Student activity and profile datasets from an online video-based collaborative learning experience

Esfefanía Martín, Manuel Gértrudix, Jaime Urquiza, Pablo A. Haya,

British Journal of Educational Technology. Article first published online: 20 JUL 2015 (2015) DOI: 10.1111/bjet.12318 [download] (JCR, IF 2014: 1.394, Q1)

This paper describes two datasets extracted from a video-based educational experience using a social and collaborative platform. The length of the trial was 3 months. It involved 111 students from two different courses. Twenty-nine came from Computer Engineering (CE) course and 82 from Media and Communication (M&C) course. They were organised into nine interdisciplinary groups. Each group included three or four CE students and eight or nine M&C students. An additional group filmed the making of. This group has only M&C students. Four teachers supervised the trial. The total number of meaningful events was 2984.

Anonymized version of the activity dataset and profile dataset are publicly available.

Fair Trade metaphor as a Control Privacy Method for Pervasive Environments: Concepts and Evaluation

Abraham Esquivel, Pablo A. Haya and Xavier Alamán. Sensor 15(6), 14207-14229 (2015) doi:10.3390/s150614207 [download] (JCR, IF 2014: 2.093, Q1)

This paper presents a proof of concept from which the metaphor of “fair trade” is validated as an alternative to manage the private information of users. Our privacy solution deals with user’s privacy as a tradable good for obtaining environmental services. Thus, users gain access to more valuable services as they share more personal information. This strategy, combined with optimistic access control and transaction registry mechanisms, enhances users’ confidence in the system while encouraging them to share their information, with the consequent benefit for the community. The study results are promising considering the user responses regarding the usefulness, ease of use, information classification and perception of control with the mechanisms proposed by the metaphor.

Analysing content and patterns of interaction for improving the learning design of networked learning environments

Pablo A. Haya, Oliver Daems, Nils Malzahn, Jorge Castellanos and Heinz Ulrich Hoppe

British Journal of Educational Technology. Article first published online: 3 MAR 2015 (2015) DOI: 10.1111/bjet.12264 [download] (JCR, IF 2014: 1.394, Q1)

Learning Analytics constitutes a key tool for supporting Learning Design and teacher-led inquiry into student learning. In this paper, we demonstrate how a Social Learning Analytics toolkit can combine social network analysis and content analysis for supporting a global and formal teacher inquiry. This toolkit not only supports teachers in improving the organisation of the learning process but also generates important input to improve the students’ reflection on their own learning. Our examples show how combinations of different levels of analysis can provide deep insight in the learning process. We report a case study that exemplifies the main features of our approach and the kind of outcomes that can be obtained. Commenting and rating processes on videos are analysed based on user traces from a social learning platform. Finally, we point out implications on the learning design for networked learning environments in general.

Discussion network

Big Data para la gestión de recursos humanos

David Aguado, Pablo A. Haya, Alvaro Barbero

Observatorio de Recursos Humanos 98 (2015) [download]

Big Data para la gestión de recursos humanos

Los gestores de RR.HH. han declarado explícitamente su interés por el Big Data. A pesar de ello, a día de hoy, no es fácil encontrar en nuestro país proyectos de Big Data ejecutados en el negocio de la gestión de Recursos Humanos. Este artículo pretende ayudar al gestor de RR.HH. a entender qué es el Big Data y cómo puede ponerlo al servicio de su negocio, ofreciéndole una visión específica de cómo se define y cuáles son sus características principales, las aplicaciones desarrolladas hasta la fecha en este sector y las dificultades y retos principales a la hora de implantar modelos Big Data en la gestión de Recursos Humanos.

Inferring ECA-based rules for ambient intelligence using evolutionary feature extraction

Leila S. Shafti, Pablo A. Haya, Manuel García-Herranz, Eduardo Pérez

Journal of Ambient Intelligence and Smart Environments 5 (6), 563-587 (2013) [download] (JCR, IF 2012: 1.298, Q2)

One of the goals in Ambient Intelligence is to enable Intelligent Environments to take decisions based on the perceived context. In our previous work, we successfully explored how the inhabitants can communicate their own preferences with the environment using Event-Condition-Action (ECA) rules. The easiness of the communication language combined with an appropriate explanation mechanism gives trust to the Intelligent Environment actions. However, defining every preference, and maintaining them up-to-date can be cumbersome. Therefore, a complementary mechanism is required to learn from user behavior and adapt to small changes without being explicitly requested for. Inferring behaviors effectively from data collected from sensors in an Intelligent Environment is a challenging problem. The main issues include primitive representation of data, the necessity of a high number of sensors, and dealing with few training data collected in a short time. We present MFE3/GADR, an evolutionary constructive induction method to ease inferring inhabitants’ preferences from data collected from simple sensors. We show that this method detects successfully relevant sensors and constructs highly informative features that abstract relations among them. The constructed features, in addition to improving significantly the learning accuracy, break down and encapsulate the performance of inhabitants into decision trees that can easily be converted to ECA rules for further use in the Intelligent Environment. Comparing the empirical results show that our method can reduce a large set of complex ECA rules that represent the preferences to a smaller set of simple ECA rules.

Designing videogames to improve students’ motivation

P. Molins-Ruano, C. Sevilla, S. Santini, P.A. Haya, P. Rodríguez, G.M. Sacha

Computers in Human Behavior 31 (2014) 571–579 [download] (JCR, IF 2012: 2.694, Q1 21/129 Psychology, multidisciplinary)

The use of new technical tools as a mean to increase the motivation and improve the education of students is an intriguing and pressing issue. Specifically, great interest has been shown in the use of videogames since they constitute a common leisure-time activity of many young students, a circumstance that shows their motivational, if not their educational, potential. In this paper we suggest that the design of videogames can be a very effective activity. To demonstrate this, we have used game design as a test-bed for an experience involving Computer Science and History students: interdisciplinary teams have cooperated in the design of a video-game on an historical theme. The experience has been repeated along three academic years. The students’ motivation has been evaluated in the last 2 years, demonstrating that it is higher when they use the interdisciplinary design of videogames as a way of learning instead of traditional learning methods.