research-article

A Neural-Assessment System Based on Emirates (QFE)

Authors:

Fatima Alzahraa Kouka,

Lamees Mohammad Dalbah,

Shaimaa Mahmood Mounir,

Raed Abu ZitarAuthors Info & Claims

ESSE '20: Proceedings of the 2020 European Symposium on Software Engineering

Pages 204 - 210

https://doi.org/10.1145/3393822.3432320

Published: 21 December 2020 Publication History

Abstract

In order to strengthen the teaching and learning phase it is assumed that the assessment of course results dependent upon student grades is important. Our analysis methods and workflows leverage the benefits of AI, for example the capacity to evaluate vast data sets and detect correlations more accurately than humans would use artificial intelligence technologies to help classify large data. It would be used to assess the course learning results based on QF-Emirates (Qualifiers Frame of the United Arab Emirates) criteria with actual data and use it to recommend teaching and learning interventions. We investigate and validate the right neural networks architecture that produces full performance. To that end, a modern algorithm has been improvised. Application to a database to store data and provide data regarding the review of course learning results would be deployed for our suggested recommendation framework. The suggestion method is evaluated and findings are promising as a machine-learning framework. Our neural network based system was able to generate solutions for new cases and provide support in the assessment of courses learning outcomes.

References

[1]

Cambridge dictionary [Online]. Available: https://dictionary.cambridge.org/dictionary/english/intelligence.

[2]

M. Negnevitsky, "Artificial Intelligence a Guide to Intelligent System", ISBN: 0 321 20466 2, May, 2011.

[3]

T. Segaran, "Collective Intelligence", (chapter 12) ISBN-10: 0596529325, August 2007.

[4]

A. Géron, "Hands-on Machine Learning with Scitkit-learn, Keras & TensorFlow Concepts, Tools, and Techniques to Build Intelligent Systems", ISBN: 9781492032632, June, 2019

[5]

S. Ruder, "An overview of gradient descent optimization algorithms" in Insight Centre for Data Analytics, NUI, Galway, 15 January 2017: https://arxiv.org/pdf/1609.04747.pdf.

[6]

A. Elhassan, I. Jenhani, G. B. Brahim," Remedial Actions Recommendation via multi-Label Classification: A Course Learning Improvement Method", International Journal of Machine Learning and Computing, Vol. 8, No. 6, December 2018.

[7]

Medium, https://medium.com/dataseries/7-steps-to-machine-learning-how-to-prepare-for-an-automated-future-78c7918cb35d, accessed: January 2020.

[8]

Intellipaat, https://intellipaat.com/blog/tutorial/artificial-intelligence-tutorial/back-propagation-algorithm/, accessed: January 2020.

[9]

Qualifications Framework for the Emirates Handbook, National Qualifications Authority(NQA)ofUAE", NQA Board, 20 February 2012, 1b1.2012. https://www.khda.gov.ae/CMS/WebParts/TextEditor/Documents/Know_about_National_Qualifications_Framework_QAD_Book_02_Eng.pdf.

[10]

R. Elmasri, S. B. Navathe," Fundamentals of Database Systems"(1st chapter), ISBN 10: 0-136-08620-9, April, 2010.

[11]

Ecompter Notes http://ecomputernotes.com/fundamental/what-is-a-database/strong-and-weak-entity-sets, accessed: January 2020.

[12]

WKU https://www.wku.edu/cs/student_resources/software_links.php, accessed: January 2020.

[13]

Creative Folders, https://www.creativefolders.in/2018/03/microsoft-access-2013-office-2013.html, accessed: January 2020.

[14]

The TechFootPrint, https://rnavagamuwa.com/cool-stuff/tumbling-cube-in-matlab/attachment/8ohuzvqgmw/, accessed: January 2020.

[15]

EXSILOP https://blog.exsilio.com/all/accuracy-precision-recall-f1-score-interpretation-of-performance-measures/, accessed: January 2020.

[16]

Cambridge Dictionary [Online]. Available: https://dictionary.cambridge.org/dictionary/english/intelligence.

