Enabling constructive alignment in programming instruction

In this thesis, simple methods have been sought to lower the teacher’s threshold to start to apply constructive alignment in instruction. From the phases of the instructional process, aspects that can be improved with little effort by the teacher have been identified. Teachers have been interviewed in order to find out what students actually learn in computer science courses. A quantitative analysis of the structured interviews showed that in addition to subject specific skills and knowledge, students learn many other skills that should be mentioned in the learning outcomes of the course. The students’ background, such as their prior knowledge, learning style and culture, affects how they learn in a course. A survey was conducted to map the learning styles of computer science students and to see if their cultural background affected their learning style. A statistical analysis of the data indicated that computer science students are different learners than engineering students in general and that there is a connection between the student’s culture and learning style. In this thesis, a simple self-assessment scale that is based on Bloom’s revised taxonomy has been developed. A statistical analysis of the test results indicates that in general the scale is quite reliable, but single students still slightly overestimate or under-estimate their knowledge levels. For students, being able to follow their own progress is motivating, and for a teacher, self-assessment results give information about how the class is proceeding and what the level of the students’ knowledge is.

Rough Notes on Programming AVR Microcontrollers in C

These notes follow on from the material that you studied in CSSE1000 Introduction to Computer Systems. There you studied details of logic gates, binary numbers and instruction set architectures using the Atmel AVR microcontroller family as an example. In your present course (METR2800 Team Project I), you need to get on to designing and building an application which will include such a microcontroller. These notes focus on programming an AVR microcontroller in C and provide a number of example programs to illustrate the use of some of the AVR peripheral devices.

A parallel programming model for ada

Over the last three decades, computer architects have been able to achieve an increase in performance for single processors by, e.g., increasing clock speed, introducing cache memories and using instruction level parallelism. However, because of power consumption and heat dissipation constraints, this trend is going to cease. In recent times, hardware engineers have instead moved to new chip architectures with multiple processor cores on a single chip. With multi-core processors, applications can complete more total work than with one core alone. To take advantage of multi-core processors, parallel programming models are proposed as promising solutions for more effectively using multi-core processors. This paper discusses some of the existent models and frameworks for parallel programming, leading to outline a draft parallel programming model for Ada.

A teaching/learning support tool for introductory programming courses

In This work we present a Web-based tool developed with the aim of reinforcing teaching and learning of introductory programming courses. This tool provides support for teaching and learning. From the teacher's perspective the system introduces important gains with respect to the classical teaching methodology. It reinforces lecture and laboratory sessions, makes it possible to give personalized attention to the student, assesses the degree of participation of the students and most importantly, performs a continuous assessment of the student's progress. From the student's perspective it provides a learning framework, consisting in a help environment and a correction environment, which facilitates their personal work. With this tool students are more motivated to do programming

Combining Generic Programming and Service-Oriented Architectures for the Effective and Timely Development of Complex e-Learning Systems

Peer-reviewed

Teaching mathematics and programming : new approaches with empirical evaluation

Programming and mathematics are core areas of computer science (CS) and consequently also important parts of CS education. Introductory instruction in these two topics is, however, not without problems. Studies show that CS students find programming difficult to learn and that teaching mathematical topics to CS novices is challenging. One reason for the latter is the disconnection between mathematics and programming found in many CS curricula, which results in students not seeing the relevance of the subject for their studies. In addition, reports indicate that students' mathematical capability and maturity levels are dropping. The challenges faced when teaching mathematics and programming at CS departments can also be traced back to gaps in students' prior education. In Finland the high school curriculum does not include CS as a subject; instead, focus is on learning to use the computer and its applications as tools. Similarly, many of the mathematics courses emphasize application of formulas, while logic, formalisms and proofs, which are important in CS, are avoided. Consequently, high school graduates are not well prepared for studies in CS. Motivated by these challenges, the goal of the present work is to describe new approaches to teaching mathematics and programming aimed at addressing these issues: Structured derivations is a logic-based approach to teaching mathematics, where formalisms and justifications are made explicit. The aim is to help students become better at communicating their reasoning using mathematical language and logical notation at the same time as they become more confident with formalisms. The Python programming language was originally designed with education in mind, and has a simple syntax compared to many other popular languages. The aim of using it in instruction is to address algorithms and their implementation in a way that allows focus to be put on learning algorithmic thinking and programming instead of on learning a complex syntax. Invariant based programming is a diagrammatic approach to developing programs that are correct by construction. The approach is based on elementary propositional and predicate logic, and makes explicit the underlying mathematical foundations of programming. The aim is also to show how mathematics in general, and logic in particular, can be used to create better programs.

