Human grading of introductory programming assignments is tedious and error-prone, hence researchers have attempted to develop tools that support automatic assessment of programming code. However, most such efforts oft...
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ISBN:
(纸本)9789868473577
Human grading of introductory programming assignments is tedious and error-prone, hence researchers have attempted to develop tools that support automatic assessment of programming code. However, most such efforts often focus only on scoring solutions, rather than assessing whether students correctly understand the problems. To aid the students improve programming skills, effective feedback on programming assignments plays an important role. Individual feedback generation is tedious and painstaking process. We present a tool that not only automatically generates the static and dynamic program analysis outcomes, but also clusters similar code submissions to provide scalable and effective feedback to the students. We studied our tool on data from introductory Java programming assignments of year 1 course in School of Information Systems. In this paper, we share the details of our tool and findings of our experiments on 261 code submissions.
The benefits of using assessment tools for programming assignments have been widely discussed in computing education. However, as both researchers and instructors are unaware of the characteristics of existing tools, ...
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ISBN:
(纸本)9781509007653
The benefits of using assessment tools for programming assignments have been widely discussed in computing education. However, as both researchers and instructors are unaware of the characteristics of existing tools, they are either not used or are reimplemented. This paper presents the results of a study conducted to collect and evaluate evidence about tools that assist in the assessment of programming assignments. To achieve our goal, we performed a systematic literature review since it provides an objective procedure for identifying the quantity of existing research related to a research question. The results identified subjects in the development of new assessment tools that researchers could better investigate and characteristics of assessment tools that could help instructors make selections for their programming courses.
In this study, an online compiler and a source code plagiarism detection tool have been included into the Moodle based distance education system of our Computer Engineering department. For this purpose Moodle system h...
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In this study, an online compiler and a source code plagiarism detection tool have been included into the Moodle based distance education system of our Computer Engineering department. For this purpose Moodle system has been extended with the GCC compiler, and the Moss source code plagiarism detection tool. We observed that using the online compiler and the plagiarism detection tool reduces time and effort needed for the assessment of the programming assignments;prevents our students from plagiarism;and increases their success in their programming based Data Structures course. (c) 2014 Wiley Periodicals, Inc. Comput Appl Eng Educ 23:363-373, 2015;View this article online at;DOI
The aim of the paper is to present observations on automatic and semi-automatic assessment for programming assignments used in different e-learning contexts. Teaching of programming is an important part of different I...
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The aim of the paper is to present observations on automatic and semi-automatic assessment for programming assignments used in different e-learning contexts. Teaching of programming is an important part of different Informatics Engineering, Computer Science or Informatics, Computing, Information Technology and Communication courses in Universities and high schools. Students taking these courses have to demonstrate competences in problem solving and programming by creating working programs. Checking program validity is usually based on testing a program on diverse test cases. Testing for batch-type problems involves creating a set of input data cases, running a program submitted by a contestant with those input cases, analysing obtained outputs, etc. Assessment of programming assignments is as complex as testing of software systems. A lot of automatic assessment systems for programming assignments have been created to support teachers in submission assessment. However the problem of balance between the quality and the speed of assessment for programming assignments is important. Authors conducted the research on the possibilities of advanced semi-automatic approach in assessment, which can be used as compromise between manual and automatic assessment. A semi-automatic testing environment for evaluating programming assignments is developed, and the practical use of this system in Lithuania's optional programming maturity examination is presented. Presented research is useful for evaluating results of engineering education in general, and informatics/computer engineering education particularly.
Automated assistance for detecting cheating on programs has long been investigated by CS educators, especially with the rise of "homework help" websites over the past decade, and recently with AI tools like ...
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ISBN:
(纸本)9798400704239
Automated assistance for detecting cheating on programs has long been investigated by CS educators, especially with the rise of "homework help" websites over the past decade, and recently with AI tools like ChatGPT. The main detection approach has long been flagging similar submission pairs. Modern cheating, like hiring contractors or using ChatGPT, may not yield such similarity. And, cases based on similarity alone may be weak. Thus, over the past several years, building on logs from an online program auto-grader (zyBooks), we developed additional "cheating concern metrics": points rate, style anomalies, style inconsistencies, IP address anomalies, code replacements, and initial copying. Most are defined not only for one programming assignment but also across a set of assignments. The metrics can help catch more kinds of cheating, provide more compelling evidence of cheating, reduce false cheating accusations based on similarity alone, and help instructors focus their limited cheat-detection time on the most egregious cases. We describe the techniques, and our experiences (via our own Python scripts and a commercial tool) for several terms, showing benefits of having more metrics than just similarity. Of 30 cheating cases over 3 terms and 300 students, most were based on metrics beyond similarity, all students admitted, none later contested, and time per student was only 1-2 hours (far less than previously). Our goal is to prevent cheating in the first place, by reducing opportunity via strong detection tools, as part of a multi-faceted approach to having students truly learn and stay out of trouble.
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To addres...
