324 resultados para Computer programming.


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This special issue of the Journal of Urban Technology brings together five articles that are based on presentations given at the Street Computing workshop held on 24 November 2009 in Melbourne in conjunction with the Australian Computer-Human Interaction conference (OZCHI 2009). Our own article introduces the Street Computing vision and explores the potential, challenges and foundations of this research vision. In order to do so, we first look at the currently available sources of information and discuss their link to existing research efforts. Section 2 then introduces the notion of Street Computing and our research approach in more detail. Section 3 looks beyond the core concept itself and summarises related work in this field of interest.

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Programming is a subject that many beginning students find difficult. This paper describes a knowledge base designed for the purpose of analyzing programs written in the PHP web development language. The aim is to use this knowledge base in an Intelligent Tutoring System that will provide effective feedback to students. The main focus of this research is that a programming exercise can have many correct solutions. This paper presents an overview of how the proposed knowledge base can be utilized to accept different solutions to a given exercise

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Student performance on examinations is influenced by the level of difficulty of the questions. It seems reasonable to propose therefore that assessment of the difficulty of exam questions could be used to gauge the level of skills and knowledge expected at the end of a course. This paper reports the results of a study investigating the difficulty of exam questions using a subjective assessment of difficulty and a purpose-built exam question complexity classification scheme. The scheme, devised for exams in introductory programming courses, assesses the complexity of each question using six measures: external domain references, explicitness, linguistic complexity, conceptual complexity, length of code involved in the question and/or answer, and intellectual complexity (Bloom level). We apply the scheme to 20 introductory programming exam papers from five countries, and find substantial variation across the exams for all measures. Most exams include a mix of questions of low, medium, and high difficulty, although seven of the 20 have no questions of high difficulty. All of the complexity measures correlate with assessment of difficulty, indicating that the difficulty of an exam question relates to each of these more specific measures. We discuss the implications of these findings for the development of measures to assess learning standards in programming courses.

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Recent research has proposed Neo-Piagetian theory as a useful way of describing the cognitive development of novice programmers. Neo-Piagetian theory may also be a useful way to classify materials used in learning and assessment. If Neo-Piagetian coding of learning resources is to be useful then it is important that practitioners can learn it and apply it reliably. We describe the design of an interactive web-based tutorial for Neo-Piagetian categorization of assessment tasks. We also report an evaluation of the tutorial's effectiveness, in which twenty computer science educators participated. The average classification accuracy of the participants on each of the three Neo-Piagetian stages were 85%, 71% and 78%. Participants also rated their agreement with the expert classifications, and indicated high agreement (91%, 83% and 91% across the three Neo-Piagetian stages). Self-rated confidence in applying Neo-Piagetian theory to classifying programming questions before and after the tutorial were 29% and 75% respectively. Our key contribution is the demonstration of the feasibility of the Neo-Piagetian approach to classifying assessment materials, by demonstrating that it is learnable and can be applied reliably by a group of educators. Our tutorial is freely available as a community resource.

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This paper considers the problem of reconstructing the motion of a 3D articulated tree from 2D point correspondences subject to some temporal prior. Hitherto, smooth motion has been encouraged using a trajectory basis, yielding a hard combinatorial problem with time complexity growing exponentially in the number of frames. Branch and bound strategies have previously attempted to curb this complexity whilst maintaining global optimality. However, they provide no guarantee of being more efficient than exhaustive search. Inspired by recent work which reconstructs general trajectories using compact high-pass filters, we develop a dynamic programming approach which scales linearly in the number of frames, leveraging the intrinsically local nature of filter interactions. Extension to affine projection enables reconstruction without estimating cameras.

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Computer games have become a commonplace but engaging activity among students. They enjoy playing computer games as they can perform larger-than-life activities virtually such as jumping from great heights, flying planes, and racing cars; actions that are otherwise not possible in real life. Computer games also offer user interactivity which gives them a certain appeal. Considering this appeal, educators should consider integrating computer games into student learning and to encourage students to author computer games of their own. It is thought that students can be engaged in learning by authoring and using computer games and can also gain essential skills such as collaboration, teamwork, problem solving and deductive reasoning. The research in this study revolves around building student engagement through the task of authoring computer games. The study aims to demonstrate how the creation and sharing of student-authored educational games might facilitate student engagement and how ICT (information and communication technology) plays a supportive role in student learning. Results from this study may lead to the broader integration of computer games into student learning and contribute to similar studies. In this qualitative case study, based in a state school in a low socio-economic area west of Brisbane, Australia, students were selected in both junior and senior secondary classes who have authored computer games as a part of their ICT learning. Senior secondary students (Year 12 ICT) were given the task of programming the games, which were to be based on Mathematics learning topics while the junior secondary students (Year 8 ICT) were given the task of creating multimedia elements for the games. A Mathematics teacher volunteered to assist in the project and provided guidance on the inclusion of suitable Mathematics curricular content into these computer games. The student-authored computer games were then used to support another group of Year 8 Mathematics students to learn the topics of Area, Volume and Time. Data was collected through interviews, classroom observations and artefacts. The teacher researcher, acting in the role of ICT teacher, coordinated with the students and the Mathematics teacher to conduct this study. Instrumental case study was applied as research methodology and Third Generation Activity Theory served as theoretical framework for this study. Data was analysed adopting qualitative coding procedures. Findings of this study indicate that having students author and play computer games promoted student engagement and that ICT played a supportive role in learning and allowed students to gain certain essential skills. Although this study will suggest integrating computer games to support classroom learning, it cannot be presumed that computer games are an immediate solution for promoting student engagement.

