Giorgio Casadei

Adaptive intelligent hypermedia using XML

In this paper we discuss the problems of developing Web-based Adaptive Hypermedia (AH) for engineering education using Extensible Markup Language (XML). AH systems are capable of altering the presentation of the content of the hypermedia on the basis of a dynamic understanding of the individual user [5]. The user profile can be collected in a user model, while the knowledge about the domain (the content of the hypermedia) can be represented in the form of a concept-based domain model. So we have defined two different markup languages using XML: the former for structuring the domain model and the latter for describing the student model. These languages can be easily extended and authored, with the result of obtaining a simple methodology for data structuring in the field of Web-based educational AH.

Knowledge acquisition in intelligent tutoring system: a data mining approach

In the last years Intelligent Tutoring Systems have been a very successful way for improving learning experience. Many issues must be addressed until this technology can be defined mature. One of the main problems within the Intelligent Tutoring Systems is the process of contents authoring: knowledge acquisition and manipulation process is a difficult task because it requires specialized skills on computer programming and knowledge engineering. In this paper we propose a mechanism based on first order data mining to partially automate the process of knowledge acquisition. The knowledge has to be used in the ITS during the tutoring process for personalized instruction. Such a mechanism can be applied in Constraint Based Tutor and in the Pseudo-Cognitive Tutor.

An Item Response Theory Model for Student Ability Evaluation Using Computer-Automated Test Results

The aim of this paper is to evaluate the student learning about Computer Science subjects. A questionnaire based on ordinal scored items has been submitted to the students through a computer automated system. The data collected have been analyzed by using a latent variable model for ordinal data within the Item Response Theory framework. The scores obtained from the model allow to classify the students according to the reached competence.

Genetic Algorithms and Classifier Systems in simulating a Cooperative behavior

Genetic Algorithms and Classifier Systems are often used in biologic-like and evolutionary behaviors’ simulations. The basic example is Wood7 Wilson’s world. In this environment it is interesting to study some problems: Can evolve the cooperative behaviors of organisms present in the world? How and when do the behaviors evolve? Some preliminary results show the conditions under that cooperative behavior rules are developing rapidly. Particularly we have pointed out the likely of following observations: a. The cooperative behavior develops more easily if the initial population start from the same point. b. It exists some thresholds under that the cooperative behavior can’t evolve; these thresholds depend to the population size.

Classifier System in Traffic Management

The systems of controlling and improving traffic movement have been studied for several years now. The usefulness of these systems is that they can modify and change the lights signals of traffic lights. It is not enough to intervene when the situation has reached a critical point such as a traffic jam. The system has to work out how the traffic will flow. The ideal solution would be a system that works out and foresees the situation on the roads based on a model of motorists’ behaviour. This research shows how to best utilise the classifier systems so that it would be possible to create a model that is similar to that of the real world.

An Adaptive Assessment System to Evaluate Student Ability Level

The experience from years of development and use, the advance of technology, and the development of authoring tools for questions and tests has resulted in a sophisticated, computer based assessment system. However, there is still a lot of room for further development. Some of the current ideas for development are discussed in the remainder of this work. A primary aim of assessment, both formative and summative, is provide the necessary information to improve future educational experiences because it provides feedback on whether the course and learning objectives have been achieved to satisfactory level. Yet, it is important that the assessment data be accurate and relevant to effectively make informed decisions about the curriculum. Moreover, formative assessment can also be used to help bridge the gap between assessment and learning. This may be achieved particularly where assessment strategies are combined with useful feedback, and integrated within the learning process. The answers to the described objectives are enhanced if we could integrate adaptive testing techniques; accurate and fitted assessment data may improve both the curriculum and the student ability level. The idea behind a computerized adaptive testing (CAT) is quite forward: to apply to each examinee only those items useful to know his proficiency level. As a consequence of this, CAT is more efficient than conventional (i.e., fixeditem) tests. It provides more precise measurements for same-length tests or shorter tests for same-precision measurements.

Computer-Automated Testing: An Evaluation of Student Performance

In the last few years, the need for an automated way to assess people has increased quickly because of the growing request from both private and public structures. Many Learning Management Systems (LMS) have been developed in order to automatize the learning and assessment process. In most of the cases these systems don’t allow a quality content evaluation and an efficient ability estimation. In this paper we analyze the features of the Proportional Odd Model (POM), belonging to the Item Response Theory. The POM enables to translate an automatic test deliver in an efficient way in order to get an evaluation through either a summative or a formative way. The data have been collected in some undergraduate courses of Bologna University, by using test delivering and by authoring system developed in ASP and Java, respectively.

Problem Solving Olympics: An Inclusive Education Model for Learning Informatics

The paper presents the Olimpiadi di Problem Solving, a mild and inclusive competition aimed to promote computational thinking and general problem-solving in Italian schools. We describe motivation, teaching strategies behind the initiative, as well as its structure, organization and give some sample of the problems proposed to students. We also present some data that show the broad participation of Italian schools to the initiative, and a preliminary analysis of the results obtained by the students in the last 5 editions, which suggests that the competition fosters deep learning of computational thinking knowledge and skills.