Data mining in education

The third chapter, data mining in education, examines potentials and constraints in the use of data mining in education, summarizing the potential they have to offer meaningful support to: students, teachers, tutors, authors, developers, researchers, and the education and training institutions in which they work and study.

Combining artificial intelligence and human problem solving: Proposing a new architecture for ITS's

This paper shows a comparative study between the Artificial Intelligence Problem Solving and the Human Problem Solving. The study is based on the solution by many ways of problems proposed via multiple-choice questions. General techniques used by humans to solve this kind of problems are grouped in blocks and each block is divided in steps. A new architecture for ITS - Intelligent Tutoring System is proposed to support experts' knowledge representation and novices' activities. Problems are represented by a text and feasible answers with particular meaning and form, to be rigorously analyzed by the solver to find the right one. Paths through a conceptual space of states represent each right solution.

Design instrucional: uma abordagem do design gráfico para o desenvolvimento de ferramentas de suporte à Educação a Distância

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Adaptive Rückmeldungen im intelligenten Tutorensystem LARGO

Das intelligente Tutorensystem LARGO für die Rechtswissenschaften soll Jurastudenten helfen, Argumentationsstrategien zu lernen. Im verwendeten Ansatz werden Gerichtsprotokolle als Lernmaterialien verwendet: Studenten annotieren diese und erstellen graphische Repräsentationen des Argumentationsverlaufs. Das System kann dabei zur Reflexion über die von Anwälten vorgebrachten Argumente anregen und Lernende auf mögliche Schwächen in ihrer Analyse des Disputs hinweisen. Zur Erkennung von Schwächen verwendet das System Graphgrammatiken und kollaborative Filtermechanismen. Dieser Artikel stellt dar, wie in LARGO auf Basis der Bestimmung eines „Benutzungskontextes“ die Rückmeldungen im System benutzungsadaptiv gestaltet werden. Weiterhin diskutieren wir auf Basis der Ergebnisse einer kontrollierten Studie mit dem System, welche mit Jurastudierenden an der University of Pittsburgh stattfand, in wie weit der automatisch bestimmte Benutzungskontext zur Vorhersage von Lernerfolgen bei Studenten verwendbar ist.

Visualization of a student predictive model for 3D virtual environments driven to procedural training

This document presents theimplementation ofa Student Behavior Predictor Viewer(SBPV)for a student predictive model. The student predictive model is part of an intelligent tutoring system, and is built from logs of students’ behaviors in the “Virtual Laboratory of Agroforestry Biotechnology”implemented in a previous work.The SBPVis a tool for visualizing a 2D graphical representationof the extended automaton associated with any of the clusters ofthe student predictive model. Apart from visualizing the extended automaton, the SBPV supports the navigation across the automaton by means of desktop devices. More precisely, the SBPV allows user to move through the automaton, to zoom in/out the graphic or to locate a given state. In addition, the SBPV also allows user to modify the default layout of the automaton on the screen by changing the position of the states by means of the mouse. To developthe SBPV, a web applicationwas designedand implementedrelying on HTML5, JavaScript and C#.

Mejoras y extensiones en el Front-End de un modelo de predicción de acciones de un estudiante en un laboratorio virtual 3D

Este documento presenta las mejoras y las extensiones introducidas en la herramienta de visualización del modelo predictivo del comportamiento del estudiante o Student Behavior Predictor Viewer (SBPV), implementada en un trabajo anterior. El modelo predictivo del comportamiento del estudiante es parte de un sistema inteligente de tutoría, y se construye a partir de los registros de actividad de los estudiantes en un laboratorio virtual 3D, como el Laboratorio Virtual de Biotecnología Agroforestal, implementado en un trabajo anterior, y cuyos registros de actividad de los estudiantes se han utilizado para validar este trabajo fin de grado. El SBPV es una herramienta para visualizar una representación gráfica 2D del grafo extendido asociado con cualquiera de los clusters del modelo predictivo del estudiante. Además de la visualización del grafo extendido, el SBPV controla la navegación a través del grafo por medio del navegador web. Más concretamente, el SBPV permite al usuario moverse a través del grafo, ampliar o reducir el zoom del gráfico o buscar un determinado estado. Además, el SBPV también permite al usuario modificar el diseño predeterminado del grafo en la pantalla al cambiar la posición de los estados con el ratón. Como parte de este trabajo fin de grado, se han corregido errores existentes en la versión anterior y se han introducido una serie de mejoras en el rendimiento y la usabilidad. En este sentido, se han implementado nuevas funcionalidades, tales como la visualización del modelo de comportamiento de cada estudiante individualmente o la posibilidad de elegir el método de clustering para crear el modelo predictivo del estudiante; así como ha sido necesario rediseñar la interfaz de usuario cambiando el tipo de estructuras gráficas con que se muestran los elementos del modelo y mejorando la visualización del grafo al interaccionar el usuario con él. Todas estas mejoras se explican detenidamente en el presente documento.---ABSTRACT---This document presents the improvements and extensions made to the visualization tool Student Behavior Predictor Viewer (SBPV), implemented in a previous job. The student behavior predictive model is part of an intelligent tutoring system, and is built from the records of students activity in a 3D virtual laboratory, like the “Virtual Laboratory of Agroforestry Biotechnology” implemented in a previous work, and whose records of students activity have been used to validate this final degree work. The SBPV is a tool for visualizing a 2D graphical representation of the extended graph associated with any of the clusters of the student predictive model. Apart from visualizing the extended graph, the SBPV supports the navigation across the graph by means of desktop devices. More precisely, the SBPV allows user to move through the graph, to zoom in/out the graphic or to locate a given state. In addition, the SBPV also allows user to modify the default layout of the graph on the screen by changing the position of the states by means of the mouse. As part of this work, some bugs of the previous version have been fixed and some enhancements have been implemented to improve the performance and the usability. In this sense, we have implemented new features, such as the display of the model behavior of only one student or the possibility of selecting the clustering method to create the student predictive model; as well as it was necessary to redesign the user interface changing the type of graphic structures that show model elements and improving the rendering of the graph when the user interacts with it. All these improvements are explained in detail in the next sections.

