Object-Based Customization of Learning Content: Potentials and Pitfalls

Specification consortia and standardization bodies concentrate on e-Learning objects to en-sure reusability of content. Learning objects may be collected in a library and used for deriv-ing course offerings that are customized to the needs of different learning communities. How-ever, customization of courses is possible only if the logical dependencies between the learn-ing objects are known. Metadata for describing object relationships have been proposed in several e-Learning specifications. This paper discusses the customization potential of e-Learning objects but also the pitfalls that exist if content is customized inappropriately.

New Methodology for Integrating Teams into Multidisciplinary Project Based Learning

This paper describes the collaboration among students and professors in four different subjects, to develop multidisciplinary projects. The objective is to simulate the conditions in a company environment. A new methodology based on student interaction and content development in a Wiki environment has been developed. The collaborative server created an ‘out of the classroom’ discussion forum for students of different subjects, and allowed them to compile a ‘project work’ portfolio. Students and professors participated with enthusiasm, due to the correct well-distributed work and the easiness of use of the selected platform in which only an internet connected computer is needed to create and to discuss the multidisciplinary projects. Quality of developed projects has been dramatically improved due to integration of results provided from the different teams.

Games based learning for Exploring Cultural Conflict

In this paper we discuss the early stage design of MIXER, a technology enhance educational application focused at supporting children in learning about cultural conflict, achieved through the use of a game with an effective embodied AI agent. MIXER is being developed re-using existing technology applied to a different context and purpose with the aim of creating an educational and enjoyable experience for 9-11 year olds. This paper outlines MIXER’s underpinning technology and theory. It presents early stage design and development, highlighting current research directions.

Project-based learning experience on Data Structures course

This paper presents the innovations in the practical work of the Data Structures subject carried out in the last five years, including a transition period and a first year of implantation of the European Higher Education Area. The practical coursework is inspired by a project-based methodology and from 2008/2009 additional laboratory sessions are included in the subject schedule. We will present the academic results and ratios of the mentioned time period which imply a significant improvement on students' performance.

Applying Problem-Based Project-Organized Learning in a traditional system

Nowadays, PBL is considered a suitable methodology for engineering education. But making the most of this methodology requires some features, such as multidisciplinary, illstructured teamwork and autonomous research that sometimes are not easy to achieve. In fact, traditional university systems, including curricula, teaching methodologies, assessment and regulation, do not help the implementation of these features. Firstly, we look through the main differences found between a traditional system and the Aalborg model, considered a reference point in PBL. Then, this work is aimed at detecting the main obstacles that a standing traditional system presents to PBL implementation. A multifaceted PBL experience, covering three different disciplines, brings us to analyse these difficulties, order them according to its importance and decide which should be the first changes. Finally, we propose a straightforward introduction of generic competences in the curricula aimed at supporting the use of Problem-Based Project-Organized Learning

An example of Learning based on competences: Use of Maxima in Linear Algebra for Engineers

This paper analyzes the role of Computer Algebra Systems (CAS) in a model of learning based on competences. The proposal is an e-learning model Linear Algebra course for Engineering, which includes the use of a CAS (Maxima) and focuses on problem solving. A reference model has been taken from the Spanish Open University. The proper use of CAS is defined as an indicator of the generic ompetence: Use of Technology. Additionally, we show that using CAS could help to enhance the following generic competences: Self Learning, Planning and Organization, Communication and Writing, Mathematical and Technical Writing, Information Management and Critical Thinking.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: An application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39)

Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learning MBCs from data. Basically, it consists of determining the Markov blanket around each class variable using the HITON algorithm, then specifying the directionality over the MBC subgraphs. Our approach is applied to the prediction problem of the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson’s Disease Questionnaire (PDQ-39) in order to estimate the health-related quality of life of Parkinson’s patients. Fivefold cross-validation experiments were carried out on randomly generated synthetic data sets, Yeast data set, as well as on a real-world Parkinson’s disease data set containing 488 patients. The experimental study, including comparison with additional Bayesian network-based approaches, back propagation for multi-label learning, multi-label k-nearest neighbor, multinomial logistic regression, ordinary least squares, and censored least absolute deviations, shows encouraging results in terms of predictive accuracy as well as the identification of dependence relationships among class and feature variables.