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The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading, timely feedback, and personalized support, enhancing the education process. This paper aims to develop "GRAD-AI," an automated grading tool for computer programming assignments. The objective is to overcome the limitations of manual grading by harnessing AI's capabilities to deliver accurate and timely assessments, thus creating a more interactive and supportive learning environment. The results show that GRAD-AI provides unbiased grading and timely and accurate feedback delivery for programming assignments by using the Halstead Complexity Measure, Term Frequency - Inverse Document Frequency Measure, Abstract Syntax Tree Process, and K-means Clustering. GRAD-AI marks a substantial stride in improving grading and feedback delivery within the education sector. Its real-time feedback provision and gap identification contribute to enhanced learning outcomes. As AI's role expands, integrating automated grading tools like GRAD-AI becomes crucial for fostering personalized learning and adaptability. The paper underscores AI's potential to revolutionize assessment and grading processes, supporting global students' growth and development.
Existing online judge systems for automatically evaluating programming exercises mainly rely on standard input and output streams without considering small pieces of code such as functions, methods or classes. This ap...
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ISBN:
(纸本)9798350338317
Existing online judge systems for automatically evaluating programming exercises mainly rely on standard input and output streams without considering small pieces of code such as functions, methods or classes. This approach qualifies for short programming exercises in which input and outputs are clearly indicated. However, these kinds of judges are hard to apply in long programming exercises. This article presents a novel online judge system called UnitJudge designed for evaluating long programming practices based on unit testing for small pieces of the practice. In the experiments on two long practices about the game of the Goose in Fundamentals of programming subject the first year of the Double Grade of Computer Science and Mathematics and the Grade of Data Engineer and Artificial Intelligence in Complutense University of Madrid, students perceived UnitJudge useful (5.62 out of 7) and easy to learn (5.99 out of 7) according to the Usefulness, Satisfaction and Ease of use validated scale.
Plagiarism in programming assignments is a common and current challenge. However, insufficient studies have examined plagiarism in the Middle East region. Thus, this research surveyed 422 students from a middle easter...
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Plagiarism in programming assignments is a common and current challenge. However, insufficient studies have examined plagiarism in the Middle East region. Thus, this research surveyed 422 students from a middle eastern university. It primarily purported to assess the students' perception of plagiarism in writing programming assignments. Additionally, this study reported the changes in students' perceptions of plagiarism in programming assignments between 2018 and 2021, the extent of this dishonest behaviour, and the demographical factors that influence it. A comparative analysis of the data from the 2017-2018 and 2020-2021 surveys of students specialising in Information Technology-related programmes found that those in the latter survey considered plagiarism less acceptable. In addition, the female students and those with a Cumulative Grade Point Average (CGPA) higher than or equal to three also considered cheating and plagiarism behaviours in programming assignments to be less acceptable. Furthermore, these findings did not report a substantial perception variance related to student class standing or specialisation.
BRIDGES is a software framework for creating engaging assignments for required courses such as data structures and algorithms. It provides students with a simplified API that populates their own data structure impleme...
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BRIDGES is a software framework for creating engaging assignments for required courses such as data structures and algorithms. It provides students with a simplified API that populates their own data structure implementations with live and real-world data, and provides the ability for students to easily visualize the data structures they create as part of routine classroom exercises. The objective is to use the infrastructure to promote a better understanding of the data structure and its underlying algorithms. This report describes the BRIDGES infrastructure and provides evaluation data collected over the first five years of the project. In the first 2 years, as we were developing the BRIDGES projects, our focus was on gathering data to assess whether the addition of the BRIDGES exercises had an effect on student retention of core concepts in data structures;and throughout the 5-year duration of the project, student interest and faculty feedback were collected online and anonymously. A mixed method design was used to evaluate the project impact. A quasiexperimental design compared student cohorts who were enrolled in comparable course sections that used BRIDGES with those that did not. Qualitative and quantitative measures were developed and used together with course grades and grade point averages. Interest and relevance in BRIDGES programming assignments was assessed with additional survey data from students and instructors. Results showed that students involved in BRIDGES projects demonstrated larger gains in knowledge of data structures compared to students enrolled in comparable course sections, as well as long-term benefits in their performance in four follow-on required courses. Survey responses indicated that some investment of time was needed to use BRIDGES, but the extra efforts were associated with several notable outcomes. Students and instructors had positive perceptions of the value of engaging in BRIDGES projects. BRIDGES can become a tool to get stu
In this paper, we present a novel approach of automated evaluation of programming assignments (AEPA) the highlight of which is that it automatically identifies multiple solution approaches to the programming question ...
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ISBN:
(纸本)9781450381048
In this paper, we present a novel approach of automated evaluation of programming assignments (AEPA) the highlight of which is that it automatically identifies multiple solution approaches to the programming question from the set of submitted solutions. Our approach does not require the instructor to foresee all the possible solution approaches and accomplishes this task with little or no human intervention. This paves the way to multiple fundamental improvements in the way automated evaluation of programming assignments is done today. We have applied our method on multiple data sets of practical scale. In all cases, our method was able to detect the solution approaches employed by the students.
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