5 research outputs found
BlueFix : using crowd-sourced feedback to support programming students in error diagnosis and repair.
Feedback is regarded as one of the most important influences on student learning and motivation. But standard compiler feedback is designed for experts - not novice programming students, who can find it difficult to interpret and understand. In this paper we present BlueFix, an online tool currently integrated into the BlueJ IDE which is designed to assist programming students with error diagnosis and repair. Unlike existing approaches, BlueFix proposes a feedback algorithm based upon frameworks combined from the HCI and Pedagogical domains, which can provide different students with dynamic levels of support based upon their compilation behaviour. An evaluation revealed that students' viewed our tool positively and that our methodology could identify appropriate fixes for uncompilable source code with a significantly higher rate of speed and precision over related techniques in the literature
BlueFix: Using Crowd-sourced Feedback to Support Programming Students in Error Diagnosis and Repair
Feedback is regarded as one of the most important influences on student learning and motivation. But standard compiler feedback is designed for experts - not novice programming students, who can find it difficult to interpret and understand. In this paper we present BlueFix, an online tool currently integrated into the BlueJ IDE which is designed to assist programming students with error diagnosis and repair. Unlike existing approaches, BlueFix proposes a feedback algorithm based upon frameworks combined from the HCI and Pedagogical domains, which can provide different students with dynamic levels of support based upon their compilation behaviour. An evaluation revealed that students' viewed our tool positively and that our methodology could identify appropriate fixes for uncompilable source code with a significantly higher rate of speed and precision over related techniques in the literature
Practical, appropriate, empirically-validated guidelines for designing educational games
There has recently been a great deal of interest in the
potential of computer games to function as innovative
educational tools. However, there is very little evidence of
games fulfilling that potential. Indeed, the process of
merging the disparate goals of education and games design
appears problematic, and there are currently no practical
guidelines for how to do so in a coherent manner. In this
paper, we describe the successful, empirically validated
teaching methods developed by behavioural psychologists
and point out how they are uniquely suited to take
advantage of the benefits that games offer to education. We
conclude by proposing some practical steps for designing
educational games, based on the techniques of Applied
Behaviour Analysis. It is intended that this paper can both
focus educational games designers on the features of games
that are genuinely useful for education, and also introduce a
successful form of teaching that this audience may not yet
be familiar with
Supporting Source Code Search with Context-Aware and Semantics-Driven Query Reformulation
Software bugs and failures cost trillions of dollars every year, and could even lead to deadly accidents (e.g., Therac-25 accident). During maintenance, software developers fix numerous bugs and implement hundreds of new features by making necessary changes to the existing software code. Once an issue report (e.g., bug report, change request) is assigned to a developer, she chooses a few important keywords from the report as a search query, and then attempts to find out the exact locations in the software code that need to be either repaired or enhanced. As a part of this maintenance, developers also often select ad hoc queries on the fly, and attempt to locate the reusable code from the Internet that could assist them either in bug fixing or in feature implementation. Unfortunately, even the experienced developers often fail to construct the right search queries. Even if the developers come up with a few ad hoc queries, most of them require frequent modifications which cost significant development time and efforts. Thus, construction of an appropriate query for localizing the software bugs, programming concepts or even the reusable code is a major challenge. In this thesis, we overcome this query construction challenge with six studies, and develop a novel, effective code search solution (BugDoctor) that assists the developers in localizing the software code of interest (e.g., bugs, concepts and reusable code) during software maintenance. In particular, we reformulate a given search query (1) by designing novel keyword selection algorithms (e.g., CodeRank) that outperform the traditional alternatives (e.g., TF-IDF), (2) by leveraging the bug report quality paradigm and source document structures which were previously overlooked and (3) by exploiting the crowd knowledge and word semantics derived from Stack Overflow Q&A site, which were previously untapped. Our experiment using 5000+ search queries (bug reports, change requests, and ad hoc queries) suggests that our proposed approach can improve the given queries significantly through automated query reformulations. Comparison with 10+ existing studies on bug localization, concept location and Internet-scale code search suggests that our approach can outperform the state-of-the-art approaches with a significant margin