Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1485
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dc.contributor.authorWickramasinghe, M.L.-
dc.contributor.authorWijethunga, H.P.-
dc.contributor.authorYapa, S.R.-
dc.contributor.authorVishwajith, D.M.D.-
dc.contributor.authorSamaratunge Arachchillage, U.S.S.-
dc.contributor.authorAmarasena, N.-
dc.date.accessioned2022-03-04T04:01:51Z-
dc.date.available2022-03-04T04:01:51Z-
dc.date.issued2020-12-10-
dc.identifier.isbn978-1-7281-8412-8-
dc.identifier.urihttp://rda.sliit.lk/handle/123456789/1485-
dc.description.abstractWorldwide educators considered that, automate the evaluation of programming language-based exams is a more challenging task due to its complexity and the diversity of solutions implemented by students. This research investigates and provides insight into the applicability and development of a java based online exam evaluator as a solution to traditional onerous manual exam assessment methodology. The proposed system allows students to take online exams in Java for an implemented source code in a practical exam, automatically reporting the results to the administrator simultaneously. Accordingly, this research examines existing methods, identifies their limitations, and explores the significance of introducing a smart object-oriented program-based exam evaluator as a solution. This method minimizes all human errors and makes the system more efficient. An automated answer checker checks and marks are given as human-counterpart and generate a report with possible suggestions for improvement of the answer scripts and generate a classification report to predict the student’s final exam marks. This software application uses a Knowledge base, Abstract Syntax tree (AST), ANTLR, Image processing, and Machine Learning (ML) as key technologies. The proposed system gains a higher accuracy of 95% as performed by a separate human-counterpart. These results show a high level of accuracy and automate marking is the major emphasis to save human evaluation effort and maximize productivity.en_US
dc.language.isoenen_US
dc.publisher2020 2nd International Conference on Advancements in Computing (ICAC), SLIITen_US
dc.relation.ispartofseriesVol.1;-
dc.subjectKnowledge baseen_US
dc.subjectAbstract Syntax treeen_US
dc.subjectImage Processingen_US
dc.subjectMachine Learningen_US
dc.subjectANTLRen_US
dc.titleSmart Exam Evaluator for Object-Oriented Programming Modulesen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/ICAC51239.2020.9357320en_US
Appears in Collections:2nd International Conference on Advancements in Computing (ICAC) | 2020
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