Turning math attractive to computer science students: an application-to-model approach

This paper describes an innovative approach to develop the understanding about the relevance of mathematics to computer science. The mathematical subjects are introduced through an application-to-model scheme that lead computer science students to a better understanding of why they have to learn math and learn it effectively. Our approach consists of a single one semester course, taught at the first semester of the program, where the students are initially exposed to some typical computer applications. When they recognize the applications' complexity, the instructor gives the mathematical models supporting such applications, even before a formal introduction to the model in a math course. We applied this approach at Unesp (Brazil) and the results include a large reduction in the rate of students that abandon the college and better students in the final years of our program.

Principles versus artifacts in computer science curriculum design

Computer Science is a subject which has difficulty in marketing itself. Further, pinning down a standard curriculum is difficult-there are many preferences which are hard to accommodate. This paper argues the case that part of the problem is the fact that, unlike more established disciplines, the subject does not clearly distinguish the study of principles from the study of artifacts. This point was raised in Curriculum 2001 discussions, and debate needs to start in good time for the next curriculum standard. This paper provides a starting point for debate, by outlining a process by which principles and artifacts may be separated, and presents a sample curriculum to illustrate the possibilities. This sample curriculum has some positive points, though these positive points are incidental to the need to start debating the issue. Other models, with a less rigorous ordering of principles before artifacts, would still gain from making it clearer whether a specific concept was fundamental, or a property of a specific technology. (C) 2003 Elsevier Ltd. All rights reserved.

Programming Paradigms in Computer Science Education

Main styles, or paradigms of programming – imperative, functional, logic, and object-oriented – are shortly described and compared, and corresponding programming techniques are outlined. Programming languages are classified in accordance with the main style and techniques supported. It is argued that profound education in computer science should include learning base programming techniques of all main programming paradigms.

The Double Pareto-Lognormal Distribution and its applications in actuarial science and finance

Le but de ce mémoire de maîtrise est de décrire les propriétés de la loi double Pareto-lognormale, de montrer comment on peut introduire des variables explicatives dans le modèle et de présenter son large potentiel d'applications dans le domaine de la science actuarielle et de la finance. Tout d'abord, nous donnons la définition de la loi double Pareto-lognormale et présentons certaines de ses propriétés basées sur les travaux de Reed et Jorgensen (2004). Les paramètres peuvent être estimés en utilisant la méthode des moments ou le maximum de vraisemblance. Ensuite, nous ajoutons une variable explicative à notre modèle. La procédure d'estimation des paramètres de ce mo-\\dèle est également discutée. Troisièmement, des applications numériques de notre modèle sont illustrées et quelques tests statistiques utiles sont effectués.

A scaled-down conference model for courses covering ever-changing fields in computer science undergraduate degree programs

Resumen tomado de la publicación

Molecular quantum similarity in QSAR: applications in computer-aided molecular design

La present tesi està centrada en l'ús de la Teoria de Semblança Quàntica per a calcular descriptors moleculars. Aquests descriptors s'utilitzen com a paràmetres estructurals per a derivar correlacions entre l'estructura i la funció o activitat experimental per a un conjunt de compostos. Els estudis de Relacions Quantitatives Estructura-Activitat són d'especial interès per al disseny racional de molècules assistit per ordinador i, en particular, per al disseny de fàrmacs. Aquesta memòria consta de quatre parts diferenciades. En els dos primers blocs es revisen els fonaments de la teoria de semblança quàntica, així com l'aproximació topològica basada en la teoria de grafs. Ambdues teories es fan servir per a calcular els descriptors moleculars. En el segon bloc, s'ha de remarcar la programació i implementació de programari per a calcular els anomenats índexs topològics de semblança quàntica. La tercera secció detalla les bases de les Relacions Quantitatives Estructura-Activitat i, finalment, el darrer apartat recull els resultats d'aplicació obtinguts per a diferents sistemes biològics.

An Experience-Driven Pedagogy for the Instruction of Software Testing in Computer Science

In the realm of computer programming, the experience of writing a program is used to reinforce concepts and evaluate ability. This research uses three case studies to evaluate the introduction of testing through Kolb's Experiential Learning Model (ELM). We then analyze the impact of those testing experiences to determine methods for improving future courses. The first testing experience that students encounter are unit test reports in their early courses. This course demonstrates that automating and improving feedback can provide more ELM iterations. The JUnit Generation (JUG) tool also provided a positive experience for the instructor by reducing the overall workload. Later, undergraduate and graduate students have the opportunity to work together in a multi-role Human-Computer Interaction (HCI) course. The interactions use usability analysis techniques with graduate students as usability experts and undergraduate students as design engineers. Students get experience testing the user experience of their product prototypes using methods varying from heuristic analysis to user testing. From this course, we learned the importance of the instructors role in the ELM. As more roles were added to the HCI course, a desire arose to provide more complete, quality assured software. This inspired the addition of unit testing experiences to the course. However, we learned that significant preparations must be made to apply the ELM when students are resistant. The research presented through these courses was driven by the recognition of a need for testing in a Computer Science curriculum. Our understanding of the ELM suggests the need for student experience when being introduced to testing concepts. We learned that experiential learning, when appropriately implemented, can provide benefits to the Computer Science classroom. When examined together, these course-based research projects provided insight into building strong testing practices into a curriculum.

