Mónica Trella

Introducing prerequisite relations in a multi-layered bayesian student model

In this paper we present an extension of a previously developed generic student model based on Bayesian Networks. A new layer has been added to the model to include prerequisite relationships. The need of this new layer is motivated from different points of view: in practice, this kind of relationships are very common in any educational setting, but also their use allows for improving efficiency of both adaptation mechanisms and the inference process. The new prerequisite layer has been evaluated using two different experiments: the first experiment uses a small toy example to show how the BN can emulate human reasoning in this context, while the second experiment with simulated students suggests that prerequisite relationships can improve the efficiency of the diagnosis process by allowing increased accuracy or reductions in the test length.

An Empirical Approach to On-Line Learning in SIETTE

SIETTE is a web-based evaluation tool that implements CAT theory. With the help of a simulation program, different empirical experiments have been performed with SIETTE with two different goals: a) to study the influence of the parameters of characteristic item curves and selection criteria in test length and accuracy; and b) to study different learning strategies for these parameters. The results of the experiments are shown and interpreted.

INGRID: a web service tool for hierarchical open learner model visualization

This paper presents a tool to visualize open learner models. The tool is domain independent and is freely available as a web service. It can be easily integrated with any existing web-based learning environment.

A Web-Based Socratic Tutor for Trees Recognition

Socratic dialogues has been widely uses as a way of implement an ITS. The idea behind it is that the teaching and learning process should be based upon a personal reflection that can be obtained posing the right question on a guided dialogue. This methodology assumes that the knowledge acquisition is a discovering process in which both the teacher and the student plays an active role. This tutorial strategy has been developed as a part of a web based ITS architecture for declarative domains and it has been applied to the botanical domain. In this paper we describe this component, the knowledge representation that support it and the web interface used.

Using Bayesian Networks in Computerized Adaptive Tests

In this paper we propose the use of Bayesian Networks as a theoretical framework for Computerized Adaptive Tests. To this end, we develop the Bayesian Network that supports the Adaptive Testing Algorithm, that is, we define what variables should be taken into account, what kind of relationships should be established among them, and what are the required parameters. As parameter specification is one of the most difficult problems when using Bayesian Networks, we suggest the use of several simplifications. By using such simplifications, the required conditional probabilities can be obtained in a relatively simple way.

The SIETTE Automatic Assessment Environment

This article describes the evolution and current state of the domain-independent Siette assessment environment. Siette supports different assessment methods—including classical test theory, item response theory, and computer adaptive testing—and integrates them with multidimensional student models used by intelligent educational systems. Teachers can use an authoring tool to create large item pools of different types of questions, including multiple choice, open answer, generative questions, and complex tasks. Siette can be used for formative and summative assessment and incorporates different learning elements, including scaffolding features, such as hints, feedback, and misconceptions. It includes numerous other features covering different educational needs and techniques, such as spaced repetition, collaborative testing, or pervasive learning. Siette is designed as a web-based assessment component that can be semantically integrated with intelligent systems or with large LMSs, such as Moodle. This article reviews the evolution of the Siette system, presents information on its use, and analyses this information from a broader and critical perspective on the use of intelligent systems in education.

BabelWin: An environment for learning and monitoring reading and writing skills

In this paper we describe the structure and behaviour of an interactive learning environment for reading and writing exercises. This environment lets the teachers configure and personalize the exercises from a set of templates. It also lets them analyse the pupils” results and delivers reports, substantially improving tracking the learning process. To develop this environment, the cognitive processes that form part of reading and writing skills have been taken into account, as well as other aspects such as easy user interfaces, graphical presentation, and visual reinforcement.

Primary Preschool Experiences with Computers in the Classroom

This paper presents some experiences of learning with computers in a preschool setting. The MEDEA framework (a Spanish acronym of Methodology and Tools for the Development of Intelligent Environments of Teaching and Learning) is used to define the activities and construct the user models. The result is an environment that has been installed in the classroom as a new resource and which has been used in conjunction with traditional learning tasks. The system has been successfully evaluated with children from different countries and cultures.