Interface-based Programming Assignments and Automatic Grading of Java Programs

AutoGrader is a framework developed at Miami University for the automatic grading of student programming assignments written in the Java programming language. AutoGrader leverages the abstract concept of interfaces, brought out by the Java interface language construct, in both the assignment and grading of programming assignments. The use of interfaces reinforces the role of procedural abstraction in ob ject-oriented programming and allows for a common API to all student code. This common API then enables automatic grading of program functionality. AutoGrader provides a simple instructor API and enables the automatic testing of student code through the Java language features of interfaces and reflection1 . AutoGrader also supports static code analysis using PMD [4] to detect possible bugs, dead code, suboptimal, and overcomplicated code. While AutoGrader is written in and only handles Java programs, this style of automated grading is adaptable to any language that supports (or can mimic) named interfaces and/or abstract functions and that also supports runtime reflection

Mathematics base for navigation mobile robot using reachability petri net

Navigation is the journey that brings the precision and accuracy especially for the trip from one place to many destinations. Traveling mobile robot will be challenged when there are plenty of travel options and obstacles; it is necessary for special methods to deal with this. Petri net modeling is one method that can be applied in this navigation. As a model network graph, Petri net can be seen as a model of superior visuals for their token moves that define the process dynamics of a system. Other models that have been provided, such as flow charts, block diagrams or network topology, are using the method of mathematical reachability. Meanwhile Petri net obtained the navigation as a result of marking the value. The final results of this research is that Petri net can be used to obtain mobile robot for navigation

Automated Feedback for 'Fill in the Gap' Programming Exercises

Timely feedback is a vital component in the learning process. It is especially important for beginner students in Information Technology since many have not yet formed an effective internal model of a computer that they can use to construct viable knowledge. Research has shown that learning efficiency is increased if immediate feedback is provided for students. Automatic analysis of student programs has the potential to provide immediate feedback for students and to assist teaching staff in the marking process. This paper describes a “fill in the gap” programming analysis framework which tests students’ solutions and gives feedback on their correctness, detects logic errors and provides hints on how to fix these errors. Currently, the framework is being used with the Environment for Learning to Programming (ELP) system at Queensland University of Technology (QUT); however, the framework can be integrated into any existing online learning environment or programming Integrated Development Environment (IDE

Semi Automated Partial Credit Grading of Programming Assignments

The grading of student programs is a time consuming process. As class sizes continue to grow, especially in entry level courses, manually grading student programs has become an even more daunting challenge. Increasing the difficulty of grading is the needs of graphical and interactive programs such as those used as part of the UNH Computer Science curriculum (and various textbooks). There are existing tools that support the grading of introductory programming assignments (TAME and Web-CAT). There are also frameworks that can be used to test student code (JUnit, Tester, and TestNG). While these programs and frameworks are helpful, they have little or no no support for programs that use real data structures or that have interactive or graphical features. In addition, the automated tests in all these tools provide only “all or nothing” evaluation. This is a significant limitation in many circumstances. Moreover, there is little or no support for dynamic alteration of grading criteria, which means that refactoring of test classes after deployment is not easily done. Our goal is to create a framework that can address these weaknesses. This framework needs to: 1. Support assignments that have interactive and graphical components. 2. Handle data structures in student programs such as lists, stacks, trees, and hash tables. 3. Be able to assign partial credit automatically when the instructor can predict errors in advance. 4. Provide additional answer clustering information to help graders identify and assign consistent partial credit for incorrect output that was not predefined. Most importantly, these tools, collectively called RPM (short for Rapid Program Management), should interface effectively with our current grading support framework without requiring large amounts of rewriting or refactoring of test code

Programming assignments automatic grading: review of tools and implementations

Automatic grading of programming assignments is an important topic in academic research. It aims at improving the level of feedback given to students and optimizing the professor time. Several researches have reported the development of software tools to support this process. Then, it is helpfulto get a quickly and good sight about their key features. This paper reviews an ample set of tools forautomatic grading of programming assignments. They are divided in those most important mature tools, which have remarkable features; and those built recently, with new features. The review includes the definition and description of key features e.g. supported languages, used technology, infrastructure, etc. The two kinds of tools allow making a temporal comparative analysis. This analysis infrastructure, etc. The two kinds of tools allow making a temporal comparative analysis. This analysis shows good improvements in this research field, these include security, more language support, plagiarism detection, etc. On the other hand, the lack of a grading model for assignments is identified as an important gap in the reviewed tools. Thus, a characterization of evaluation metrics to grade programming assignments is provided as first step to get a model. Finally new paths in this research field are proposed

Automatic Image Marking Process

Abstract-Efficient evaluation of student programs and timely processing of feedback is a critical challenge for faculty. Despite persistent efforts and significant advances in this field, there is still room for improvement. Therefore, the present study aims to analyse the system of automatic assessment and marking of computer science programming students’ assignments in order to save teachers or lecturers time and effort. This is because the answers are marked automatically and the results returned within a very short period of time. The study develops a statistical framework to relate image keywords to image characteristics based on optical character recognition (OCR) and then provides analysis by comparing the students’ submitted answers with the optimal results. This method is based on Latent Semantic Analysis (LSA), and the experimental results achieve high efficiency and more accuracy by using such a simple yet effective technique in automatic marking

Architecture to Support Automatic Grading Processes in Programming Teaching

La calificación automática de tareas de programación es un tema importante dentro del campo de la innovación educativa que se enfoca en mejorar las habilidades de programación de los estudiantes y en optimizar el tiempo que el profesorado dedica a ello. Uno de los principales problemas vigentes está relacionado con la diversidad de criterios para calificar las tareas de programación. El presente trabajo propone e implementa una arquitectura, basada en el concepto de orquestación de servicios, para soportar varios procesos de calificación automática de tareas de programación. Esto es obtenido a través de las características de modularidad, extensibilidad y flexibilidad que la arquitectura provee al proceso de calificación. La arquitectura define como pieza clave un elemento llamado Grading-submodule, el mismo que provee un servicio de evaluación del código fuente considerando un criterio de calificación. La implementación se ha llevado a cabo sobre la herramienta Virtual Programming Lab; y los resultados demuestran la factibilidad de realización, y la utilidad tanto para el profesorado como para los estudiantes. ---------- ABSTRACT---------- Automatic grading of programming assignments is an important topic in academic research. It aims at improving students’ programming skills and optimizing the time of teaching staff. One important gap is related to the diversity of criteria to grade programming assignments. This work proposes and implements an architecture, based on the services orchestration concept, to support many kinds of grading process of programming assignments. It is achieved due architecture’s features including modularity, extensibility, and flexibility. The cornerstone of the architecture is a new software component named Grading-submodule, which provides of an evaluation service for the source code considering a grading criterion. The implementation has been done on Virtual Programming Lab. Results show workability, and uselfulness for teaching staff and students

Automatic Evaluation of Python and C Programs with codecheck

This project enhances the codecheck autograder by implementing automatic evaluation of C and Python programs. Two security approaches are implemented and analyzed in order to complete this goal. The first approach involves isolation by using virtualization and the second approach involves hardening of the host operating system. I describe both implementations and measure their performance levels to see which approach is more efficient

Java Auto Grader

The project is developing a “Java Automatic Grader” for java project assignment. It ensures that every assignment or work given to the students is done in the right way. Students should get automatic evaluation after submitting the assignment. We are implementing each test case in such a way that student should only get marks for satisfying all the requirements of the project assignment