Education 2.0: Student Generated Learning Materials through Collaborative Work

AbstractThe Inside-Outside strategy pushes students to be more involved in their learning. As shown by the Integrated Learning Processes model this improves learning. A course on operating systems was redesigned in such a way that students would generate most of their learning materials as well a significant part of their evaluation exams. This new approach resulted in a statistical significant improvement of student's grade as measured by a standardized exam compared with a previous student intake

Software Libre, Pirateria y Cultura de TI en Mexico

This research in progress analyzes the use of open-source software as a potential alternate path to applications piracy that affects so much the Mexican region, causing economic losses in millions and severe damages to national morality. We propose a determination model where the lack of information technology use culture, along with the high costs associated to commercial applications, fosters the generation of a black market for pirate software. Due to the cognitive dissonance generated, values tend to relax making piracy acceptable or, in the worst cases, an encouragement to act against the great producers of technology in the world. The open-source software alternative provides a possibility for the competitive development of firms, without breaking the law, and promoting a cooperative spirit rarely observed in the business context of Latin American cultures. A perception analysis through a cross-sectional survey study is proposed. We expect to gain valuable insights for the establishment of awareness-building programs in the industry sector regarding the use and benefits of information technologies

Gamifying massive online courses: effects on the social networks and course completion rates

This paper analyzes the e ects of gamification in the social network of a massive online course. An educational social-networking platform gathered information about the contributions of participants and about the social networks that were formed during the course. A gamification layer with three game elements (points, badges, and leaderboard) was then implemented in the online learning platform. Social network analysis (SNA) and principal component analysis (PCA) were used to analyze the di erences between a treatment and a comparison group (N = 591 and N = 427), using a set of 20 variables for each participant which quantified contributions to the learning platform as well as position and influence in the social network. The results of SNA show that gamification influences the structure of the social network of the course. The results also suggest that the variables cluster similarly for each group and that the linear combination of variables called the first component (F1) is a good descriptor of students’ work and position in the network. F1 can be used to build predictive models of course completion. The models show that the probability of passing the course increases more rapidly in the treatment (gamified) group.Spanish Ministry of Economic A airs and Digital Transformation (Grant TIN2014-54874-R) and Government of Comunidad de Madrid (Grant CM/JIN/2019-037).info:eu-repo/semantics/publishedVersio

Plataforma Web de Gestión de Actividades de aprendizaje, para soporte del modelo de Aula Invertida en Educación Media

This article presents the SmartFC web platform, a tool aimed at teachers, which supports the implementation of the flipped classroom model even in conditions of low or no connectivity. This proposal introduce the use of open educational resources but also proposes a learning activity to be designed or reused by each teacher under the flipped classroom model, in addition to propitiating the creation of more participative and collaborative classe

A monitoring-based approach for WSN security using IEEE-802.15.4/6LowPAN and DTLS communication

International audienceIn this paper, we present a monitoring based approach for securing upper layer communications of WSN (Wireless Sensor Networks), the latter using IEEE802.15.4/6LoWPAN stacks and tinyDTLS. The monitoring techniques have been integrated as an extension to the industrial tool MMT (Montimage Monitoring Tool). The MMT-extension verifies that the network is working following a set of security rules that have been defined by ETSI. The security rules check if the protocol stack is working properly. If MMT detects a security rule that was not respected, then it sends an alarm to the system manager so that he can take properly reactive adjustments. We tested each of the security rules in MMT's extension using point-to-point configuration. After all these tests were verified, we tested our MMT-extension using real data gathered from the FIT IoT-LAB platform. The results of these tests shown that our MMT's extension for WSN using IEEE-802.15.4/6LowPAN and DTLS communication is feasible

Mathematical modelling based learning strategy

We present the Mathematical Modelling Learning strategy in which students create a model that will predict behaviour of existing phenomena using real data. In our implementation students create models from atmospheric data and solve them to determine which weather conditions favour high levels of pollutants in the atmosphere of Monterrey metropolitan area in Mexico. To carry out the strategy we structure course topics around this single comprehensive and integrative project. Students follow a procedure consisting of 4 stages. In the first stage they do statistical analysis of the data. In the second stage, students interpolate missing data and project component data to a 2D map of the metro area. In the third stage students create the mathematical models by carrying out curve fitting through least squares technique. In the third stage, students solve the models by finding roots, solving systems of equations, solving differential equations or integrating. The final deliverable is to determine under which weather conditions there can be an environmental situation that put people's health in danger. Analysis of the strategy is presented as well as statistical results. © The Authors. Published by Elsevier B.V

A parallel implementation of singular value decomposition for video-on-demand services design using principal component analysis

We have developed a mathematical model for video on demand server design based on principal component analysis. Singular value decomposition on the video correlation matrix is used to perform the PCA. The challenge is to counter the computational complexity, which grows proportionally to n3, where n is the number of video streams. We present a solution from high performance computing, which splits the problem up and computes it in parallel on a distributed memory system. © The Authors. Published by Elsevier B.V

Overcoming uncertainty on video-on-demand server design by using self-similarity and principal component analysis

In this paper we use a small amount of video files to design a video-on-demand server. We use the available video information to overcome uncertainties such as future user preference, type of video file (movie, cartoon, documentary), video compression technique, etc. Using principal component analysis we overcome such uncertainties by reducing the dimensionality of the video data, creating a new video trace that captures statistical characteristics of most video files; we call this the characteristic video trace. Using the Pareto probability distribution for the size of the video frames (of the characteristic video trace) and self-similarity we develop a non-asymptotic model which predicts memory buffer size for a required quality of service. By obtaining the necessary parameters for the mathematical model from the characteristic video trace we could design the server without more information. © 2013 The Authors. Published by Elsevier B.V