[17]

M. Negnevitsky, "Artificial Intelligence a Guide to Intelligent System", ISBN: 0 321 20466 2, May, 2011.

[18]

T. Segaran, "Collective Intelligence", (chapter 12) ISBN-10: 0596529325, August 2007.

[19]

The Tech Foot Print webpage https://rnavagamuwa.com/cool-stuff/tumbling-cube-in-matlab/attachment/8ohuzvqgmw/, accessed: January 2020.

[20]

EXSILOP, https://blog.exsilio.com/all/accuracy-precision-recall-f1-score-interpretation-of-performance-measures/, accessed: January 2020.

[21]

A. F. Nuseirat and R. A. Zitar, Trajectory path planning using hybrid reinforcement and back propagation through time training, International Journal of Cybernetics and Systems, vol.34, no.8, 2003.

[22]

R. A. Zitar and M. H. Hassoun, Neurocontrollers trained with rule extracted by a genetic assisted reinforcement learning system, IEEE Trans. Neural Networks, vol.6, no.4, pp.859--879, 1995.

Digital Library

[23]

M. M. Al-Tahrawi and R. A. Zitar, Polynomial networks versus other techniques in text categorization, International Journal of Pattern Recognition and Artificial Intelligence, vol.22, no.2, pp.295- 322, 2008.

[24]

R. A. Zitar and A. Hamdan, Spam detection using genetic based artificial immune system: A review and a model, Artificial Intelligence Review, 2011.

[25]

R. A. Zitar, Optimum gripper using ant colony intelligence, Industrial Robot Journal, vol.23, no.1, 2004.

[26]

R. A. Zitar and A. M. Al-Fahed Nuseirat, A theoretical approach of an intelligent robot gripper to grasp polygon shaped object, International Journal of Intelligent and Robotic Systems, vol.31, pp.397--422, 2001.

Digital Library

[27]

A. M. Al-Fahed Nuseirat and R. A. Zitar, A neural network approach to optimum grip in the presence of small slips, International Journal of Robotic Systems, vol.18, no.6, pp.305--315, 2001.

Cited By

Zitar R(2022)A Review of the Genetic Algorithm and JAYA Algorithm Applications2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)10.1109/CISP-BMEI56279.2022.9980332(1-7)Online publication date: 5-Nov-2022
https://doi.org/10.1109/CISP-BMEI56279.2022.9980332
Abu Zitar R(2021)A Review for the Genetic Algorithm and the Red Deer Algorithm Applications2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)10.1109/CISP-BMEI53629.2021.9624319(1-6)Online publication date: 23-Oct-2021
https://doi.org/10.1109/CISP-BMEI53629.2021.9624319
Al-Zahra FMounir SDalbah LZitar R(2021)Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System2021 22nd International Arab Conference on Information Technology (ACIT)10.1109/ACIT53391.2021.9677281(1-7)Online publication date: 21-Dec-2021
https://doi.org/10.1109/ACIT53391.2021.9677281

Index Terms

A Neural-Assessment System Based on Emirates (QFE)
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Instance-based learning

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cover image ACM Other conferences

ESSE '20: Proceedings of the 2020 European Symposium on Software Engineering

November 2020

220 pages

ISBN:9781450377621

DOI:10.1145/3393822

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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UNIBO: University of Bologna

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 December 2020

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ESSE 2020

ESSE 2020: 2020 European Symposium on Software Engineering

November 6 - 8, 2020

Rome, Italy

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Cited By

Zitar R(2022)A Review of the Genetic Algorithm and JAYA Algorithm Applications2022 15th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)10.1109/CISP-BMEI56279.2022.9980332(1-7)Online publication date: 5-Nov-2022
https://doi.org/10.1109/CISP-BMEI56279.2022.9980332
Abu Zitar R(2021)A Review for the Genetic Algorithm and the Red Deer Algorithm Applications2021 14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)10.1109/CISP-BMEI53629.2021.9624319(1-6)Online publication date: 23-Oct-2021
https://doi.org/10.1109/CISP-BMEI53629.2021.9624319
Al-Zahra FMounir SDalbah LZitar R(2021)Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System2021 22nd International Arab Conference on Information Technology (ACIT)10.1109/ACIT53391.2021.9677281(1-7)Online publication date: 21-Dec-2021
https://doi.org/10.1109/ACIT53391.2021.9677281

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