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Automatic evaluation and error identification of solutions to single-variable algebraic questions

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dc.contributor.advisor Ranathunga, S
dc.contributor.advisor Dias, G
dc.contributor.author Erabadda, ELBH
dc.date.accessioned 2017-06-06T08:08:59Z
dc.date.available 2017-06-06T08:08:59Z
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/12788
dc.description.abstract There are two types of single-variable equation solving questions that are present in the Ordinary Level mathematics curriculum in Sri Lanka: linear equations with fractions and quadratic equations. Answers to these questions are open-ended and multi-step in nature. This thesis describes a mechanism that evaluates answers to these two types of questions and awards full/ partial credit. It is quite common that students make mistakes in their answers, which results in partial credit. They may repeat the same errors if they do not receive feedback on their mistakes. Therefore feedback in student errors is important for any subject. This thesis introduces a method to automatically identify the errors that the students make in their answers for the aforementioned two types of questions. To the best of our knowledge, this is the first work on automatically identifying student errors in complex multi-step solutions to single-variable equation solving questions. Our evaluations show that the system we have implemented is capable of awarding full/ partial credit to student answers according to a marking scheme and also to identify errors in student answers with minimal teacher intervention. These evaluations were carried out using student answers from different sources. en_US
dc.language.iso en en_US
dc.subject COMPUTER SCIENCE AND ENGINEERING-Thesis
dc.subject SINGLE-VARIABLE EQUATION SOLVING QUESTIONS
dc.subject Computer aided assessment
dc.subject Error identification
dc.title Automatic evaluation and error identification of solutions to single-variable algebraic questions en_US
dc.type Thesis-Full-text en_US
dc.identifier.faculty Engineering en_US
dc.identifier.degree MSc (Major Component Research) en_US
dc.identifier.department Department of Computer Science & Engineering en_US
dc.date.accept 2017-02
dc.identifier.accno TH3307 en_US


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