Abstract
In this paper, we report a study of an innovative mobile application to support grading paper-based programming exams. We call the app – Programming Grading Assistant (PGA). It scans pre-generated QR-codes of paper-based question-and-concepts associations and uses OCR to recognize handwritten answers. PGA provides interfaces for teachers to calibrate recognition results, as well as to adjust partial credit assignment according to conceptual incorrectness of the answers. We evaluate the mobile grading process and the quality of grading results based on the assessed semantic information. The results demonstrate that the mobile grading approach keeps persistent traces of students’ performance, including semantic feedback and ultimately enhances grading consistency.
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Notes
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The mobile grading app is currently available upon request.
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- 3.
Source of Java Ontology: http://www.pitt.edu/~paws//ont/java.owl.
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Hsiao, IH. (2016). Mobile Grading Paper-Based Programming Exams: Automatic Semantic Partial Credit Assignment Approach. In: Verbert, K., Sharples, M., KlobuÄŤar, T. (eds) Adaptive and Adaptable Learning. EC-TEL 2016. Lecture Notes in Computer Science(), vol 9891. Springer, Cham. https://doi.org/10.1007/978-3-319-45153-4_9
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