Uso de técnicas de agrupamiento en la clasificación de estilos de aprendizaje

Gudiño-Peñaloza, Fernando; González-Mendoza, Miguel; Mora-Vargas, Jaime

doi:10.13053/rcs-95-1-11

Cited by 5 publications

(4 citation statements)

References 7 publications

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“…In this sense the visualization of the multivariate data plays an important role in the fulfillment of the objectives [5]. Some studies in the educational area use graphical visualization techniques such as radar charts to make comparisons that are easy to interpret [6,7]; In other studies, on university academic performance and the aspects that affect it, data analysis techniques have been applied [8,9] or techniques of evaluation of results obtained [10].…”

Section: Multivariate Analysismentioning

confidence: 99%

Representation of Learning Strategies through Visual Techniques of Multivariate Analysis in University Students

Garrido¹,

Mateos²,

Aguilar³

et al. 2018

RCS

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This research aims to identify the learning strategies employed by university students; and represent them through graphic techniques of multivariate analysis. The sample consisted of 30 students from the Multidisciplinary Academic Division of the Rivers; of the degrees in Administration and Administrative Computing of the generational cohorts 2010, 2011 and 2012. The instrument used is the Inventory of Strategies of Learning and Motivational Orientation (EDAOM), this instrument consists of a self-assessment that the student makes on the learning strategies that employs. For the implementation of the visual techniques was used the Language R, with these techniques were represented individually to the students with their respective learning strategies. The results show the interaction of the students with the learning strategies and the academic performance, visualization that the students of the Degree in Administrative Computing obtain the lowest values in the strategies of performance and academic performance.

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Section: Multivariate Analysismentioning

confidence: 99%

Representation of Learning Strategies through Visual Techniques of Multivariate Analysis in University Students

Garrido¹,

Mateos²,

Aguilar³

et al. 2018

RCS

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“…There are some works where graphic representations have been developed to know the behavior of the data in educational areas at the license level, such as radar graphs where it is possible to visualize the comparison of the data in a fast way, facilitating the interpretation of the data through colored lines that form polygons [5,6]. Likewise, research has been found related to academic performance and the elements that influence university students where data analysis techniques have been applied [7,8] or techniques for evaluating the results obtained [9].…”

Section: Introductionmentioning

confidence: 99%

Multivariate Analysis of University Student Engagement through Visualization Techniques

Mateos¹,

Garrido²,

Aguilar³

et al. 2018

RCS

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The objective of this work is to apply visualization techniques for the representation of multivariate analysis results. The techniques were used to publicize the results of student engagement at universities of careers in technology at a university in the south of México. To measure student engagement, the UWES-S instrument was used, composed of vigor, dedication and absorption dimensions. The graphs presented in this paper are: Graphics Matrices, GGE Biplot and Chernoff faces, which were developed with the R language. It concludes on the utility that visualization techniques have in the multivariate analysis, given that in this it is studio was able to identify how students interact (genotypes) with the environment (variables of student engagement), identifying that the majority presents a stable level of student engagement. With the Chernoff faces, it was possible to visualize through the facial features in detail the presence of student engagement as a result medium level.

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“…Research has been found where different techniques of data analysis have been used to obtain information about the academic performance of university students, such as knowing the factors that cause students to desertion through the use of decision trees [7], the use of techniques of grouping to know the styles of learning [8], among others. Some research involves the personal factor with academic performance, data have been obtained from formal surveys, which have been applied data analysis techniques to discover the relationships between the variables involved, such as rules of association techniques [9], Classification techniques such as trees [10]. There are currently a large variety of studies based on the use of principal components where observations are presented on the axes formed by the first two main components [11].…”

Section: Introductionmentioning

confidence: 99%

A Comparison Represented in the Form of Radar of University Student Engagement in Degrees in Technologies

Mateos¹,

Aguilar²,

Ortiz³

et al. 2016

RCS

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This research work aims to raise awareness of the results of the student engagement in university students of three careers in technologies, of a university in the south of Mexico, through the development of graphics that allows displaying in an adequate manner the cases under study, facilitating the interpretation of the same. To measure the student engagement was used the instrument Utrecht Work Engagement Scale for Students (UWES-S), which is composed of the dimensions, vigor, dedication and absorption. Graphs presented in this work are a graphics array correlation, a graphical representation of radial and a chart GGE bi plot. It was observed that the student engagement is in general, for this population sample, average level, identifying as predominant the dimension of dedication.

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Uso de técnicas de agrupamiento en la clasificación de estilos de aprendizaje

Cited by 5 publications

References 7 publications

Representation of Learning Strategies through Visual Techniques of Multivariate Analysis in University Students

Representation of Learning Strategies through Visual Techniques of Multivariate Analysis in University Students

Multivariate Analysis of University Student Engagement through Visualization Techniques

A Comparison Represented in the Form of Radar of University Student Engagement in Degrees in Technologies

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