The impact of integrated programming on student attitude and achievement in grade 9 academic mathematics and science

This research studioo the effect of integrated instruction in mathematics and~ science on student achievement in and attitude towards both mathematics and science. A group of grade 9 academic students received instruction in both science and mathematics in an integrated program specifically developed for the purposes of the research. This group was compared to a control group that had received science and mathematics instruction in a traditional, nonintegrated program. The findings showed that in all measures of attitude, there was no significant difference between the students who participated in the integrated science and mathematics program and those who participated in a traditional science and mathematics program. The findings also revealed that integration did improve achievement on some of the measures used. The performance on mathematics open-ended problem-solving tasks improved after participation in the integrated program, suggesting that the integrated students were better able to apply their understanding of mathematics in a real-life context. The performance on the final science exam was also improved for the integrated group. Improvement was not noted on the other measures, which included EQAO scores and laboratory practical tasks. These results raise the issue of the suitability of the instruments used to gauge both achievement and attitude. The accuracy and suitability of traditional measures of achievement are considered. It is argued that they should not necessarily be used as the measure of the value of integrated instruction in a science and mathematics classroom.

Evolving Distributed Algorithms with Genetic Programming

Distributed systems are one of the most vital components of the economy. The most prominent example is probably the internet, a constituent element of our knowledge society. During the recent years, the number of novel network types has steadily increased. Amongst others, sensor networks, distributed systems composed of tiny computational devices with scarce resources, have emerged. The further development and heterogeneous connection of such systems imposes new requirements on the software development process. Mobile and wireless networks, for instance, have to organize themselves autonomously and must be able to react to changes in the environment and to failing nodes alike. Researching new approaches for the design of distributed algorithms may lead to methods with which these requirements can be met efficiently. In this thesis, one such method is developed, tested, and discussed in respect of its practical utility. Our new design approach for distributed algorithms is based on Genetic Programming, a member of the family of evolutionary algorithms. Evolutionary algorithms are metaheuristic optimization methods which copy principles from natural evolution. They use a population of solution candidates which they try to refine step by step in order to attain optimal values for predefined objective functions. The synthesis of an algorithm with our approach starts with an analysis step in which the wanted global behavior of the distributed system is specified. From this specification, objective functions are derived which steer a Genetic Programming process where the solution candidates are distributed programs. The objective functions rate how close these programs approximate the goal behavior in multiple randomized network simulations. The evolutionary process step by step selects the most promising solution candidates and modifies and combines them with mutation and crossover operators. This way, a description of the global behavior of a distributed system is translated automatically to programs which, if executed locally on the nodes of the system, exhibit this behavior. In our work, we test six different ways for representing distributed programs, comprising adaptations and extensions of well-known Genetic Programming methods (SGP, eSGP, and LGP), one bio-inspired approach (Fraglets), and two new program representations called Rule-based Genetic Programming (RBGP, eRBGP) designed by us. We breed programs in these representations for three well-known example problems in distributed systems: election algorithms, the distributed mutual exclusion at a critical section, and the distributed computation of the greatest common divisor of a set of numbers. Synthesizing distributed programs the evolutionary way does not necessarily lead to the envisaged results. In a detailed analysis, we discuss the problematic features which make this form of Genetic Programming particularly hard. The two Rule-based Genetic Programming approaches have been developed especially in order to mitigate these difficulties. In our experiments, at least one of them (eRBGP) turned out to be a very efficient approach and in most cases, was superior to the other representations.

A teaching/learning support tool for introductory programming courses

In This work we present a Web-based tool developed with the aim of reinforcing teaching and learning of introductory programming courses. This tool provides support for teaching and learning. From the teacher's perspective the system introduces important gains with respect to the classical teaching methodology. It reinforces lecture and laboratory sessions, makes it possible to give personalized attention to the student, assesses the degree of participation of the students and most importantly, performs a continuous assessment of the student's progress. From the student's perspective it provides a learning framework, consisting in a help environment and a correction environment, which facilitates their personal work. With this tool students are more motivated to do programming

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.

The design, implementation, and analysis of a computer-assisted instruction system on a mini-computer,

Thesis (M.S.)--University of Illinois at Urbana-Champaign.

Planning, programming, budgeting, evaluating systems /

WI docs. no.: Ed.3/2:I 5/1979/7/4