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The evolution of new information technologies has originated new possibilities to develop pedagogical methodologies that provide the necessary knowledge and skills in the higher education environment. These technologies are built around... more
The evolution of new information technologies has originated new possibilities to develop pedagogical methodologies that provide the necessary knowledge and skills in the higher education environment. These technologies are built around the use of Internet and other new technologies, such as virtual education, distance learning, and long-life learning. This chapter focuses on several traditional artificial intelligence (AI) techniques, such as automated planning and scheduling, and how they can be applied to pedagogical and educational environments. The chapter describes both the main issues related with AI techniques and e-learning technologies, and how long-life learning processes and problems can be represented and managed by using an AI-based approach.
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The presence of MOOCs has increased exponentially in the context of distance education. However, many students who enroll in this type of courses drop out before completion. Several circumstances may cause dropout at any stage of the... more
The presence of MOOCs has increased exponentially in the context of distance education. However, many students who enroll in this type of courses drop out before completion. Several circumstances may cause dropout at any stage of the course and, in any case, before getting the certificate. Some students are not able to follow the course, others fail in the exams and leave, others only aim at getting a general overview of the course contents, others take all the activities but the final test, because of being interested in gaining knowledge but not in obtaining the certificate, etc. For this reason, it is interesting to analyze and understand the behavior of each student while interacting with the course. In this direction, the goal of this work is to predict whether a student will abandon a MOOC before completing it, so that it is possible to intervene accordingly, by warning the teacher about the dropout risk, notifying the student about this risk, etc. Different machine learning techniques have been tested with real data of a MOOC supported by EdX at UAM. In this article, the results of the work carried out in this direction are presented.
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Abstract. E-Learning systems offer students innovative and attractive ways of learning through augmentation or substitution of traditional lectures and exercises with online learning material. Such material can be accessed at any time... more
Abstract. E-Learning systems offer students innovative and attractive ways of learning through augmentation or substitution of traditional lectures and exercises with online learning material. Such material can be accessed at any time from anywhere using different devices, and can be personalized according to the individual student’s needs, goals and knowledge. However, authoring and evaluation of this material remains a complex a task. While many researchers focus on the authoring support, not much has been done to facilitate the evaluation of e-Learning applications, which requires processing of the vast quantity of data generated by students. We address this problem by proposing an approach for detecting potential symptoms of low performance in e-Learning courses. It supports two main steps: generating the production rules of C4.5 algorithm and filtering the most representative rules, which could indicate low performance of students. In addition, the approach has been evaluated o...
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In this article we present the architecture of an m-learning (mobile-learning) environment using Bluetooth as communications technology. We also describe its practical implementation into a technical laboratory where students can access,... more
In this article we present the architecture of an m-learning (mobile-learning) environment using Bluetooth as communications technology. We also describe its practical implementation into a technical laboratory where students can access, work and leave at any time. The system incorporates artificial intelligence techniques in order to adapt itself to the characteristics of each user. This strategy allows us to recognize each student, organize his/her work and evaluate his/her results, without educator intervention. Nevertheless, the teacher will be reported about the student activities and will be advised when the situation requires it. The Bluetooth facilities assure good isolation between different classrooms and multiuser wireless connections.
Adaptive educational hypermedia systems (AEHS) seek to make easier the learning process for each student by providing each one (potentially) different educative contents, customized according to the student’s needs and preferences. One of... more
Adaptive educational hypermedia systems (AEHS) seek to make easier the learning process for each student by providing each one (potentially) different educative contents, customized according to the student’s needs and preferences. One of the main concerns with AEHS is to test and decide whether adaptation strategies are beneficial for all the students or, on the contrary, some of them would benefit from different decisions of the adaptation engine. Data-mining (DM) techniques can provide support to deal with this issue; specifically, this chapter proposes the use of DM techniques for detecting potential problems of adaptation in AEHS. © 2010 by Taylor & Francis Group, LLC
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This chapter focuses on the key practical aspects to be considered when facing the task of developing predictive models for student learning outcomes. It is based on the authors' experience building and delivering dropout prediction... more
This chapter focuses on the key practical aspects to be considered when facing the task of developing predictive models for student learning outcomes. It is based on the authors' experience building and delivering dropout prediction models within higher education contexts. The chapter presents the information used to generate the predictive models, how this information is treated, how the models are fed, which types of algorithms have been used, and why and how the obtained results have been evaluated. It recommends best practices for building, training, and evaluating predictive models. It is hoped that readers will find these recommendations useful for the design, development, deployment, and use of early warning systems.
