Marina Vicario


2 Cognitive Footprints: Analytical and Predictive Paradigm for Digital Learning

Authors: Marina Vicario, Amadeo Argüelles, Pilar Gómez, Carlos Hernández


In this paper, the Computer Research Network of the National Polytechnic Institute of Mexico proposes a paradigmatic model for the inference of cognitive patterns in digital learning systems. This model leads to metadata architecture useful for analysis and prediction in online learning systems; especially on MOOc's architectures. The model is in the design phase and expects to be tested through an institutional of courses project which is going to develop for the MOOc.

Keywords: Digital Learning, Learning Analytics, Educational Computing, cognitive footprints, predictive learning, educational informatics

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1 Using the M-Learning to Support Learning of the Concept of the Derivative

Authors: Elena F. Ruiz, Marina Vicario, Chadwick Carreto, Rubén Peredo


One of the main obstacles in Mexico’s engineering programs is math comprehension, especially in the Derivative concept. Due to this, we present a study case that relates Mobile Computing and Classroom Learning in the “Escuela Superior de Cómputo”, based on the Educational model of the Instituto Politécnico Nacional (competence based work and problem solutions) in which we propose apps and activities to teach the concept of the Derivative. M- Learning is emphasized as one of its lines, as the objective is the use of mobile devices running an app that uses its components such as sensors, screen, camera and processing power in classroom work. In this paper, we employed Augmented Reality (ARRoC), based on the good results this technology has had in the field of learning. This proposal was developed using a qualitative research methodology supported by quantitative research. The methodological instruments used on this proposal are: observation, questionnaires, interviews and evaluations. We obtained positive results with a 40% increase using M-Learning, from the 20% increase using traditional means.

Keywords: Mobile Computing, Augmented Reality, Educational Research, Classroom Learning

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