Automatic Image Marking Process

Aeman Masbah, Zhongyu Lu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Efficient evaluation of student programs and timely processing of feedback is a critical challenge for faculty. Despite persistent efforts and significant advances in this field, there is still room for improvement. Therefore, the present study aims to analyse the system of automatic assessment and marking of computer science programming students’ assignments in order to save teachers or lecturers time and effort. This is because the answers are marked automatically and the results returned within a very short period of time. The study develops a statistical framework to relate image keywords to image characteristics based on optical character recognition (OCR) and then provides analysis by comparing the students’ submitted answers with the optimal results. This method is based on Latent Semantic Analysis (LSA), and the experimental results achieve high efficiency and more accuracy by using such a simple yet effective technique in automatic marking.
LanguageEnglish
Title of host publicationINFOCOMP 2016 The Sixth International Conference on Advanced Communications and Computation
Place of PublicationValencia, Spain
PublisherInternational Academy, Research, and Industry Association (IARIA)
Pages7-11
Number of pages5
ISBN (Electronic)9781612084787
Publication statusPublished - 22 May 2016
EventThe Sixth International Conference on Advanced Communications and Computation - Holiday Inn Express, Valencia, Spain
Duration: 22 May 201626 May 2016
Conference number: 6
https://www.iaria.org/conferences2016/INFOCOMP16.html (Link to Conference Website )

Publication series

NameINFOCOMP
ISSN (Print)2308-3484

Conference

ConferenceThe Sixth International Conference on Advanced Communications and Computation
Abbreviated titleINFOCOMP 2016
CountrySpain
CityValencia
Period22/05/1626/05/16
Internet address

Fingerprint

Students
Optical character recognition
Computer programming
Computer science
Semantics
Feedback
Processing

Cite this

Masbah, A., & Lu, Z. (2016). Automatic Image Marking Process. In INFOCOMP 2016 The Sixth International Conference on Advanced Communications and Computation (pp. 7-11). (INFOCOMP). Valencia, Spain: International Academy, Research, and Industry Association (IARIA).
Masbah, Aeman ; Lu, Zhongyu. / Automatic Image Marking Process. INFOCOMP 2016 The Sixth International Conference on Advanced Communications and Computation. Valencia, Spain : International Academy, Research, and Industry Association (IARIA), 2016. pp. 7-11 (INFOCOMP).
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Masbah, A & Lu, Z 2016, Automatic Image Marking Process. in INFOCOMP 2016 The Sixth International Conference on Advanced Communications and Computation. INFOCOMP, International Academy, Research, and Industry Association (IARIA), Valencia, Spain, pp. 7-11, The Sixth International Conference on Advanced Communications and Computation, Valencia, Spain, 22/05/16.

Automatic Image Marking Process. / Masbah, Aeman; Lu, Zhongyu.

INFOCOMP 2016 The Sixth International Conference on Advanced Communications and Computation. Valencia, Spain : International Academy, Research, and Industry Association (IARIA), 2016. p. 7-11 (INFOCOMP).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - Efficient evaluation of student programs and timely processing of feedback is a critical challenge for faculty. Despite persistent efforts and significant advances in this field, there is still room for improvement. Therefore, the present study aims to analyse the system of automatic assessment and marking of computer science programming students’ assignments in order to save teachers or lecturers time and effort. This is because the answers are marked automatically and the results returned within a very short period of time. The study develops a statistical framework to relate image keywords to image characteristics based on optical character recognition (OCR) and then provides analysis by comparing the students’ submitted answers with the optimal results. This method is based on Latent Semantic Analysis (LSA), and the experimental results achieve high efficiency and more accuracy by using such a simple yet effective technique in automatic marking.

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Masbah A, Lu Z. Automatic Image Marking Process. In INFOCOMP 2016 The Sixth International Conference on Advanced Communications and Computation. Valencia, Spain: International Academy, Research, and Industry Association (IARIA). 2016. p. 7-11. (INFOCOMP).