In programming exercise classes at universities, instructors must quickly determine the learner's situation and provide support. However, it is difficult to deal with learners making logic errors. This is because ...
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TEDViT is a program behavior visualization system that can reflect explanatory intentions of a teacher by visualizing it in a target world. This system can dynamically reflect changes in variables caused by program be...
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ISBN:
(纸本)9789869721486
TEDViT is a program behavior visualization system that can reflect explanatory intentions of a teacher by visualizing it in a target world. This system can dynamically reflect changes in variables caused by program behavior in terms of numerical values on objects. However, it is difficult to map the variable values to the position, size, and color of the object. In this study, we implemented a function in TEDViT to dynamically map variable values to object properties. We report an experimental evaluation using 10 subjects.
In programming exercises, a few professors and assistants generally instruct many students. To conduct precise guidance, it is important for professors but difficult to detect the learning situation of each student, s...
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ISBN:
(纸本)9781728139463
In programming exercises, a few professors and assistants generally instruct many students. To conduct precise guidance, it is important for professors but difficult to detect the learning situation of each student, such as whether they are having difficulties in learning. However, there have been no effective methods for extracting occurrences of stumbling that do not result in compilation errors since most existing methods have targeted only those that do. In this research, we aimed at developing methods for detecting when inexperienced students make mistakes in expressing the intended processing as a program (i.e. stumbling in the construction of program logic). In this paper, we initially describe a method we developed for extracting candidates of such stumbling on the basis of an analysis of compilation histories. We also describe methods for estimating such stumbling from among extracted candidates by analyzing transitions in the similarity between source codes. Finally, we describe an experiment done using multiple methods of similarity calculation and discuss the characteristics of our methods on the basis of results.
In programming exercises, a few professors and assistants generally instruct many students. To conduct precise guidance, it is important for professors but difficult to detect the learning situation of each student, s...
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ISBN:
(纸本)9781728139470
In programming exercises, a few professors and assistants generally instruct many students. To conduct precise guidance, it is important for professors but difficult to detect the learning situation of each student, such as whether they are having difficulties in learning. However, there have been no effective methods for extracting occurrences of stumbling that do not result in compilation errors since most existing methods have targeted only those that do. In this research, we aimed at developing methods for detecting when inexperienced students make mistakes in expressing the intended processing as a program (i.e. stumbling in the construction of program logic). In this paper, we initially describe a method we developed for extracting candidates of such stumbling on the basis of an analysis of compilation histories. We also describe methods for estimating such stumbling from among extracted candidates by analyzing transitions in the similarity between source codes. Finally, we describe an experiment done using multiple methods of similarity calculation and discuss the characteristics of our methods on the basis of results.
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