes: (i) A Domain-Specific Language and its corresponding graphic editor that supports accessible LO’s design. Helping teachers during the instructional design and allowing them to describe accessibility requirements for students with visual disabilities. (ii) A LO’s generation engine that takes as input design artifacts and generates the source code that implements accessible LO. Abstracting teachers from technological aspects (e.g., programming language instructions) necessary to construct LO with accessibility features. The applicability of this approach is illustrated by using the DSL and the generation engine to design and automatically implement an accessible LO according to the accessibility profile specified during design. Finally, the generated LO was published in the Learning Management System Moodle. © 2020, Springer Nature Switzerland AG.
An overview of the LALA project
(CEUR-WS, 2020) Muñoz Merino, Paul; Delgado Kloos, Carlos; Tsai, Yi Shan; Gasevic, Dragan; Verbert, Katrien; Pérez Sanagustín, María del Mar; Hilliger, Isabel; Zúñiga Prieto, Miguel Ángel; Ortiz Rojas, Margarita; Scheihing, Eliana
The LALA project (“Building Capacity to Use Learning Analytics to Improve Higher Education in Latin America”) is a project that aims at building capacity about the use of data in education for improving education in Latin America. This article presents a general overview of the LALA project including the LALA framework (as a set of guidelines, recommendations and patterns for enabling adoption of learning analytics), the adaptation of learning analytics tools (mainly three different tools used in Europe) and the pilots with learning analytics experiences. The results of this project could serve as an example for other institutions in the Latin American region or other under-represented regions to adopt Learning Analytics as part of their processes.
Temporal analysis of 911 emergency calls through time series modeling
(Springer, 2020) Robles Granda, Pablo Dario; Tello Guerrero, Marco Andres; Solano Quinde, Lizandro Damián; Zúñiga Prieto, Miguel Ángel
We present two techniques for modeling time series of emergency events using data from 911 emergency calls in the city of Cuenca-Ecuador. We study state-of-the-art methods for time series analysis and assess the benefits and drawbacks of each one of them. In this paper, we develop an emergency model using a large dataset corresponding to the period January 1st 2015 through December 31st 2016 and test a Gaussian Process and an ARIMA model for temporal prediction purposes. We assess the performance of our approaches experimentally, comparing the standard residual error (SRE) and the execution time of both models. In addition, we include climate and holidays data as explanatory variables of the regressions aiming to improve the prediction. The results show that ARIMA model is the most suitable one for forecasting emergency events even without the support of additional variables.
Coordinating learning analytics policymaking and implementation at scale
(2020) Pesántez Cabrera, Paola Gabriela; Solano Quinde, Lizandro Damián; Sigüenza Guzmán, Lorena Catalina; Zúñiga Prieto, Miguel Ángel
Many Latin‐American institutions recognise the potential of learning analytics (LA). However, the number of actual LA implementations at scale remains limited, notwithstanding considerable effort made to formulate guidelines and frameworks to support the LA policy development. Guidance on how to coordinate the interaction between the LA policymaking and implementation is mostly missing, leaving a difficult challenge up to practitioners. In this study we propose a coordination model to support future LA initiatives at scale. We explore the problem by comparing two cases in Belgium and Ecuador. Following up we use the LA implementation timeline as a driver for planning the interaction between the policymaking and implementation. We continue by testing an application of the model with LA experts predominantly from Latin‐American institutions, asking them to map low‐level items of the SHEILA policy framework to four implementation phases. The results of this mapping support that LA policy building can be spread over time, that it can coincide with LA implementation at scale, and that both efforts can be coordinated. It is hoped that this study will provide additional guidance for future Latin‐American and other LA initiatives.
Proposal of an assistant for the automation of the design and creation process of learning objects
(Institute of Electrical and Electronics Engineers Inc., 2018) Bermeo Conto, Jorge; Maldonado Mahauad, Jorge Javier; Cabrera, Boris; Zúñiga Prieto, Miguel Ángel
Learning Objects (LOs) are digital educational materials that enable the teaching and learning process to be mediated. Howev-er, their design and creation often exceeds the possibilities that a teacher has for their production. Teachers are experienced users in the educational field and have little or no experience in pro-gramming tools, so it is expected that the production of an OA can be scalable. The aim of this paper is to present an intermedi-Ate software solution that supports the systematic application and documentation of the phases proposed in the DICREVOA meth-odology for the design, analysis and implementation of OA. For this a case study with the proposed graphic editors is presented. As a result, this wizard for the automation of the design and creation process of OA will allow teachers to exploit and improve the productivity, reliability, maintainability and portability of this type of educational resource from their experience in the domain of the educational context. © 2018 IEEE.