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User interfaces for source code editing are a crucial component in any software development environment, and in many editors visual annotations (overlaid on the textual source code) are used to provide important contextual information to the programmer. This paper focuses on the real-time programming activity of ‘cyberphysical’ programming, and considers the type of visual annotations which may be helpful in this programming context.

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This special issue of the Journal of Urban Technology brings together five articles that are based on presentations given at the Street Computing Workshop held on 24 November 2009 in Melbourne in conjunction with the Australian Computer- Human Interaction conference (OZCHI 2009). Our own article introduces the Street Computing vision and explores the potential, challenges, and foundations of this research trajectory. In order to do so, we first look at the currently available sources of information and discuss their link to existing research efforts. Section 2 then introduces the notion of Street Computing and our research approach in more detail. Section 3 looks beyond the core concept itself and summarizes related work in this field of interest. We conclude by introducing the papers that have been contributed to this special issue.

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In this research paper, we study a simple programming problem that only requires knowledge of variables and assignment statements, and yet we found that some early novice programmers had difficulty solving the problem. We also present data from think aloud studies which demonstrate the nature of those difficulties. We interpret our data within a neo-Piagetian framework which describes cognitive developmental stages through which students pass as they learn to program. We describe in detail think aloud sessions with novices who reason at the neo-Piagetian preoperational level. Those students exhibit two problems. First, they focus on very small parts of the code and lose sight of the "big picture". Second, they are prone to focus on superficial aspects of the task that are not functionally central to the solution. It is not until the transition into the concrete operational stage that decentration of focus occurs, and they have the cognitive ability to reason about abstract quantities that are conserved, and are equipped to adapt skills to closely related tasks. Our results, and the neo-Piagetian framework on which they are based, suggest that changes are necessary in teaching practice to better support novices who have not reached the concrete operational stage.

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This paper presents a new method to determine feeder reconfiguration scheme considering variable load profile. The objective function consists of system losses, reliability costs and also switching costs. In order to achieve an optimal solution the proposed method compares these costs dynamically and determines when and how it is reasonable to have a switching operation. The proposed method divides a year into several equal time periods, then using particle swarm optimization (PSO), optimal candidate configurations for each period are obtained. System losses and customer interruption cost of each configuration during each period is also calculated. Then, considering switching cost from a configuration to another one, dynamic programming algorithm (DPA) is used to determine the annual reconfiguration scheme. Several test systems were used to validate the proposed method. The obtained results denote that to have an optimum solution it is necessary to compare operation costs dynamically.

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This tutorial is designed to help new users become familiar with using the Spartan-3E board. The tutorial steps through: writing a small program in VHDL which carries out simple combinational logic; connecting the program inputs and outputs to the switches, buttons and LEDs on the Spartan-3E board; downloading the program to the Spartan-3E board using version 14.7 of the Xilinx ISE; and simulating the program using the iSim Simulator.

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Fast restoration of critical loads and non-black-start generators can significantly reduce the economic losses caused by power system blackouts. In a parallel power system restoration scenario, the sectionalization of restoration subsystems plays a very important role in determining the pickup of critical loads before synchronization. Most existing research mainly focuses on the startup of non-black-start generators. The restoration of critical loads, especially the loads with cold load characteristics, has not yet been addressed in optimizing the subsystem divisions. As a result, sectionalized restoration subsystems cannot achieve the best coordination between the pickup of loads and the ramping of generators. In order to generate sectionalizing strategies considering the pickup of critical loads in parallel power system restoration scenarios, an optimization model considering power system constraints, the characteristics of the cold load pickup and the features of generator startup is proposed in this paper. A bi-level programming approach is employed to solve the proposed sectionalizing model. In the upper level the optimal sectionalizing problem for the restoration subsystems is addressed, while in the lower level the objective is to minimize the outage durations of critical loads. The proposed sectionalizing model has been validated by the New-England 39-bus system and the IEEE 118-bus system. Further comparisons with some existing methods are carried out as well.

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In this paper, we look at the concept of reversibility, that is, negating opposites, counterbalances, and actions that can be reversed. Piaget identified reversibility as an indicator of the ability to reason at a concrete operational level. We investigate to what degree novice programmers manifest the ability to work with this concept of reversibility by providing them with a small piece of code and then asking them to write code that undoes the effect of that code. On testing entire cohorts of students in their first year of learning to program, we found an overwhelming majority of them could not cope with such a concept. We then conducted think aloud studies of novices where we observed them working on this task and analyzed their contrasting abilities to deal with it. The results of this study demonstrate the need for better understanding our students' reasoning abilities, and a teaching model aimed at that level of reality.