Compiling a simulation language in APL

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in APL Quote Quad, http://dx.doi.org/10.1145/327600.327625This paper describes the procedure used to build several compilers, written in APL and APL2, to translate two continuous simulation languages into APL and C++. The advantages and disadvantages of using APL to write a compiler are discussed. A compromise had to be found between performance (the model execution speed) and flexibility (the ease to modify parameters and test "what if" situations). The resulting compiler (an APL2 packaged workspace) has been used successfully to generate educational applications and in medical research.This paper has been sponsored by the Spanish Interdepartmental Commission of Science and Technology (CICYT), project number TIC-96-0723-C02-01

An Approach for Automatic Generation of on-line Information Systems based on the Integration of Natural Language Processing and Adaptive Hypermedia Techniques

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid. Escuela Politécnica Superior, Departamento de ingeniería informática. Fecha de lectura: 29-05-200

¿Pueden los ordenadores evaluar automáticamente preguntas abiertas?

Tradicionalmente la sección de evaluación de la mayoría de los cursos on-line se basaba únicamente en preguntas de elección múltiple. Sin embargo, según la opinión generalizada de muchos investigadores, educadores y psicólogos restringirse exclusivamente a preguntas cerradas no permite evaluar completamente las habilidades cognitivas de los estudiantes. Esto ha tenido como consecuencia la creación del campo conocido como Evaluación Automática de preguntas abiertas. Lo que se plantea en este artículo es si realmente funciona. Esto es, ¿cuán fiable es un ordenador como evaluador automático de respuestas en texto libre escritas por estudiantes? Para dar respuesta a este interrogante hemos revisado la historia de este campo y visto como en los últimos años, estos sistemas han empezado a usarse como comprobadores de las notas puestas por los profesores, para asegurar una correcta evaluación. En todo caso no se puede olvidar que los ordenadores (al menos por ahora) no son más que máquinas sin sentido común ni inteligencia propia, lo que les impide enfrentarse con éxito a respuestas demasiado originales que quizás estén bien pero se salen de lo comúnmente establecido como correcto. El desafío está propuesto y, en nuestra opinión, mantener los objetivos realistas será lo que consiga que este campo avance, con paso firme, despejando cualquier incertidumbre sobre su validezEste trabajo ha sido financiado por el proyecto TIN2004-0314 del Ministerio de Educación y Ciencia español

On the dynamic adaptation of Computer Assisted Assessment of free-text answers

The final publication is available at Springer via http://dx.doi.org/10.1007/11768012_54Proceedings of 4th International Conference, AH 2006, Dublin, Ireland, June 21-23, 2006.To our knowledge, every free-text Computer Assisted Assessment (CAA) system automatically scores the students and gives feedback to them according to their responses, but, none of them include yet personalization options. The free-text CAA system Atenea [1] had simple adaptation possibilities by keeping static student profiles [2]. In this paper, we present a new adaptive version called Willow. It is based on Atenea and adds the possibility of dynamically choosing the questions to be asked according to their difficulty level, the students’ profile and previous answers. Both Atenea and Willow have been tested with 32 students that manifested their satisfaction after using them. The results stimulate us to continue exploiting the possibilities of incorporating dynamic adaptation to free-text CAA.This work has been sponsored by Spanish Ministry of Science and Technology, project number TIN2004-0314

Automatic identification of terms for the generation of students’ concept maps

Proceedings of the 4th International Conference on Multimedia and Information and Communication Technologies in Education, M-icte 2006, held in Seville (Spain) on November 2006Willow, an adaptive multilingual free-text Computer-Assisted Assessment system, automatically evaluates students’ free-text answers given a set of correct ones. This paper presents an extension of the system in order to generate the students’ concept maps while they are being assessed. To that aim, a new module for the automatic identification of the terms of a particular knowledge field has been created. It identifies and keeps track of the terms that are being used in the students’ answers, and calculates a confidence score of the student's knowledge about each term. An empyrical evaluation using the students' real answers show that it is robust enough to generate a good set of terms from a very small set of answers.This work has been sponsored by Spanish Ministry of Science and Technology, project number TIN2004-0314

The impact of learning styles on student grouping for collaborative learning: a case study