An approach to automatic learning assessment based on the computational theory of perceptions

E-learning systems output a huge quantity of data on a learning process. However, it takes a lot of specialist human resources to manually process these data and generate an assessment report. Additionally, for formative assessment, the report should state the attainment level of the learning goals defined by the instructor. This paper describes the use of the granular linguistic model of a phenomenon (GLMP) to model the assessment of the learning process and implement the automated generation of an assessment report. GLMP is based on fuzzy logic and the computational theory of perceptions. This technique is useful for implementing complex assessment criteria using inference systems based on linguistic rules. Apart from the grade, the model also generates a detailed natural language progress report on the achieved proficiency level, based exclusively on the objective data gathered from correct and incorrect responses. This is illustrated by applying the model to the assessment of Dijkstra’s algorithm learning using a visual simulation-based graph algorithm learning environment, called GRAPHs

Problem-based learning supported by semantic techniques

Problem-based learning has been applied over the last three decades to a diverse range of learning environments. In this educational approach, different problems are posed to the learners so that they can develop different solutions while learning about the problem domain. When applied to conceptual modelling, and particularly to Qualitative Reasoning, the solutions to problems are models that represent the behaviour of a dynamic system. The learner?s task then is to bridge the gap between their initial model, as their first attempt to represent the system, and the target models that provide solutions to that problem. We propose the use of semantic technologies and resources to help in bridging that gap by providing links to terminology and formal definitions, and matching techniques to allow learners to benefit from existing models.

Web-based education in Spanish Universities. A Comparison of Open Source E-Learning Platforms

Web-based education or „e-learning‟ has become a critical component in higher education for the last decade, replacing other distance learning methods, such as traditional computer training or correspondence learning. The number of university students who take on-line courses is continuously increasing all over the world. In Spain, nearly a 90% of the universities have an institutional e-learning platform and over 60% of the traditional on-site courses use this technology as a supplement to the traditional face-to-face classes. This new form of learning allows the disappearance of geographical barriers and enables students to schedule their own learning process, among some other advantages. On-line education is developed through specific software called „e-learning platform‟ or „virtual learning environment‟ (VLE). A considerable number of web-based tools to deliver distance courses are currently available. Open source software packages such as Moodle, Sakai, dotLRN or Dokeos are the most commonly used in the virtual campuses of Spanish universities. This paper analyzes the possibilities that virtual learning environments provide university teachers and learners and offers a technical comparison among some of the most popular e-learning learning platforms.

Measuring the influence of Cooperative Learning and Project Based Learning on problem solvin skill.

The aim of this study is to evaluate the effects obtained after applying two active learning methodologies (cooperative learning and project based learning) to the achievement of the competence problem solving. This study was carried out at the Technical University of Madrid, where these methodologies were applied to two Operating Systems courses. The first hypothesis tested was whether the implementation of active learning methodologies favours the achievement of ?problem solving?. The second hypothesis was focused on testing if students with higher rates in problem solving competence obtain better results in their academic performance. The results indicated that active learning methodologies do not produce any significant change in the generic competence ?problem solving? during the period analysed. Concerning this, we consider that students should work with these methodologies for a longer period, besides having a specific training. Nevertheless, a close correlation between problem solving self appraisal and academic performance has been detected.

Assessing user bias in affect detection within context-based spoken dialog systems

This paper presents an empirical evidence of user bias within a laboratory-oriented evaluation of a Spoken Dialog System. Specifically, we addressed user bias in their satisfaction judgements. We question the reliability of this data for modeling user emotion, focusing on contentment and frustration in a spoken dialog system. This bias is detected through machine learning experiments that were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. The target used was the satisfaction rating and the predictors were conversational/dialog features. Our results indicated that standard classifiers were significantly more successful in discriminating frustration and contentment and the intensities of these emotions (reflected by user satisfaction ratings) from annotator data than from user data. Indirectly, the results showed that conversational features are reliable predictors of the two abovementioned emotions.

Project based learning activities as a means of adapting conventional curricula to the demands of the 21st century aeronautical engineer: The design and building of the EYEFLY 1.

In this paper we report the process of designing and building the EYEFLY 1, a real UAS platform which has just performed its maiden flight. For the development of this aircraft, 30 groups of students from successive years at the Escuela Universitaria de Ingeniería Técnica Aeronáutica (EUITA) of the Universidad Politécnica de Madrid (UPM) carried out their compulsory End of Degree Project as a coordinated Project Based learning activity. Our conclusions clearly indicate that Project Based Learning activities can provide a valid complement to more conventional, theoretically-based, teaching methods. The combination of both approaches will allow us to maintain traditional but well-tested methods for providing our students with a sound knowledge of fundamental engineering disciplines and, at the same time, to introduce our students to exciting and relevant engineering situations and sceneries where social and business skills, such as communication skills, team-working or decision-taking, can be put into practice.