6,131 research outputs found

    Do Enhanced Compiler Error Messages Help Students? Results Inconclusive.

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    One common frustration students face when first learning to program in a compiled language is the difficulty in interpreting the compiler error messages they receive. Attempts to improve error messages have produced differing results. Two recently published papers showed conflicting results, with one showing measurable change in student behavior, and the other showing no measurable change. We conducted an experiment comparable to these two over the course of several semesters in a CS1 course. This paper presents our results in the context of previous work in this area. We improved the clarity of the compiler error messages the students receive, so that they may more readily understand their mistakes and be able to make effective corrections. Our goal was to help students better understand their syntax mistakes and, as a reasonable measure of our success, we expected to document a decrease in the number of times students made consecutive submissions with the same compilation error. By doing this, we could demonstrate that this enhancement is effective. After collecting and thoroughly analyzing our own experimental data, we found that—despite anecdotal stories, student survey responses, and instructor opinions testifying to the tool’s helpfulness— enhancing compiler error messages shows no measurable benefit to students. Our results validate one of the existing studies and contradict another. We discuss some of the reasons for these results and conclude with projections for future research

    Introductory programming: a systematic literature review

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    As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

    On Novices\u27 Interaction with Compiler Error Messages: A Human Factors Approach

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    The difficulty in understanding compiler error messages can be a major impediment to novice student learning. To alleviate this issue, multiple researchers have run experiments enhancing compiler error messages in automated assessment tools for programming assignments. The conclusions reached by these published experiments appear to be conflicting. We examine these experiments and propose five potential reasons for the inconsistent conclusions concerning enhanced compiler error messages: (1) students do not read them, (2) researchers are measuring the wrong thing, (3) the effects are hard to measure, (4) the messages are not properly designed, (5) the messages are properly designed, but students do not understand them in context due to increased cognitive load. We constructed mixed-methods experiments designed to address reasons 1 and 5 with a specific automated assessment tool, Athene, that previously reported inconclusive results. Testing student comprehension of the enhanced compiler error messages outside the context of an automated assessment tool demonstrated their effectiveness over standard compiler error messages. Quantitative results from a 60 minute one-on-one think-aloud study with 31 students did not show substantial increase in student learning outcomes over the control. However, qualitative results from the one-on-one thinkaloud study indicated that most students are reading the enhanced compiler error messages and generally make effective changes after encountering them

    Beyond Automated Assessment: Building Metacognitive Awareness in Novice Programmers in CS1

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    The primary task of learning to program in introductory computer science courses (CS1) cognitively overloads novices and must be better supported. Several recent studies have attempted to address this problem by understanding the role of metacognitive awareness in novices learning programming. These studies have focused on teaching metacognitive awareness to students by helping them understand the six stages of learning so students can know where they are in the problem-solving process, but these approaches are not scalable. One way to address scalability is to implement features in an automated assessment tool (AAT) that build metacognitive awareness in novice programmers. Currently, AATs that provide feedback messages to students can be said to implement the fifth and sixth learning stages integral to metacognitive awareness: implement solution (compilation) and evaluate implemented solution (test cases). The computer science education (CSed) community is actively engaged in research on the efficacy of compile error messages (CEMs) and how best to enhance them to maximize student learning and it is currently heavily disputed whether or not enhanced compile error messages (ECEMs) in AATs actually improve student learning. The discussion on the effectiveness of ECEMs in AATs remains focused on only one learning stage critical to metacognitive awareness in novices: implement solution. This research carries out an ethnomethodologically-informed study of CS1 students via think-aloud studies and interviews in order to propose a framework for designing an AAT that builds metacognitive awareness by supporting novices through all six stages of learning. The results of this study provide two important contributions. The first is the confirmation that ECEMs that are designed from a human-factors approach are more helpful for students than standard compiler error messages. The second important contribution is that the results from the observations and post-assessment interviews revealed the difficulties novice programmers often face to developing metacognitive awareness when using an AAT. Understanding these barriers revealed concrete ways to help novice programmers through all six stages of the problem-solving process. This was presented above as a framework of features, which when implemented properly, provides a scalable way to implicitly produce metacognitive awareness in novice programmers

    Effective Compiler Error Message Enhancement for Novice Programming Students

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    Programming is an essential skill that all computing students must master. However programming can be difficult to learn. Compiler error messages are crucial for correcting errors, but are often difficult to understand and pose a barrier to progress for many novices. High frequencies of errors, particularly repeated errors, have been shown to be indicators of students who are struggling with learning to program. This study involves a custom IDE that enhances Java compiler error messages, intended to be more useful to novices than those supplied by the compiler. The effectiveness of this approach was tested in an empirical control/intervention study of approximately 200 students generating almost 50,000 errors. The design allows for direct comparisons between enhanced and non-enhanced error messages. Results show that the intervention group experienced reductions in the number of overall errors, errors per student, and several repeated error metrics. This work is important for two reasons. First, the effects of error message enhancement have been recently debated in the literature. This study provides substantial evidence that it can be effective. Second, these results should be generalizable at least in part, to other programming languages, students and institutions, as we show that the control group of this study is comparable to several others using Java and other languages