aiTutor : um etutor de agentes inteligentes

Relatório de estágio apresentado para a obtenção do grau de mestre em Educação e Comunicação Multimédia

aiTutor : um etutor de agentes inteligentes

Relatório de estágio apresentado para a obtenção do grau de mestre em Educação e Comunicação Multimédia

Intelligent behavior in a Cyber-Ambient training system for control center operators

This paper deals with the application of an intelligent tutoring approach to delivery training in diagnosis procedures of a Power System. In particular, the mechanisms implemented by the training tool to support the trainees are detailed. This tool is part of an architecture conceived to integrate Power Systems tools in a Power System Control Centre, based on an Ambient Intelligent paradigm. The present work is integrated in the CITOPSY project which main goal is to achieve a better integration between operators and control room applications, considering the needs of people, customizing requirements and forecasting behaviors.

Intelligent Bio-Inspired system for manufacturing scheduling under uncertainties

A novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS), Case-based Reasoning (CBR), and Bio-Inspired Optimization Techniques (BIT) will be described. AC has emerged as a paradigm aiming at incorporating applications with a management structure similar to the central nervous system. The main intentions are to improve resource utilization and service quality. In this paper we envisage the use of MAS paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with AC properties, in order to reduce the complexity of managing manufacturing systems and human interference. The proposed CBR based Intelligent Scheduling System was evaluated under different dynamic manufacturing scenarios.

Cyber-ambient intelligent training of operators in power systems control centres

Cyber-Physical Systems and Ambient Intelligence are two of the most important and emerging paradigms of our days. The introduction of renewable sources gave origin to a completely different dimension of the distribution generation problem. On the other hand, Electricity Markets introduced a different dimension in the complexity, the economic dimension. Our goal is to study how to proceed with the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances.

Intelligent automatic overtaking system using vision for vehicle detection

There is clear evidence that investment in intelligent transportation system technologies brings major social and economic benefits. Technological advances in the area of automatic systems in particular are becoming vital for the reduction of road deaths. We here describe our approach to automation of one the riskiest autonomous manœuvres involving vehicles – overtaking. The approach is based on a stereo vision system responsible for detecting any preceding vehicle and triggering the autonomous overtaking manœuvre. To this end, a fuzzy-logic based controller was developed to emulate how humans overtake. Its input is information from the vision system and from a positioning-based system consisting of a differential global positioning system (DGPS) and an inertial measurement unit (IMU). Its output is the generation of action on the vehicle’s actuators, i.e., the steering wheel and throttle and brake pedals. The system has been incorporated into a commercial Citroën car and tested on the private driving circuit at the facilities of our research center, CAR, with different preceding vehicles – a motorbike, car, and truck – with encouraging results.

An Intelligent System for Investigations and Provision of Safety for Complex Constructions

Methodology of computer-aided investigation and provision of safety for complex constructions and a prototype of the intelligent applied system, which implements it, are considered. The methodology is determined by the model of the object under scrutiny, by the structure and functions of investigation of safety as well as by a set of research methods. The methods are based on the technologies of object-oriented databases, expert systems and on the mathematical modeling. The intelligent system’s prototype represents component software, which provides for support of decision making in the process of safety investigations and investigation of the cause of failure. Support of decision making is executed by analogy, by determined search for the precedents (cases) with respect to predicted (on the stage of design) and observed (on the stage of exploitation) parameters of the damage, destruction and malfunction of a complex hazardous construction.