Browsing by Author "Orellana Cordero, Marcos"

Now showing 1 - 3 of 3

Data mining techniques for analysing data extracted from serious games: a systematic literature review
(Universidad de Toulous, Universidad de Limoges, Laboratorio de Investigación de Robótica, 2022) Acosta Urigüen, María Inés; Cedillo Orellana, Irene Priscila; Orellana Cordero, Marcos
Serious games are applications that pursue, on the one hand, the users' entertainment and, on the other hand, look to promote their learning, cognitive stimulation, among reaching other objectives. Moreover, data generated from those games (e.g., demographic information, gaming precision, user efficiency) provide insights helpful in improving certain aspects such as the attention and memory of the gamers. Therefore, applying data mining techniques over those data allows obtaining multiple patterns to improve the game interface, identify preferences, discover, predict, train, and stimulate the users' cognitive situation, among other aspects, to reach the games' objectives. Unfortunately, although several solutions have been addressed about this topic, no secondary studies have been found to condensate research that uses data mining to extract patterns from serious games. Thus, this paper presents a Systematic Literature Review (SLR) to extract such evidence from studies reported between 2001 and 2021. Besides, this SLR aims to answer research questions involving serious games solutions that train the cognitive functions of th
Finding insights between active aging Variables: towards a data mining approach
(Universidad de Toulous, Universidad de Limoges, Laboratorio de Investigación de Robótica, 2022) Orellana Cordero, Marcos; Lima, Juan Fernando; Bueno Pacheco, Alexandra; Prado Cabrera, Katerine Daniela; Acosta Urigüen, María Inés; Cedillo Orellana, Irene Priscila
Several proposals on active aging have been addressed within the psychological field, conceptualizing it satisfactorily as a perspective of aging. Those proposals generate indicators that assess the level of physical health, psychological wellbeing, adequate social adaptation. Physical, cognitive, and functional faculties, interpersonal relationships, and productive activities have been evaluated. Although several technological approaches have been proposed to promote active aging, they have not included a deep understanding of the results obtained from solution implementations. Then, this paper presents the first step towards an approach that uses variables proposed by active aging models (e.g., health, cognition, activity, affection, fitness aspects) to generate knowledge through patterns. These patterns are identified using data obtained through several instruments (i.e., psychological evaluations, health studies, and human experts' contributions). Thus, selecting those variables and evaluating them as future models is necessary. Domain experts perform this evaluation. The evaluation of this proposal has been completed with participants belonging to the health area through a case study. This evaluation generates input data for engineers to apply data mining techniques to reveal strategic knowledge. Finally, from the psychologist's point of view, the results showed that the contribution results are appropriate for achieving healthy aging indicators.
MASHEDU: intelligent mashups for education - towards a data mining approach
(14th International Conference on Computer Supported Education, 2022) Martínez, Pablo; Orellana Cordero, Marcos; Cedillo Orellana, Irene Priscila
Nowadays, technological tools greatly support the work of teaching-learning tasks. In this sense, there are various sources of information from which teachers and students rely on to complement their academic activities. Content is sought on the web, significantly updated and easy to understand, generally in the form of videos. As people progress in their learning, they face terms, concepts, and topics that they are not familiar with them. However, those topics are included in the video. In this context, a complex process is generated of alternating sections of the video with other sources of information that explain the related topics and contribute to the understanding of the topic discussed. In this regard, and considering the possibility of systematically consuming information from various sources, it is necessary to build a method and an application that orchestrates the contents of these sources in a convenient, fast and automatic way, according to the person's learning. This proposal contemplates the development of a Mashup. This mashup integrates different data sources in a single graphical interface. Also, it is considered the construction of a core software solution based on text mining techniques. This solution allows extracting the textual content from videos and identifying the terms that could support the knowledge of the topic. It would significantly contribute to the fact that related topics are presented unified in the same interface. At the same time, the learning experience is greatly improved, avoiding losing the common thread of the observed video. Therefore, this article presents a process of orchestrating various data sources in a Web Mashup application. It includes videos available on YouTube channels, with other sources (e.g., Wikipedia, Pinterest) that help understand the topic better, generating hypertext references based on the generation of terms through text mining techniques. A Mathematics Learning mashup has been built to show the proposal’s feasibility.