In this paper we are reporting the finding on the use of a static analysis of C source code written by students learning to program. Two different tools for static code analysis were used to analyze the solutions subm...
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ISBN:
(纸本)9781509054671
In this paper we are reporting the finding on the use of a static analysis of C source code written by students learning to program. Two different tools for static code analysis were used to analyze the solutions submitted by the students on the partial exams and exams from the introductory course in programming in a three year period. We have collected, analyzed and compared most common errors reported by both tools. We further investigate if the available checks provided by these tools, often used in professional software development practices to find bugs and improve the code quality, can also help novice programmers in tracking down and resolving their problems in the code or have any other value in the process of learning programming.
University research workers need to use the computer as a tool. They are not computer professionals and it is not possible for them to effectively exploit computer facilities without advice and guidance. We argue that...
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University research workers need to use the computer as a tool. They are not computer professionals and it is not possible for them to effectively exploit computer facilities without advice and guidance. We argue that amongst the various sources of information available in a University, the official Advisory Service of a Computer Centre plays a crucial role in assisting users. Moreover, its relation to other sources of information makes it a valuable ground for studying the general problems of guiding non-professional computer users. Two groups of variables are isolated: those concerned with user expertise and those concerned with the quality of software. A gross measure of expertise is suggested and shown to generate behavioural questions which will need to be addressed by any theory of computing skill that is broad enough to apply to the design of computer guidance systems. An analysis is made of user queries and suggestions made for the improvement of applications software. A research programme is outlined.
Learning to program is difficult, a situation that is largely responsible for high attrition rates in Computer Science schools. Novice programmers struggle to grasp an early understanding of programming, which can lea...
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ISBN:
(纸本)9781920682767
Learning to program is difficult, a situation that is largely responsible for high attrition rates in Computer Science schools. Novice programmers struggle to grasp an early understanding of programming, which can lead to frustration and eventually surrender. The problem has generated interest in a range of enquiries, and has given impetus to the need for a teaching-research nexus towards a better understanding of novice programming problems. We continue the trend in this paper and report on a study we have conducted of novice programmers' efforts in summative assessment. Our study involves multiple-choice questions and coding question drawn from a programming examination. We analyse the answers provided by novices to final examination questions, and attempt to understand why students make such errors. We aim to categorise and classify the questions in the context of two well-known learning taxonomies: Bloom's Taxonomy and the SOLO Taxonomy.
Due to an increasing number of students, more and more learning institutions tend to use computer-supported learning tools like online learning platforms or intelligent tutoring systems. This has opened up the opportu...
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ISBN:
(纸本)9781467386340
Due to an increasing number of students, more and more learning institutions tend to use computer-supported learning tools like online learning platforms or intelligent tutoring systems. This has opened up the opportunity to collect a huge amount of students' data. Educational Data Mining (EDM) uses mining techniques to derive information from these data about students' knowledge, behavior and experience to improve education. In this paper, we present a framework for mining programming errors of computer science students by analyzing the students' solutions to a programming assignment. The framework serves as both, a computer aided assessment tool as well as an immediate feedback tool about the learning progress of the students for the educator.
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