14,084 research outputs found

    Learning Programming, Syntax Errors and Institution-specific Factors

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    Learning programming is a road that is paved with mistakes. Initially, novices are bound to write code with syntactic mistakes, but after a while semantic mistakes take a larger role in the novice programmers’ lives. Researchers who wish to understand that road are increasingly using data recorded from students’ programming processes. Such data can be used to draw inferences on the typical errors, and on how students approach fixing them. At the same time, if the lens that is used to analyze such data is used only from one angle, the view is likely to be narrow. In this work, we replicate a previous multi-institutional study by Brown et al. [5]. That study used a large scale programming process data repository to analyze mistakes that novices make while learning programming. In our single institution replication of that study, we use data collected from approximately 800 students. We investigate the frequency, time required to fix, and the development of mistakes through the semester. We contrast our findings from our single institution with the multi-institutional study, and show that whilst the data collection tools and the research methodology are the same, the results can differ solely due to how the course is conducted

    37 Million Compilations: Investigating Novice Programming Mistakes in Large-Scale Student Data

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    Previous investigations of student errors have typically focused on samples of hundreds of students at individual institutions. This work uses a year's worth of compilation events from over 250,000 students all over the world, taken from the large Blackbox data set. We analyze the frequency, time-to-fix, and spread of errors among users, showing how these factors inter-relate, in addition to their development over the course of the year. These results can inform the design of courses, textbooks and also tools to target the most frequent (or hardest to fix) errors

    TLAD 2010 Proceedings:8th international workshop on teaching, learning and assesment of databases (TLAD)

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    This is the eighth in the series of highly successful international workshops on the Teaching, Learning and Assessment of Databases (TLAD 2010), which once again is held as a workshop of BNCOD 2010 - the 27th International Information Systems Conference. TLAD 2010 is held on the 28th June at the beautiful Dudhope Castle at the Abertay University, just before BNCOD, and hopes to be just as successful as its predecessors.The teaching of databases is central to all Computing Science, Software Engineering, Information Systems and Information Technology courses, and this year, the workshop aims to continue the tradition of bringing together both database teachers and researchers, in order to share good learning, teaching and assessment practice and experience, and further the growing community amongst database academics. As well as attracting academics from the UK community, the workshop has also been successful in attracting academics from the wider international community, through serving on the programme committee, and attending and presenting papers.This year, the workshop includes an invited talk given by Richard Cooper (of the University of Glasgow) who will present a discussion and some results from the Database Disciplinary Commons which was held in the UK over the academic year. Due to the healthy number of high quality submissions this year, the workshop will also present seven peer reviewed papers, and six refereed poster papers. Of the seven presented papers, three will be presented as full papers and four as short papers. These papers and posters cover a number of themes, including: approaches to teaching databases, e.g. group centered and problem based learning; use of novel case studies, e.g. forensics and XML data; techniques and approaches for improving teaching and student learning processes; assessment techniques, e.g. peer review; methods for improving students abilities to develop database queries and develop E-R diagrams; and e-learning platforms for supporting teaching and learning

    TLAD 2010 Proceedings:8th international workshop on teaching, learning and assesment of databases (TLAD)

    Get PDF
    This is the eighth in the series of highly successful international workshops on the Teaching, Learning and Assessment of Databases (TLAD 2010), which once again is held as a workshop of BNCOD 2010 - the 27th International Information Systems Conference. TLAD 2010 is held on the 28th June at the beautiful Dudhope Castle at the Abertay University, just before BNCOD, and hopes to be just as successful as its predecessors.The teaching of databases is central to all Computing Science, Software Engineering, Information Systems and Information Technology courses, and this year, the workshop aims to continue the tradition of bringing together both database teachers and researchers, in order to share good learning, teaching and assessment practice and experience, and further the growing community amongst database academics. As well as attracting academics from the UK community, the workshop has also been successful in attracting academics from the wider international community, through serving on the programme committee, and attending and presenting papers.This year, the workshop includes an invited talk given by Richard Cooper (of the University of Glasgow) who will present a discussion and some results from the Database Disciplinary Commons which was held in the UK over the academic year. Due to the healthy number of high quality submissions this year, the workshop will also present seven peer reviewed papers, and six refereed poster papers. Of the seven presented papers, three will be presented as full papers and four as short papers. These papers and posters cover a number of themes, including: approaches to teaching databases, e.g. group centered and problem based learning; use of novel case studies, e.g. forensics and XML data; techniques and approaches for improving teaching and student learning processes; assessment techniques, e.g. peer review; methods for improving students abilities to develop database queries and develop E-R diagrams; and e-learning platforms for supporting teaching and learning

    Visual and Textual Programming Languages: A Systematic Review of the Literature

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    It is well documented, and has been the topic of much research, that Computer Science courses tend to have higher than average drop out rates at third level. This is a problem that needs to be addressed with urgency but also caution. The required number of Computer Science graduates is growing every year but the number of graduates is not meeting this demand and one way that this problem can be alleviated is to encourage students at an early age towards studying Computer Science courses. This paper presents a systematic literature review on the role of visual and textual programming languages when learning to program, particularly as a first programming language. The approach is systematic, in that a structured search of electronic resources has been conducted, and the results are presented and quantitatively analysed. This study will give insight into whether or not the current approaches to teaching young learners programming are viable, and examines what we can do to increase the interest and retention of these students as they progress through their education.Comment: 18 pages (including 2 bibliography pages), 3 figure

    MatLab vs. Python vs. R

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    Novice Java Programming Mistakes: Large-Scale Data vs. Educator Beliefs

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    Teaching is the process of conveying knowledge and skills to learners. It involves preventing misunderstandings or correcting misconceptions that learners have acquired. Thus, effective teaching relies on solid knowledge of the discipline, but also a good grasp of where learners are likely to trip up or misunderstand. In programming, there is much opportunity for misunderstanding, and the penalties are harsh: failing to produce the correct syntax for a program, for example, can completely prevent any progress in learning how to program. Because programming is inherently computer-based, we have an opportunity to automatically observe programming behaviour -- more closely even than an educator in the room at the time. By observing students' programming behaviour, and surveying educators, we can ask: do educators have an accurate understanding of the mistakes that students are likely to make? In this study, we combined two years of the Blackbox dataset (with more than 900 thousand users and almost 100 million compilation events) with a survey of 76 educators to investigate which mistakes students make while learning to program Java, and whether the educators could make an accurate estimate of which mistakes were most common. We find that educators' estimates do not agree with one another or the student data, and discuss the implications of these results

    Contemporary developments in teaching and learning introductory programming: Towards a research proposal

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    The teaching and learning of introductory programming in tertiary institutions is problematic. Failure rates are high and the inability of students to complete small programming tasks at the completion of introductory units is not unusual. The literature on teaching programming contains many examples of changes in teaching strategies and curricula that have been implemented in an effort to reduce failure rates. This paper analyses contemporary research into the area, and summarises developments in the teaching of introductory programming. It also focuses on areas for future research which will potentially lead to improvements in both the teaching and learning of introductory programming. A graphical representation of the issues from the literature that are covered in the document is provided in the introduction
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