Hint generation in programming tutors

Programming is increasingly recognized as a useful and important skill. Online programming courses that have appeared in the past decade have proven extremely popular with a wide audience. Learning in such courses is however not as effective as working directly with a teacher, who can provide students with immediate relevant feedback. The field of intelligent tutoring systems seeks to provide such feedback automatically. Traditionally, tutors have depended on a domain model defined by the teacher in advance. Creating such a model is a difficult task that requires a lot of knowledgeengineering effort, especially in complex domains such as programming. A potential solution to this problem is to use data-driven methods. The idea is to build the domain model by observing how students have solved an exercise in the past. New students can then be given feedback that directs them along successful solution paths. Implementing this approach is particularly challenging for programming domains, since the only directly observable student actions are not easily interpretable. We present two novel approaches to creating a domain model for programming exercises in a data-driven fashion. The first approach models programming as a sequence of textual rewrites, and learns rewrite rules for transforming programs. With these rules new student-submitted programs can be automatically debugged. The second approach uses structural patterns in programs’ abstract syntax trees to learn rules for classifying submissions as correct or incorrect. These rules can be used to find erroneous parts of an incorrect program. Both models support automatic hint generation. We have implemented an online application for learning programming and used it to evaluate both approaches. Results indicate that hints generated using either approach have a positive effect on student performance

Automatic portal generation based on XML workflow description

This dissertation investigates the automatic generation of computing portals based on XML workflow descriptions. To this end, a software system is designed, implemented and evaluated that allows end-users to build their own customized portal for managing and executing distributed scientific and engineering computations in a service-oriented environment. The whole process of the computation is represented as a data-driven workflow. The portal technique provides a user-friendly problem-solving environment that addresses job assignment, job submission and job feedback. An advantage of this approach is that the complexity of the workflow execution in the distributed environment is hidden from the user. However, the manual development and configuration of the application portal requires considerable expertise in web portal techniques, which most scientific end-users do not have. This dissertation address this problem by describing a tool chain consisting of three tools to achieve automatic portal generation and configuration. In addition, this dissertation presents a mapping of each element of WSDL to the UDDI data model, the conversion from the data-flow workflow to control-flow workflow by using XSLT, an implementation of a drag-and-drop visual programming environment for the generation of a workflow skeleton, and a methodology for the automatic layout of portlets in a portal framework.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Automatic portal generation based on XML workflow description

This dissertation investigates the automatic generation of computing portals based on XML workflow descriptions. To this end, a software system is designed, implemented and evaluated that allows end-users to build their own customized portal for managing and executing distributed scientific and engineering computations in a service-oriented environment. The whole process of the computation is represented as a data-driven workflow. The portal technique provides a user-friendly problem-solving environment that addresses job assignment, job submission and job feedback. An advantage of this approach is that the complexity of the workflow execution in the distributed environment is hidden from the user. However, the manual development and configuration of the application portal requires considerable expertise in web portal techniques, which most scientific end-users do not have. This dissertation address this problem by describing a tool chain consisting of three tools to achieve automatic portal generation and configuration. In addition, this dissertation presents a mapping of each element of WSDL to the UDDI data model, the conversion from the data-flow workflow to control-flow workflow by using XSLT, an implementation of a drag-and-drop visual programming environment for the generation of a workflow skeleton, and a methodology for the automatic layout of portlets in a portal framework

sk_p: a neural program corrector for MOOCs

We present a novel technique for automatic program correction in MOOCs, capable of fixing both syntactic and semantic errors without manual, problem specific correction strategies. Given an incorrect student program, it generates candidate programs from a distribution of likely corrections, and checks each candidate for correctness against a test suite. The key observation is that in MOOCs many programs share similar code fragments, and the seq2seq neural network model, used in the natural-language processing task of machine translation, can be modified and trained to recover these fragments. Experiment shows our scheme can correct 29% of all incorrect submissions and out-performs state of the art approach which requires manual, problem specific correction strategies