Hılles, Shadı

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Hılles, Shadı
Shadı Hılles
HiLLES Shadi
HILLES Shadı
Shadı, Hılles
Hılles, S.
S., Hılles
Shadı HILLES
Hılles Shadı
Hilles S.
Shadi Hilles
Shadi HiLLES
Hilles, Shadi
Hilles Shadi
Hilles, S.
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Doç.Dr.
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shadi.hilles@okan.edu.tr
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    Citation Count: 15
    Blockchain as a decentralized communication tool for sustainable development
    (Institute of Electrical and Electronics Engineers Inc., 2021) Hılles, Shadı; Hatamleh,A.; Aseh,K.; Altrad,A.; Amayreh,K.T.; Hilles,S.; Aledinat,L.S.
    This research introduces the distributed ledger technology (blockchain) in terms of sustainable development in the future. This study is based on private, public and global communications in various industries. The growing demands for secure and decentralized transactions around the world demonstrate the need for Blockchain technology as a medium of operations and communications. The blockchain system is completely decentralized and allows users to exchange messages in an efficient and secure manner. The highlight of the paper is the anticipated future use of blockchain networks as a communication tool in every business and digital economy for a safe and sustainable development, while presenting its advantages and limitations that have been confirmed based on the experiences of various experts. Moreover, the article provides recommendations for the use of blockchain to greatly complicate its identification in future communications. The paper also concludes that the use of the blockchain system could be beneficial and enhance future communications and digital technologies. © 2021 IEEE.
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    Citation Count: 1
    Essay question generator based on bloom's taxonomy for assessing automated essay scoring system
    (Institute of Electrical and Electronics Engineers Inc., 2021) Hılles, Shadı; Hilles,S.; Bakar,Z.A.
    An automated essay scoring system (AES) is advantageous in evaluating student's learning outcomes since it gives them the chance to exhibit their knowledge. Most of the AES is using machine learning (ML) to enhance student's scores but did not consider the proper construction of the essay questions. This study aims to integrate the cognitive level of Blooms' taxonomy (BT) in constructing essay questions and compare the scores of the student. Identifying the most appropriate ML method in classifying essay exam questions (EEQ) based on BT that will be embedded in the Essay Question Generator (EQG). Using F1-Measure, the evaluation results show that the Support Vector Machine (SVM) (85.7%) outperforms Naïve Bayes (82.6%) and K-Nearest Neighbor (77.6%). Therefore, SVM together with the NLP techniques is applied to automatically extract essay questions from the given text for the teachers to select and apply. The EQG was evaluated using the scores of 375 students who answered two sets of essay exam questions using Bloom's Taxonomy (BT) and without Bloom's taxonomy (NBT). Using frequency distribution, the scores between two types were evaluated and the result shows that most students performed well in answering the essay exam using BT 5.6% of the students obtains a perfect score of 5.0 but nobody got 5.0 for NBT. In a conclusion, this study shows that the essay questions constructed according to BT cognitive level produce higher scores using EQG when compared to exam questions prepared by the teachers. © 2021 IEEE.