ABSTRACT Tesis inédita de la Universidad Autónoma de Madrid.Escuela Técnica Superior de Informática, Departamento de Ingeniería Informática.
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Información del artículo Método para la aplicación de documentación inteligente de frameworks orientados a objetos.
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Abstract Recommender systems suggest users information items they may be interested in. User profiles or usage data are compared with some reference characteristics, which may belong to the items (content-based approach), or to other users... more
Abstract Recommender systems suggest users information items they may be interested in. User profiles or usage data are compared with some reference characteristics, which may belong to the items (content-based approach), or to other users in the same context (collaborative filtering approach). These items are usually presented as a ranking, where the more relevant an item is predicted to be for a user, the higher it appears in the ranking.
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ABSTRACT Observe appropriate evidence that pointing emotions plays an important role in the learning process. However, there is no precedent of a research analyzing the relationship between emotions and academic marks using text analysis.... more
ABSTRACT Observe appropriate evidence that pointing emotions plays an important role in the learning process. However, there is no precedent of a research analyzing the relationship between emotions and academic marks using text analysis. Thus, in this article, we show the experience we have performed in order to analyze the possible existing correlations between student marks, assigned by both their classmates and by their instructors, and the emotion traces that can be found in their writings. To that end, we gathered data corresponding to text contributions of a course on Computer Systems in our University and perform the correspondent analysis. The obtained results look to indicate that some kind of correlation exists between marks and emotions in both the highest and the lowest marks.
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ABSTRACT This paper presents SentBuk, a Facebook application that extracts information about the user sentiment automatically, in a non-intrusive way. It performs sentiment analysis of user writings in Facebook walls, classifying each... more
ABSTRACT This paper presents SentBuk, a Facebook application that extracts information about the user sentiment automatically, in a non-intrusive way. It performs sentiment analysis of user writings in Facebook walls, classifying each sentence as positive, neutral or negative. Finally, the overall user sentiment is calculated. On one hand, this information is useful to enrich user models for adaptive e-learning systems, so that these systems can adapt any of their aspects (tasks to be proposed to the student, contents, and so on) according to each student sentiment, among other criteria. On the other hand, the polarity of the emotions transmitted by the students enrolled in a course can constitute a useful feedback for the course teacher.
... Tamara Dulzaines Castañeda (1); Omelio Cepero Rodríguez (2); Leonel Lazo Pérez (2) 1). Jardín Zoológico Camilo Cienfuegos de Santa Clara. ... 13. Santana Ramos Ileana.; Lazo PL.; Carrazana VA.; Suárez Fernández Yolanda.; Cepero RO.;... more
... Tamara Dulzaines Castañeda (1); Omelio Cepero Rodríguez (2); Leonel Lazo Pérez (2) 1). Jardín Zoológico Camilo Cienfuegos de Santa Clara. ... 13. Santana Ramos Ileana.; Lazo PL.; Carrazana VA.; Suárez Fernández Yolanda.; Cepero RO.; Quintero CE. ...
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Resumen: En este artículo se presentan los fundamentos y experiencias de uso de dos sistemas que dan soporte a la creación y evaluación, respectivamente, de entornos de aprendizaje móviles adaptativos. En estos entornos, generados... more
Resumen: En este artículo se presentan los fundamentos y experiencias de uso de dos sistemas que dan soporte a la creación y evaluación, respectivamente, de entornos de aprendizaje móviles adaptativos. En estos entornos, generados dinámicamente por el sistema CoMoLE, se recomiendan las actividades más adecuadas para ser realizadas por cada estudiante en cada momento, facilitándole así el aprovechamiento de su tiempo disponible; también se adapta la interfaz que da soporte a la realización de las ...
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TDX - Tesis Doctorals en Xarxa - 10 anys 2001 · 2011. Advanced Search. Restrict to TDX. ...