Multi-GPU implementation of the horizontal diffusion method of the weather research and forecast model
(ASSOCIATION FOR COMPUTING MACHINERY INC, 2016-03-12) Solano Quinde, Lizandro Damián; Gualan Saavedra, Ronald Marcelo; Zúñiga Prieto, Miguel Ángel
The Weather Research and Forecasting (WRF), a next generation mesoscale numerical weather prediction system, has a considerable amount of work regarding GPU acceleration. However, the amount of works exploiting multi-GPU sys- tems is limited. This work constitutes an effort on using GPU computing over the WRF model and is focused on a computationally intensive portion of the WRF: the Horizontal Diffusion method. Particularly, this work presents the enhancements that enable a single-GPU based implementation to exploit the parallelism of multi-GPU systems. The performance of the multi-GPU and single-GPU based implementations are compared on a computational domain of 433x308 horizontal grid points with 35 vertical levels, and the resulting speedup of the kernel is 3.5x relative to one GPU. The experiments were carried out on a multi-core computer with two NVIDIA Tesla K40m GPUs.
Analyzing students’ behavior in a MOOC course: a process-oriented approach
(Springer Verlag, 2020) Bernal, Franklin; Maldonado Mahauad, Jorge Javier; Zúñiga Prieto, Miguel Ángel; Veintimilla Reyes, Jaime Eduardo; Mejía Pesántez, Piedad Magali; Villalba Condori, Klinge
Massive Open Online Courses (MOOCs), are one of the most disruptive trends along the last 12 years. This is evidenced by the number of students enrolled since their emergence with over 101 million people taking one of the more than 11,400 MOOCs available. However, the approval rate of students in these types of courses is only about 5%. This has led to a great deal of interest among researchers in studying students’ behavior in these types of courses. The aim of this article is to explore the behavior of students in a MOOC. Specifically, to study students learning sequences and extract their behavioral patterns in the different study sessions. To reach the goal, using process mining techniques, process models of N = 1,550 students enrolled in a MOOC in Coursera were obtained. As a result, two groups of students were classified according to their study sessions, where differences were found both in the students’ interactions with the MOOC resources and in the way the lessons were approached on a weekly basis. In addition, students who passed the course repeated the assessments several times until they passed, without returning to review a video-lecture in advance. The results of this work contribute to extend the knowledge about students’ behavior in online environments.
Applying the LALA framework for the adoption of a learning analytics tool in Latin America: two case studies in Ecuador
(CEUR-WS, 2020) Zúñiga Prieto, Miguel Ángel; Ortiz, Margarita; Ulloa Amaya, Marlon Enrique; Jimenez, Alberto
Worldwide, Higher Education Institutions (HEIs) are recognizing the benefits of using Learning Analytics (LA). Thus, there is more research on the adoption of LA tools as well as works presenting different frameworks for implementing LA in HEIs, mostly in Europe. In the case of Latin America, the LALA Framework was defined, containing detailed guidelines for LA adoption that take into account policies, ethics, and development of tools in the Latin American context. However, this framework has not been applied in real scenarios. Thus, this paper presents the results obtained with the application of the LALA Framework for the development and adoption of LA tools in two Latin-American HEIs with different LA contexts. As a result, this work not only shows the feasibility of this framework to guide the adoption of LA tools but also shows that different LA context requires the execution of activities applying different approaches. This work proposes changes to improve the LALA Framework. Changes mainly related to the inclusion of adoption alternatives that allow practitioners to select the one suitable for their specific institutional context.
A systematic mapping study of specification languages in cloud services development
(Springer, 2019) Bermeo Conto, Jorge Luis; Zúñiga Prieto, Miguel Ángel; Solano Quinde, Lizandro Damián
Specification languages offer abstractions and notations that facilitate the systematic and analytical reasoning about important aspects in a specific domain problematic. In a software engineering process domain, the usage of specification languages improve the quality and delivery time of the artefacts generated during the execution of the process activities. Cloud applications, or cloud services, are service-oriented applications whose consumption is constantly growing; however, their development require support for new roles and activities. In this work we are interested in knowing how specification languages are being used by researchers and practitioners to support the development of cloud services. This work presents a systematic mapping that provides guidance to determine the current state and to characterize the specification languages that support the service life cycle activities in a cloud services development domain.
For learners, with learners: Identifying indicators for an academic advising dashboard for students
(Springer Science and Business Media Deutschland GmbH, 2020) Hilliger, Isabel; De Laet, Tinne; Henríquez, Valeria; Ortiz Rojas, Margarita; Zúñiga Prieto, Miguel Ángel; Baier, Jorge; Pérez Sanagustin, Mar
Learning Analytics (LA) dashboards aggregate indicators about student performance and demographics to support academic advising. The majority of existing dashboards are targeted at advisors and professors, but not much attention has been put into students’ need for information for their own academic decision-making. In this study, we identify relevant indicators from a student perspective using a mixed methods approach. Qualitative data was obtained from an open-ended online questionnaire answered by 31 student representatives, and quantitative data was collected from a closed-ended online questionnaire answered by 652 students from different cohorts. Findings point out relevant indicators to help students choose what courses to take in an upcoming academic period. Since this study is part of a large research project that has motivated the adoption of academic advising dashboards in different Latin American universities, these findings were also contrasted with indicators of these advising dashboards, informing future developments targeting students.