The final publication is available at Springer via http://dx.doi.org/10.1007/s11257-006-9012-7Learning style models constitute a valuable tool for improving individual learning by the use of adaptation techniques based on them. In this paper, we present how the benefit of considering learning styles with adaptation purposes, as part of the user model, can be extended to the context of collaborative learning as a key feature for group formation. We explore the effects that the combination of students with different learning styles in specific groups may have in the final results of the tasks accomplished by them collaboratively. With this aim, a case study with 166 students of computer science has been carried out, from which conclusions are drawn. We also describe how an existing web-based system can take advantage of learning style information in order to form more productive groups. Our ongoing work concerning the automatic extraction of grouping rules starting from data about previous interactions within the system is also outlined. Finally, we present our challenges, related to the continuous improvement of collaboration by the use and dynamic modification of automatic grouping rules.This project has been funded by the Spanish Ministry of Science and Education, TIN2004-03140

Sobre los efectos de combinar Análisis Semántico Latente con otras técnicas de procesamiento de lenguaje natural para la evaluación de preguntas abiertas

Este artículo presenta la combinación de Análisis Semántico Latente (LSA) con otras técnicas de procesamiento del lenguaje natural (lematización, eliminación de palabras funcionales y desambiguación de sentidos) para mejorar la evaluación automática de respuestas en texto libre. El sistema de evaluación de respuestas en texto libre llamado Atenea (Alfonseca & Pérez, 2004) ha servido de marco experimental para probar el esquema combinacional. Atenea es un sistema capaz de realizar preguntas, escogidas aleatoriamente o bien conforme al perfil del estudiante, y asignarles una calificación numérica. Los resultados de los experimentos demuestran que para todos los conjuntos de datos en los que las técnicas de PLN se han combinado con LSA la correlación de Pearson entre las notas dadas por Atenea y las notas dadas por los profesores para el mismo conjunto de preguntas mejora. La causa puede encontrarse en la complementariedad entre LSA, que trabaja a un nivel semántico superficial, y el resto de las técnicas NLP usadas en Atenea, que están más centradas en los niveles léxico y sintáctico.This article presents the combination of Latent Semantic Analysis (LSA) with other natural language processing techniques (stemming, removal of closed-class words and word sense disambiguation) to improve the automatic assessment of students' free-text answers. The combinational schema has been tested in the experimental framework provided by the free-text Computer Assisted Assessment (CAA) system called Atenea (Alfonseca & Pérez, 2004). This system is able to ask randomly or according to the students' profile an open-ended question to the student and then, assign a score to it. The results prove that for all datasets, when the NLP techniques are combined with LSA, the Pearson correlation between the scores given by Atenea and the scores given by the teachers for the same dataset of questions improves. We believe that this is due to the complementarity between LSA, which works more at a shallow semantic level, and the rest of the NLP techniques used in Atenea, which are more focused on the lexical and syntactical levels

Automatic assessment of students’ free-text answers underpinned by the combination of a BLEU-inspired algorithm and latent semantic analysis

This is an electronic version of the paper presented at the International Florida Artificial Intelligence Research Society Conference, FLAIRS 2005In previous work we have proved that the BLEU algorithm (Papineni et al. 2001), originally devised for evaluating Machine Translation systems, can be applied to assessing short essays written by students. In this paper we present a comparative evaluation between this BLEU-inspired algorithm and a system based on Latent Semantic Analysis. In addition we propose an effective combination schema for them. Despite the simplicity of these shallow NLP methods, they achieve state-of-theart correlations to the teachers’ scores while keeping the language-independence and without requiring any domain specific knowledge.This work has been sponsored by the Spanish Ministry of Science and Technology, project number TIN2004-03140

Automatic generation of students' conceptual models underpinned by free-text adaptive computer assisted assessment

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. D. Perez-Marin, E. Alfonseca, M. Freire, and P. Rodriguez, “Automatic generation of students' conceptual models underpinned by free-text adaptive computer assisted assessment”, in Sixth International Conference on Advanced Learning Technologies, 2006, Kerkrade, 2006, pp. 280-284In this paper, we present an automatic procedure to generate students' knowledge conceptual models from their answers to an automatic free-text scoring system. The conceptual model is defined as a simplified representation of the concepts and relationships among them that each student keeps in his or her mind about an area of knowledge. It is considered that each area of knowledge comprises several topics and each topic several concepts. Each concept can be identified by a term that the students should use. A concept can belong to one topic or to several topics. The conceptual model is graphically displayed to the teachers as a conceptual map so that they can instantly see which concepts have already been assimilated and which ones should still be reviewed as they have been misunderstoodThis work has been sponsored by Spanish Ministry of Science and Technology,project number TIN2004-031

Willow: automatic and adaptative assessment of students' free-text answers

This work has been sponsored by Spanish Ministry of Science and Technology, project number TIN2004-0314