    Understanding and Addressing Misconceptions in Introductory Programming: A Data-Driven Approach

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    With the expansion of computer science (CS) education, CS teachers in K-12 schools should be cognizant of student misconceptions and be prepared to help students establish accurate understanding of computer science and programming. This exploratory design-based research (DBR) study implemented a data-driven approach to identify secondary school students’ misconceptions using both their compilation and test errors and provide targeted feedback to promote students’ conceptual change in introductory programming. Research subjects were two groups of high school students enrolled in two sections of a Java-based programming course in a 2017 summer residential program for gifted and talented students. This study consisted of two stages. In the first stage, students of group 1 took the introductory programming class and used an automated learning system, Mulberry, which collected data on student problem-solving attempts. Data analysis was conducted to identify common programming errors students demonstrated in their programs and relevant misconceptions. In the second stage, targeted feedback to address these misconceptions was designed using principles from conceptual change and feedback theories and added to Mulberry. When students of group 2 took the same introductory programming class and solved programming problems in Mulberry, they received the targeted feedback to address their misconceptions. Data analysis was conducted to assess how the feedback affected the evolution of students’ (mis)conceptions. Using students’ erroneous solutions, 55 distinct compilation errors were identified, and 15 of them were categorized as common ones. The 15 common compilation errors accounted for 92% of all compilation errors. Based on the 15 common compilation errors, three underlying student misconceptions were identified, including deficient knowledge of fundamental Java program structure, misunderstandings of Java expressions, and confusion about Java variables. In addition, 10 common test errors were identified based on nine difficult problems. The results showed that 54% of all test errors were related to the difficult problems, and the 10 common test errors accounted for 39% of all test errors of the difficult problems. Four common student misconceptions were identified based on the 10 common test errors, including misunderstandings of Java input, misunderstandings of Java output, confusion about Java operators, and forgetting to consider special cases. Both quantitative and qualitative data analysis were conducted to see whether and how the targeted feedback affected students’ solutions. Quantitative analysis indicated that targeted feedback messages enhanced students’ rates of improving erroneous solutions. Group 2 students showed significantly higher improvement rates in all erroneous solutions and solutions with common errors compared to group 1 students. Within group 2, solutions with targeted feedback messages resulted in significantly higher improvement rates compared to solutions without targeted feedback messages. Results suggest that with targeted feedback messages students were more likely to correct errors in their code. Qualitative analysis of students’ solutions of four selected cases determined that students of group 2, when improving their code, made fewer intermediate incorrect solutions than students in group 1. The targeted feedback messages appear to have helped to promote conceptual change. The results of this study suggest that a data-driven approach to understanding and addressing student misconceptions, which is using student data in automated assessment systems, has the potential to improve students’ learning of programming and may help teachers build better understanding of their students’ common misconceptions and develop their pedagogical content knowledge (PCK). The use of automated assessment systems with misconception identification components may be helpful in pre-college introductory programming courses and so is encouraged as K-12 CS education expands. Researchers and developers of automated assessment systems should develop components that support identifying common student misconceptions using both compilation and non-compilation errors. Future research should continue to investigate the use of targeted feedback in automated assessment systems to address students’ misconceptions and promote conceptual change in computer science education

    Performance evaluation and enhancement of Dendro

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    DENDRO is a collection of tools for solving Finite Element problems in parallel. This package is written in C++ using the standard template library (STL) and uses the Message Passing (MPI). Dendro uses an octree data-structure to solve image-registration problems using finite element techniques. For analyzing the behavior of the package in terms of speed-up and scalability, it is important to know which part of the package is consuming most of the execution-time. The single node performance and the overall performance of the package is dependent on the code-organization and class-hierarchy. We used the PETSC profiler to collect the performance statistics and instrument the code to know which part of the code takes most of the time. Along with the function-specific execution timings, PETSC profiler also provides the information regarding how many floating point operations is being performed in total and on average (FLOP/second). PETSC also provides information related to memory usage and number of MPI messages and reductions being performed to execute that particular function. We have analyzed these performance-statistics to provide some guidelines to how we can make Dendro more efficient by optimizing certain functions. We obtained around 12X speedup over the performance of (default) Dendro by using compiler-provided optimizations and achieved more than 65% speedup over compiler optimized performance (20X over the naive Dendro performance) by manually tuning some-block of code along with the compiler-optimizations

    A gentle transition from Java programming to Web Services using XML-RPC

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    Exposing students to leading edge vocational areas of relevance such as Web Services can be difficult. We show a lightweight approach by embedding a key component of Web Services within a Level 3 BSc module in Distributed Computing. We present a ready to use collection of lecture slides and student activities based on XML-RPC. In addition we show that this material addresses the central topics in the context of web services as identified by Draganova (2003)
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