CompAS: A new approach to commonality and variability analysis with applications in computer assisted orthopaedic surgery

In rapidly evolving domains such as Computer Assisted Orthopaedic Surgery (CAOS) emphasis is often put first on innovation and new functionality, rather than in developing the common infrastructure needed to support integration and reuse of these innovations. In fact, developing such an infrastructure is often considered to be a high-risk venture given the volatility of such a domain. We present CompAS, a method that exploits the very evolution of innovations in the domain to carry out the necessary quantitative and qualitative commonality and variability analysis, especially in the case of scarce system documentation. We show how our technique applies to the CAOS domain by using conference proceedings as a key source of information about the evolution of features in CAOS systems over a period of several years. We detect and classify evolution patterns to determine functional commonality and variability. We also identify non-functional requirements to help capture domain variability. We have validated our approach by evaluating the degree to which representative test systems can be covered by the common and variable features produced by our analysis.

Advanced Protein Modeling Method: Benchmarking and Applications in Computer-Aided Drug Discovery

Development of homology modeling methods will remain an area of active research. These methods aim to develop and model increasingly accurate three-dimensional structures of yet uncrystallized therapeutically relevant proteins e.g. Class A G-Protein Coupled Receptors. Incorporating protein flexibility is one way to achieve this goal. Here, I will discuss the enhancement and validation of the ligand-steered modeling, originally developed by Dr. Claudio Cavasotto, via cross modeling of the newly crystallized GPCR structures. This method uses known ligands and known experimental information to optimize relevant protein binding sites by incorporating protein flexibility. The ligand-steered models were able to model, reasonably reproduce binding sites and the co-crystallized native ligand poses of the β2 adrenergic and Adenosine 2A receptors using a single template structure. They also performed better than the choice of template, and crude models in a small scale high-throughput docking experiments and compound selectivity studies. Next, the application of this method to develop high-quality homology models of Cannabinoid Receptor 2, an emerging non-psychotic pain management target, is discussed. These models were validated by their ability to rationalize structure activity relationship data of two, inverse agonist and agonist, series of compounds. The method was also applied to improve the virtual screening performance of the β2 adrenergic crystal structure by optimizing the binding site using β2 specific compounds. These results show the feasibility of optimizing only the pharmacologically relevant protein binding sites and applicability to structure-based drug design projects.

Teamwork competence and academic motivation in computer science engineering studies.

The present work is focused on studying two issues: the “teamwork” generic competence and the “academic motivation”. Currently the professional profile of engineers has a strong component of teamwork. On the other hand, motivational profile of students determines their tendencies when they come to work in team, as well as their performance at work. In this context we suggest four hypotheses: (H1) students improve their teamwork capacity by specific training and carrying out a set of activities integrated into an active learning process; (H2) students with higher mastery motivation have better attitude towards team working; (H3) students with higher mastery motivation obtain better results in academic performance; and (H4) students show different motivation profiles in different circumstances: type of courses, teaching methodologies, different times of the learning process. This study was carried out with computer science engineering students from two Spanish universities. The first results point to an improvement in teamwork competence of students if they have previously received specific training in facets of that competence. Other results indicate that there is a correlation between the motivational profiles of students and their perception about teamwork competence. Finally, and contrary to the initial hypothesis, these profiles appear to not influence significantly the academic performance of students.

Teamwork, motivational profiles and academic performance in computer science engineering

The present work is aimed at discussing several issues related to the teamwork generic competence, motivational profiles and academic performance. In particular, we study the improvement of teamwork attitude, the predominant types of motivation in different contexts and some correlations among these three components of the learning process. The above-mentioned aspects are of great importance. Currently, the professional profile of engineers has a strong teamwork component and the motivational profile of students determines both their tendencies when they come to work as part of a team, as well as their performance at work. Taking these issues into consideration, we suggest four hypotheses: (H1) students improve their teamwork capacity through specific training and carrying out of a set of activities integrated into an active learning process; (H2) students with higher mastery motivation have a better attitude towards teamwork; (H3) students with different types of motivations reach different levels of academic performance; and (H4) students show different motivation profiles in different circumstances: type of courses, teaching methodologies, different times of the learning process. This study was carried out with Computer Science Engineering students from two Spanish universities. The first results point to an improvement in teamwork competence of students if they have previously received specific training in facets of that competence. Other results indicate that there is a correlation between the motivational profiles of students and their perception of teamwork competence. Finally, results point to a clear relationship between some kind of motivation and academic performance. In particular, four kinds of motivation are analyzed and students are classified into two groups according to them. After analyzing several marks obtained in compulsory courses, we perceive that those students that show higher motivation for avoiding failure obtain, in general, worse academic performance.

The graduate program in computer science.

Bibliography: p. 7-9.