Browsing by Author "Pesantez Cabrera, Paola Gabriela"

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A scoping review on the use, processing and fusion of geographic data in virtual assistants
(2021) Achig Balarezo, Rosario
Virtual assistants are a growing area of research in academia and industry, with an impact on people’s daily lives. Many disciplines in science are moving towards the incorporation of intelligent virtual assistants in multiple scenarios and application domains, and GIScience is not external to this trend since they may be connected to intelligent spatial decision support systems. This article presents a scoping review to indicate relevant literature pertinent to intelligent virtual assistants and their usage of geospatial information and technologies. In particular, the study was designed to find critical aspects of GIScience and how to contribute to the development of virtual assistants. Moreover, this work explores the most prominent research lines as well as relevant technologies/platforms to determine the main challenges and current limitations regarding the use and implementation of virtual assistants in geospatial-related fields. As a result, this review shows the current state of geospatial applications regarding the use of intelligent virtual assistants, as well as revealing gaps and limitations in the use of spatial methods, standards, and resources available in spatial data infrastructures to develop intelligent decision systems based on virtual assistants for a wide array of application domains.
Towards a methodoly for creating Internet of Things (IoT) applications based on microservices
(IEEE explore, 2020) Cabrera Alvarado, Edwin Fernando; Cardenas Cardenas, Paola Johana; Cedillo Orellana, Irene Priscila; Pesantez Cabrera, Paola Gabriela; Cedillo Orellana, Irene Priscila
The Internet of Things (IoT) represents the new industrial revolution, in which physical and virtual objects are interconnected. On the other hand, microservices architectures have broken the monolithic and centralized way to build software, and provide systems with high-quality characteristics (e.g., resilience, availability, modularity, and portability). Therefore, the idea of merging those technologies can constitute a powerful strategy to be applied in environments that demand the distribution and management of many IoT devices using high-quality software. In this context, several studies that integrate IoT with microservices solutions have been analyzed. However, most of these studies aim to satisfy the functional requirements related to software and hardware, without taking into account software engineering methodologies and good practices that allow the creation of software for IoT devices considering their distributed nature. Thus, this paper presents the first approach to an agile methodology that i) contemplates the main characteristics of the IoT and ii) guides the development of appropriate software solutions based on microservices architectures to manage IoT environments acknowledging the serious difficulties that microservices imply.
Towards learning analytics adoption: A mixed methods study of data-related practices and policies in Latin American universities
(2020) Hilliger, Isabel; Ortiz Rojas, Margarita Elizabeth; Pesantez Cabrera, Paola Gabriela; Scheihing, Eliana; Tsai, Yi Shan; Muñoz Merino, Pedro J.; Broos, Tom; Whitelock Wainwright, Alexander; Gasevic, Dragan; Pérez Sanagustín, Mar
In Latin American universities, Learning Analytics (LA) has been perceived as a promising opportunity to leverage data to meet the needs of a diverse student cohort. Although universities have been collecting educational data for years, the adoption of LA in this region is still limited due to the lack of expertise and policies for processing and using educational data. In order to get a better picture of how existing data‐related practices and policies might affect the incorporation of LA in Latin American institutions, we conducted a mixed methods study in four Latin American universities (two Chilean and two Ecuadorian). In this paper, the qualitative data were based on 37 interviews with managers and 16 focus groups with 51 teaching staff and 45 students; the quantitative data were collected through two surveys answered by 1884 students and 368 teachers, respectively. The findings reveal opportunities to incorporate LA services into existing data practices in the four case studies. However, the lack of reliable information systems and policies to regulate the use of data imposes challenges that need to be overcome for future LA adoption.